1 | # -*- coding: iso-8859-15 -*- |
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2 | #import pylab as plt |
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3 | # From http://stackoverflow.com/questions/13336823/matplotlib-python-error |
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4 | import numpy as np |
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5 | import matplotlib as mpl |
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6 | mpl.use('Agg') |
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7 | import matplotlib.pyplot as plt |
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8 | from mpl_toolkits.basemap import Basemap |
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9 | import os |
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10 | from netCDF4 import Dataset as NetCDFFile |
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11 | import nc_var_tools as ncvar |
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12 | |
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13 | errormsg = 'ERROR -- error -- ERROR -- error' |
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14 | warnmsg = 'WARNING -- waring -- WARNING -- warning' |
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15 | |
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16 | fillValue = 1.e20 |
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17 | fillValueF = 1.e20 |
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18 | |
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19 | ####### Funtions |
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20 | # searchInlist: |
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21 | # datetimeStr_datetime: |
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22 | # dateStr_date: |
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23 | # numVector_String: |
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24 | # timeref_datetime: |
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25 | # slice_variable: Function to return a slice of a given variable according to values to its dimension |
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26 | # interpolate_locs: |
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27 | # datetimeStr_conversion: |
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28 | # percendone: |
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29 | # netCDFdatetime_realdatetime: |
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30 | # file_nlines: |
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31 | # variables_values: |
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32 | # check_colorBar: |
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33 | # units_lunits: |
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34 | # ASCII_LaTeX: |
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35 | # pretty_int: |
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36 | # DegGradSec_deg: |
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37 | # intT2dt: |
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38 | # lonlat_values: |
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39 | # date_CFtime: |
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40 | # pot_values: |
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41 | # CFtimes_plot: |
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42 | # color_lines: |
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43 | # output_kind: |
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44 | # check_arguments: |
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45 | # Str_Bool: |
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46 | # plot_points: |
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47 | # plot_2Dfield: |
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48 | # plot_2Dfield_easy: |
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49 | # plot_topo_geogrid: |
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50 | # plot_topo_geogrid_boxes: |
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51 | # plot_2D_shadow: |
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52 | # plot_2D_shadow_time: Plotting a 2D field with one of the axes being time |
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53 | # plot_Neighbourghood_evol:Plotting neighbourghood evolution# plot_Trajectories |
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54 | # plot_2D_shadow_contour: |
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55 | # plot_2D_shadow_contour_time: |
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56 | # dxdy_lonlat: Function to provide lon/lat 2D lilke-matrices from any sort of dx,dy values |
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57 | # plot_2D_shadow_line: |
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58 | # plot_lines: Function to plot a collection of lines |
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59 | # plot_ZQradii: Function to plot following radial averages only at exact grid poins |
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60 | |
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61 | # From nc_var_tools.py |
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62 | def reduce_spaces(string): |
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63 | """ Function to give words of a line of text removing any extra space |
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64 | """ |
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65 | values = string.replace('\n','').split(' ') |
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66 | vals = [] |
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67 | for val in values: |
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68 | if len(val) > 0: |
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69 | vals.append(val) |
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70 | |
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71 | return vals |
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72 | |
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73 | def searchInlist(listname, nameFind): |
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74 | """ Function to search a value within a list |
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75 | listname = list |
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76 | nameFind = value to find |
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77 | >>> searInlist(['1', '2', '3', '5'], '5') |
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78 | True |
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79 | """ |
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80 | for x in listname: |
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81 | if x == nameFind: |
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82 | return True |
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83 | break |
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84 | return False |
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85 | |
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86 | def datetimeStr_datetime(StringDT): |
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87 | """ Function to transform a string date ([YYYY]-[MM]-[DD]_[HH]:[MI]:[SS] format) to a date object |
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88 | >>> datetimeStr_datetime('1976-02-17_00:00:00') |
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89 | 1976-02-17 00:00:00 |
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90 | """ |
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91 | import datetime as dt |
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92 | |
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93 | fname = 'datetimeStr_datetime' |
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94 | |
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95 | dateD = np.zeros((3), dtype=int) |
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96 | timeT = np.zeros((3), dtype=int) |
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97 | |
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98 | print 'Lluis:',StringDT |
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99 | # quit() |
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100 | |
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101 | dateD[0] = int(StringDT[0:4]) |
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102 | dateD[1] = int(StringDT[5:7]) |
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103 | dateD[2] = int(StringDT[8:10]) |
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104 | |
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105 | trefT = StringDT.find(':') |
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106 | if not trefT == -1: |
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107 | # print ' ' + fname + ': refdate with time!' |
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108 | timeT[0] = int(StringDT[11:13]) |
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109 | timeT[1] = int(StringDT[14:16]) |
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110 | timeT[2] = int(StringDT[17:19]) |
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111 | |
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112 | if int(dateD[0]) == 0: |
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113 | print warnmsg |
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114 | print ' ' + fname + ': 0 reference year!! changing to 1' |
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115 | dateD[0] = 1 |
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116 | |
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117 | newdatetime = dt.datetime(dateD[0], dateD[1], dateD[2], timeT[0], timeT[1], timeT[2]) |
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118 | |
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119 | return newdatetime |
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120 | |
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121 | def dateStr_date(StringDate): |
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122 | """ Function to transform a string date ([YYYY]-[MM]-[DD] format) to a date object |
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123 | >>> dateStr_date('1976-02-17') |
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124 | 1976-02-17 |
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125 | """ |
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126 | import datetime as dt |
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127 | |
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128 | dateD = StringDate.split('-') |
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129 | if int(dateD[0]) == 0: |
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130 | print warnmsg |
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131 | print ' dateStr_date: 0 reference year!! changing to 1' |
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132 | dateD[0] = 1 |
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133 | newdate = dt.date(int(dateD[0]), int(dateD[1]), int(dateD[2])) |
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134 | return newdate |
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135 | |
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136 | def numVector_String(vec,char): |
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137 | """ Function to transform a vector of numbers to a single string [char] separated |
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138 | numVector_String(vec,char) |
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139 | vec= vector with the numerical values |
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140 | char= single character to split the values |
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141 | >>> print numVector_String(np.arange(10),' ') |
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142 | 0 1 2 3 4 5 6 7 8 9 |
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143 | """ |
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144 | fname = 'numVector_String' |
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145 | |
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146 | if vec == 'h': |
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147 | print fname + '_____________________________________________________________' |
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148 | print numVector_String.__doc__ |
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149 | quit() |
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150 | |
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151 | Nvals = len(vec) |
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152 | |
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153 | string='' |
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154 | for i in range(Nvals): |
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155 | if i == 0: |
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156 | string = str(vec[i]) |
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157 | else: |
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158 | string = string + char + str(vec[i]) |
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159 | |
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160 | return string |
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161 | |
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162 | def timeref_datetime(refd, timeval, tu): |
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163 | """ Function to transform from a [timeval] in [tu] units from the time referece [tref] to datetime object |
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164 | refd: time of reference (as datetime object) |
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165 | timeval: time value (as [tu] from [tref]) |
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166 | tu: time units |
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167 | >>> timeref = date(1949,12,1,0,0,0) |
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168 | >>> timeref_datetime(timeref, 229784.36, hours) |
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169 | 1976-02-17 08:21:36 |
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170 | """ |
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171 | import datetime as dt |
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172 | import numpy as np |
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173 | |
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174 | ## Not in timedelta |
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175 | # if tu == 'years': |
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176 | # realdate = refdate + dt.timedelta(years=float(timeval)) |
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177 | # elif tu == 'months': |
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178 | # realdate = refdate + dt.timedelta(months=float(timeval)) |
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179 | if tu == 'weeks': |
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180 | realdate = refd + dt.timedelta(weeks=float(timeval)) |
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181 | elif tu == 'days': |
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182 | realdate = refd + dt.timedelta(days=float(timeval)) |
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183 | elif tu == 'hours': |
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184 | realdate = refd + dt.timedelta(hours=float(timeval)) |
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185 | elif tu == 'minutes': |
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186 | realdate = refd + dt.timedelta(minutes=float(timeval)) |
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187 | elif tu == 'seconds': |
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188 | realdate = refd + dt.timedelta(seconds=float(timeval)) |
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189 | elif tu == 'milliseconds': |
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190 | realdate = refd + dt.timedelta(milliseconds=float(timeval)) |
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191 | else: |
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192 | print errormsg |
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193 | print ' timeref_datetime: time units "' + tu + '" not ready!!!!' |
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194 | quit(-1) |
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195 | |
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196 | return realdate |
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197 | |
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198 | def slice_variable(varobj, dimslice): |
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199 | """ Function to return a slice of a given variable according to values to its |
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200 | dimensions |
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201 | slice_variable(varobj, dims) |
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202 | varobj= object wit the variable |
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203 | dimslice= [[dimname1]:[value1]|[[dimname2]:[value2], ...] pairs of dimension |
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204 | [value]: |
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205 | * [integer]: which value of the dimension |
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206 | * -1: all along the dimension |
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207 | * [beg]:[end] slice from [beg] to [end] |
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208 | * -9: last value of the dimension |
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209 | |
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210 | """ |
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211 | fname = 'slice_variable' |
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212 | |
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213 | if varobj == 'h': |
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214 | print fname + '_____________________________________________________________' |
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215 | print slice_variable.__doc__ |
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216 | quit() |
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217 | |
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218 | vardims = varobj.dimensions |
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219 | Ndimvar = len(vardims) |
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220 | |
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221 | Ndimcut = len(dimslice.split('|')) |
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222 | if Ndimcut == 0: |
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223 | Ndimcut = 1 |
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224 | dimcut = list(dimslice) |
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225 | |
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226 | dimsl = dimslice.split('|') |
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227 | |
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228 | varvalsdim = [] |
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229 | dimnslice = [] |
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230 | monodim = [] |
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231 | for idd in range(Ndimvar): |
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232 | found = False |
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233 | for idc in range(Ndimcut): |
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234 | dimcutn = dimsl[idc].split(':')[0] |
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235 | dimcutv = dimsl[idc].split(':')[1] |
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236 | if vardims[idd] == dimcutn: |
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237 | posfrac = dimcutv.find('@') |
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238 | if posfrac != -1: |
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239 | inifrac = int(dimcutv.split('@')[0]) |
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240 | endfrac = int(dimcutv.split('@')[1]) |
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241 | varvalsdim.append(slice(inifrac,endfrac)) |
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242 | dimnslice.append(vardims[idd]) |
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243 | else: |
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244 | if int(dimcutv) == -1: |
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245 | varvalsdim.append(slice(0,varobj.shape[idd])) |
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246 | dimnslice.append(vardims[idd]) |
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247 | elif int(dimcutv) == -9: |
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248 | varvalsdim.append(varobj.shape[idd]-1) |
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249 | monodim.append(vardims[idd]) |
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250 | else: |
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251 | varvalsdim.append(int(dimcutv)) |
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252 | monodim.append(vardims[idd]) |
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253 | found = True |
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254 | break |
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255 | if not found and not searchInlist(dimnslice,vardims[idd]) and \ |
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256 | not searchInlist(monodim,vardims[idd]): |
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257 | varvalsdim.append(slice(0,varobj.shape[idd])) |
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258 | dimnslice.append(vardims[idd]) |
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259 | varvalues = varobj[tuple(varvalsdim)] |
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260 | |
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261 | varvalues = np.squeeze(varobj[tuple(varvalsdim)]) |
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262 | |
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263 | return varvalues, dimnslice |
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264 | |
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265 | def interpolate_locs(locs,coords,kinterp): |
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266 | """ Function to provide interpolate locations on a given axis |
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267 | interpolate_locs(locs,axis,kinterp) |
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268 | locs= locations to interpolate |
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269 | coords= axis values with the reference of coordinates |
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270 | kinterp: kind of interpolation |
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271 | 'lin': linear |
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272 | >>> coordinates = np.arange((10), dtype=np.float) |
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273 | >>> values = np.array([-1.2, 2.4, 5.6, 7.8, 12.0]) |
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274 | >>> interpolate_locs(values,coordinates,'lin') |
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275 | [ -1.2 2.4 5.6 7.8 13. ] |
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276 | >>> coordinates[0] = 0.5 |
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277 | >>> coordinates[2] = 2.5 |
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278 | >>> interpolate_locs(values,coordinates,'lin') |
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279 | [ -3.4 1.93333333 5.6 7.8 13. ] |
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280 | """ |
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281 | |
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282 | fname = 'interpolate_locs' |
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283 | |
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284 | if locs == 'h': |
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285 | print fname + '_____________________________________________________________' |
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286 | print interpolate_locs.__doc__ |
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287 | quit() |
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288 | |
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289 | Nlocs = locs.shape[0] |
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290 | Ncoords = coords.shape[0] |
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291 | |
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292 | dcoords = coords[Ncoords-1] - coords[0] |
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293 | |
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294 | intlocs = np.zeros((Nlocs), dtype=np.float) |
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295 | minc = np.min(coords) |
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296 | maxc = np.max(coords) |
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297 | |
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298 | for iloc in range(Nlocs): |
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299 | for icor in range(Ncoords-1): |
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300 | if locs[iloc] < minc and dcoords > 0.: |
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301 | a = 0. |
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302 | b = 1. / (coords[1] - coords[0]) |
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303 | c = coords[0] |
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304 | elif locs[iloc] > maxc and dcoords > 0.: |
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305 | a = (Ncoords-1)*1. |
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306 | b = 1. / (coords[Ncoords-1] - coords[Ncoords-2]) |
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307 | c = coords[Ncoords-2] |
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308 | elif locs[iloc] < minc and dcoords < 0.: |
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309 | a = (Ncoords-1)*1. |
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310 | b = 1. / (coords[Ncoords-1] - coords[Ncoords-2]) |
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311 | c = coords[Ncoords-2] |
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312 | elif locs[iloc] > maxc and dcoords < 0.: |
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313 | a = 0. |
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314 | b = 1. / (coords[1] - coords[0]) |
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315 | c = coords[0] |
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316 | elif locs[iloc] >= coords[icor] and locs[iloc] < coords[icor+1] and dcoords > 0.: |
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317 | a = icor*1. |
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318 | b = 1. / (coords[icor+1] - coords[icor]) |
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319 | c = coords[icor] |
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320 | print coords[icor], locs[iloc], coords[icor+1], ':', icor, '->', a, b |
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321 | elif locs[iloc] <= coords[icor] and locs[iloc] > coords[icor+1] and dcoords < 0.: |
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322 | a = icor*1. |
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323 | b = 1. / (coords[icor+1] - coords[icor]) |
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324 | c = coords[icor] |
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325 | |
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326 | if kinterp == 'lin': |
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327 | intlocs[iloc] = a + (locs[iloc] - c)*b |
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328 | else: |
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329 | print errormsg |
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330 | print ' ' + fname + ": interpolation kind '" + kinterp + "' not ready !!!!!" |
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331 | quit(-1) |
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332 | |
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333 | return intlocs |
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334 | |
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335 | def datetimeStr_conversion(StringDT,typeSi,typeSo): |
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336 | """ Function to transform a string date to an another date object |
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337 | StringDT= string with the date and time |
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338 | typeSi= type of datetime string input |
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339 | typeSo= type of datetime string output |
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340 | [typeSi/o] |
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341 | 'cfTime': [time],[units]; ]time in CF-convention format [units] = [tunits] since [refdate] |
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342 | 'matYmdHMS': numerical vector with [[YYYY], [MM], [DD], [HH], [MI], [SS]] |
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343 | 'YmdHMS': [YYYY][MM][DD][HH][MI][SS] format |
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344 | 'Y-m-d_H:M:S': [YYYY]-[MM]-[DD]_[HH]:[MI]:[SS] format |
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345 | 'Y-m-d H:M:S': [YYYY]-[MM]-[DD] [HH]:[MI]:[SS] format |
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346 | 'Y/m/d H-M-S': [YYYY]/[MM]/[DD] [HH]-[MI]-[SS] format |
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347 | 'WRFdatetime': [Y], [Y], [Y], [Y], '-', [M], [M], '-', [D], [D], '_', [H], |
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348 | [H], ':', [M], [M], ':', [S], [S] |
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349 | >>> datetimeStr_conversion('1976-02-17_08:32:05','Y-m-d_H:M:S','matYmdHMS') |
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350 | [1976 2 17 8 32 5] |
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351 | >>> datetimeStr_conversion(str(137880)+',minutes since 1979-12-01_00:00:00','cfTime','Y/m/d H-M-S') |
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352 | 1980/03/05 18-00-00 |
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353 | """ |
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354 | import datetime as dt |
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355 | |
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356 | fname = 'datetimeStr_conversion' |
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357 | |
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358 | if StringDT[0:1] == 'h': |
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359 | print fname + '_____________________________________________________________' |
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360 | print datetimeStr_conversion.__doc__ |
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361 | quit() |
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362 | |
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363 | if typeSi == 'cfTime': |
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364 | timeval = np.float(StringDT.split(',')[0]) |
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365 | tunits = StringDT.split(',')[1].split(' ')[0] |
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366 | Srefdate = StringDT.split(',')[1].split(' ')[2] |
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367 | |
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368 | # Does reference date contain a time value [YYYY]-[MM]-[DD] [HH]:[MI]:[SS] |
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369 | ## |
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370 | yrref=Srefdate[0:4] |
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371 | monref=Srefdate[5:7] |
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372 | dayref=Srefdate[8:10] |
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373 | |
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374 | trefT = Srefdate.find(':') |
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375 | if not trefT == -1: |
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376 | # print ' ' + fname + ': refdate with time!' |
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377 | horref=Srefdate[11:13] |
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378 | minref=Srefdate[14:16] |
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379 | secref=Srefdate[17:19] |
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380 | refdate = datetimeStr_datetime( yrref + '-' + monref + '-' + dayref + \ |
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381 | '_' + horref + ':' + minref + ':' + secref) |
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382 | else: |
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383 | refdate = datetimeStr_datetime( yrref + '-' + monref + '-' + dayref + \ |
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384 | + '_00:00:00') |
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385 | |
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386 | if tunits == 'weeks': |
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387 | newdate = refdate + dt.timedelta(weeks=float(timeval)) |
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388 | elif tunits == 'days': |
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389 | newdate = refdate + dt.timedelta(days=float(timeval)) |
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390 | elif tunits == 'hours': |
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391 | newdate = refdate + dt.timedelta(hours=float(timeval)) |
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392 | elif tunits == 'minutes': |
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393 | newdate = refdate + dt.timedelta(minutes=float(timeval)) |
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394 | elif tunits == 'seconds': |
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395 | newdate = refdate + dt.timedelta(seconds=float(timeval)) |
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396 | elif tunits == 'milliseconds': |
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397 | newdate = refdate + dt.timedelta(milliseconds=float(timeval)) |
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398 | else: |
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399 | print errormsg |
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400 | print ' timeref_datetime: time units "' + tunits + '" not ready!!!!' |
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401 | quit(-1) |
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402 | |
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403 | yr = newdate.year |
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404 | mo = newdate.month |
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405 | da = newdate.day |
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406 | ho = newdate.hour |
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407 | mi = newdate.minute |
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408 | se = newdate.second |
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409 | elif typeSi == 'matYmdHMS': |
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410 | yr = StringDT[0] |
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411 | mo = StringDT[1] |
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412 | da = StringDT[2] |
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413 | ho = StringDT[3] |
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414 | mi = StringDT[4] |
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415 | se = StringDT[5] |
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416 | elif typeSi == 'YmdHMS': |
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417 | yr = int(StringDT[0:4]) |
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418 | mo = int(StringDT[4:6]) |
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419 | da = int(StringDT[6:8]) |
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420 | ho = int(StringDT[8:10]) |
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421 | mi = int(StringDT[10:12]) |
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422 | se = int(StringDT[12:14]) |
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423 | elif typeSi == 'Y-m-d_H:M:S': |
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424 | dateDT = StringDT.split('_') |
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425 | dateD = dateDT[0].split('-') |
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426 | timeT = dateDT[1].split(':') |
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427 | yr = int(dateD[0]) |
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428 | mo = int(dateD[1]) |
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429 | da = int(dateD[2]) |
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430 | ho = int(timeT[0]) |
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431 | mi = int(timeT[1]) |
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432 | se = int(timeT[2]) |
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433 | elif typeSi == 'Y-m-d H:M:S': |
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434 | dateDT = StringDT.split(' ') |
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435 | dateD = dateDT[0].split('-') |
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436 | timeT = dateDT[1].split(':') |
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437 | yr = int(dateD[0]) |
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438 | mo = int(dateD[1]) |
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439 | da = int(dateD[2]) |
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440 | ho = int(timeT[0]) |
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441 | mi = int(timeT[1]) |
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442 | se = int(timeT[2]) |
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443 | elif typeSi == 'Y/m/d H-M-S': |
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444 | dateDT = StringDT.split(' ') |
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445 | dateD = dateDT[0].split('/') |
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446 | timeT = dateDT[1].split('-') |
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447 | yr = int(dateD[0]) |
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448 | mo = int(dateD[1]) |
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449 | da = int(dateD[2]) |
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450 | ho = int(timeT[0]) |
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451 | mi = int(timeT[1]) |
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452 | se = int(timeT[2]) |
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453 | elif typeSi == 'WRFdatetime': |
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454 | yr = int(StringDT[0])*1000 + int(StringDT[1])*100 + int(StringDT[2])*10 + \ |
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455 | int(StringDT[3]) |
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456 | mo = int(StringDT[5])*10 + int(StringDT[6]) |
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457 | da = int(StringDT[8])*10 + int(StringDT[9]) |
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458 | ho = int(StringDT[11])*10 + int(StringDT[12]) |
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459 | mi = int(StringDT[14])*10 + int(StringDT[15]) |
---|
460 | se = int(StringDT[17])*10 + int(StringDT[18]) |
---|
461 | else: |
---|
462 | print errormsg |
---|
463 | print ' ' + fname + ': type of String input date "' + typeSi + \ |
---|
464 | '" not ready !!!!' |
---|
465 | quit(-1) |
---|
466 | |
---|
467 | if typeSo == 'matYmdHMS': |
---|
468 | dateYmdHMS = np.zeros((6), dtype=int) |
---|
469 | dateYmdHMS[0] = yr |
---|
470 | dateYmdHMS[1] = mo |
---|
471 | dateYmdHMS[2] = da |
---|
472 | dateYmdHMS[3] = ho |
---|
473 | dateYmdHMS[4] = mi |
---|
474 | dateYmdHMS[5] = se |
---|
475 | elif typeSo == 'YmdHMS': |
---|
476 | dateYmdHMS = str(yr).zfill(4) + str(mo).zfill(2) + str(da).zfill(2) + \ |
---|
477 | str(ho).zfill(2) + str(mi).zfill(2) + str(se).zfill(2) |
---|
478 | elif typeSo == 'Y-m-d_H:M:S': |
---|
479 | dateYmdHMS = str(yr).zfill(4) + '-' + str(mo).zfill(2) + '-' + \ |
---|
480 | str(da).zfill(2) + '_' + str(ho).zfill(2) + ':' + str(mi).zfill(2) + ':' + \ |
---|
481 | str(se).zfill(2) |
---|
482 | elif typeSo == 'Y-m-d H:M:S': |
---|
483 | dateYmdHMS = str(yr).zfill(4) + '-' + str(mo).zfill(2) + '-' + \ |
---|
484 | str(da).zfill(2) + ' ' + str(ho).zfill(2) + ':' + str(mi).zfill(2) + ':' + \ |
---|
485 | str(se).zfill(2) |
---|
486 | elif typeSo == 'Y/m/d H-M-S': |
---|
487 | dateYmdHMS = str(yr).zfill(4) + '/' + str(mo).zfill(2) + '/' + \ |
---|
488 | str(da).zfill(2) + ' ' + str(ho).zfill(2) + '-' + str(mi).zfill(2) + '-' + \ |
---|
489 | str(se).zfill(2) |
---|
490 | elif typeSo == 'WRFdatetime': |
---|
491 | dateYmdHMS = [] |
---|
492 | yM = yr/1000 |
---|
493 | yC = (yr-yM*1000)/100 |
---|
494 | yD = (yr-yM*1000-yC*100)/10 |
---|
495 | yU = yr-yM*1000-yC*100-yD*10 |
---|
496 | |
---|
497 | mD = mo/10 |
---|
498 | mU = mo-mD*10 |
---|
499 | |
---|
500 | dD = da/10 |
---|
501 | dU = da-dD*10 |
---|
502 | |
---|
503 | hD = ho/10 |
---|
504 | hU = ho-hD*10 |
---|
505 | |
---|
506 | miD = mi/10 |
---|
507 | miU = mi-miD*10 |
---|
508 | |
---|
509 | sD = se/10 |
---|
510 | sU = se-sD*10 |
---|
511 | |
---|
512 | dateYmdHMS.append(str(yM)) |
---|
513 | dateYmdHMS.append(str(yC)) |
---|
514 | dateYmdHMS.append(str(yD)) |
---|
515 | dateYmdHMS.append(str(yU)) |
---|
516 | dateYmdHMS.append('-') |
---|
517 | dateYmdHMS.append(str(mD)) |
---|
518 | dateYmdHMS.append(str(mU)) |
---|
519 | dateYmdHMS.append('-') |
---|
520 | dateYmdHMS.append(str(dD)) |
---|
521 | dateYmdHMS.append(str(dU)) |
---|
522 | dateYmdHMS.append('_') |
---|
523 | dateYmdHMS.append(str(hD)) |
---|
524 | dateYmdHMS.append(str(hU)) |
---|
525 | dateYmdHMS.append(':') |
---|
526 | dateYmdHMS.append(str(miD)) |
---|
527 | dateYmdHMS.append(str(miU)) |
---|
528 | dateYmdHMS.append(':') |
---|
529 | dateYmdHMS.append(str(sD)) |
---|
530 | dateYmdHMS.append(str(sU)) |
---|
531 | else: |
---|
532 | print errormsg |
---|
533 | print ' ' + fname + ': type of output date "' + typeSo + '" not ready !!!!' |
---|
534 | quit(-1) |
---|
535 | |
---|
536 | return dateYmdHMS |
---|
537 | |
---|
538 | def percendone(nvals,tot,percen,msg): |
---|
539 | """ Function to provide the percentage of an action across the matrix |
---|
540 | nvals=number of values |
---|
541 | tot=total number of values |
---|
542 | percen=percentage frequency for which the message is wanted |
---|
543 | msg= message |
---|
544 | """ |
---|
545 | from sys import stdout |
---|
546 | |
---|
547 | num = int(tot * percen/100) |
---|
548 | if (nvals%num == 0): |
---|
549 | print '\r ' + msg + '{0:8.3g}'.format(nvals*100./tot) + ' %', |
---|
550 | stdout.flush() |
---|
551 | |
---|
552 | return '' |
---|
553 | |
---|
554 | def netCDFdatetime_realdatetime(units, tcalendar, times): |
---|
555 | """ Function to transfrom from netCDF CF-compilant times to real time |
---|
556 | """ |
---|
557 | import datetime as dt |
---|
558 | |
---|
559 | txtunits = units.split(' ') |
---|
560 | tunits = txtunits[0] |
---|
561 | Srefdate = txtunits[len(txtunits) - 1] |
---|
562 | |
---|
563 | # Calendar type |
---|
564 | ## |
---|
565 | is360 = False |
---|
566 | if tcalendar is not None: |
---|
567 | print ' netCDFdatetime_realdatetime: There is a calendar attribute' |
---|
568 | if tcalendar == '365_day' or tcalendar == 'noleap': |
---|
569 | print ' netCDFdatetime_realdatetime: No leap years!' |
---|
570 | isleapcal = False |
---|
571 | elif tcalendar == 'proleptic_gregorian' or tcalendar == 'standard' or tcalendar == 'gregorian': |
---|
572 | isleapcal = True |
---|
573 | elif tcalendar == '360_day': |
---|
574 | is360 = True |
---|
575 | isleapcal = False |
---|
576 | else: |
---|
577 | print errormsg |
---|
578 | print ' netCDFdatetime_realdatetime: Calendar "' + tcalendar + '" not prepared!' |
---|
579 | quit(-1) |
---|
580 | |
---|
581 | # Does reference date contain a time value [YYYY]-[MM]-[DD] [HH]:[MI]:[SS] |
---|
582 | ## |
---|
583 | timeval = Srefdate.find(':') |
---|
584 | |
---|
585 | if not timeval == -1: |
---|
586 | print ' netCDFdatetime_realdatetime: refdate with time!' |
---|
587 | refdate = datetimeStr_datetime(Srefdate) |
---|
588 | else: |
---|
589 | refdate = dateStr_date(Srefdate + '_00:00:00') |
---|
590 | |
---|
591 | dimt = len(times) |
---|
592 | # datetype = type(dt.datetime(1972,02,01)) |
---|
593 | # realdates = np.array(dimt, datetype) |
---|
594 | # print realdates |
---|
595 | |
---|
596 | ## Not in timedelta |
---|
597 | # if tunits == 'years': |
---|
598 | # for it in range(dimt): |
---|
599 | # realdate = refdate + dt.timedelta(years=float(times[it])) |
---|
600 | # realdates[it] = int(realdate.year) |
---|
601 | # elif tunits == 'months': |
---|
602 | # for it in range(dimt): |
---|
603 | # realdate = refdate + dt.timedelta(months=float(times[it])) |
---|
604 | # realdates[it] = int(realdate.year) |
---|
605 | # realdates = [] |
---|
606 | realdates = np.zeros((dimt, 6), dtype=int) |
---|
607 | if tunits == 'weeks': |
---|
608 | for it in range(dimt): |
---|
609 | realdate = refdate + dt.timedelta(weeks=float(times[it])) |
---|
610 | realdates[it,:]=[realdate.year, realdate.month, realdate.day, realdate.hour, realdate.minute, realdate.second] |
---|
611 | elif tunits == 'days': |
---|
612 | for it in range(dimt): |
---|
613 | realdate = refdate + dt.timedelta(days=float(times[it])) |
---|
614 | realdates[it,:]=[realdate.year, realdate.month, realdate.day, realdate.hour, realdate.minute, realdate.second] |
---|
615 | elif tunits == 'hours': |
---|
616 | for it in range(dimt): |
---|
617 | realdate = refdate + dt.timedelta(hours=float(times[it])) |
---|
618 | # if not isleapcal: |
---|
619 | # Nleapdays = cal.leapdays(int(refdate.year), int(realdate.year)) |
---|
620 | # realdate = realdate - dt.timedelta(days=Nleapdays) |
---|
621 | # if is360: |
---|
622 | # Nyears360 = int(realdate.year) - int(refdate.year) + 1 |
---|
623 | # realdate = realdate -dt.timedelta(days=Nyears360*5) |
---|
624 | # realdates[it] = realdate |
---|
625 | # realdates = refdate + dt.timedelta(hours=float(times)) |
---|
626 | realdates[it,:]=[realdate.year, realdate.month, realdate.day, realdate.hour, realdate.minute, realdate.second] |
---|
627 | elif tunits == 'minutes': |
---|
628 | for it in range(dimt): |
---|
629 | realdate = refdate + dt.timedelta(minutes=float(times[it])) |
---|
630 | realdates[it,:]=[realdate.year, realdate.month, realdate.day, realdate.hour, realdate.minute, realdate.second] |
---|
631 | elif tunits == 'seconds': |
---|
632 | for it in range(dimt): |
---|
633 | realdate = refdate + dt.timedelta(seconds=float(times[it])) |
---|
634 | realdates[it,:]=[realdate.year, realdate.month, realdate.day, realdate.hour, realdate.minute, realdate.second] |
---|
635 | elif tunits == 'milliseconds': |
---|
636 | for it in range(dimt): |
---|
637 | realdate = refdate + dt.timedelta(milliseconds=float(times[it])) |
---|
638 | realdates[it,:]=[realdate.year, realdate.month, realdate.day, realdate.hour, realdate.minute, realdate.second] |
---|
639 | elif tunits == 'microseconds': |
---|
640 | for it in range(dimt): |
---|
641 | realdate = refdate + dt.timedelta(microseconds=float(times[it])) |
---|
642 | realdates[it,:]=[realdate.year, realdate.month, realdate.day, realdate.hour, realdate.minute, realdate.second] |
---|
643 | else: |
---|
644 | print errormsg |
---|
645 | print ' netCDFdatetime_realdatetime: time units "' + tunits + '" is not ready!!!' |
---|
646 | quit(-1) |
---|
647 | |
---|
648 | return realdates |
---|
649 | |
---|
650 | def file_nlines(filen): |
---|
651 | """ Function to provide the number of lines of a file |
---|
652 | filen= name of the file |
---|
653 | >>> file_nlines('trajectory.dat') |
---|
654 | 49 |
---|
655 | """ |
---|
656 | fname = 'file_nlines' |
---|
657 | |
---|
658 | if not os.path.isfile(filen): |
---|
659 | print errormsg |
---|
660 | print ' ' + fname + ' file: "' + filen + '" does not exist !!' |
---|
661 | quit(-1) |
---|
662 | |
---|
663 | fo = open(filen,'r') |
---|
664 | |
---|
665 | nlines=0 |
---|
666 | for line in fo: nlines = nlines + 1 |
---|
667 | |
---|
668 | fo.close() |
---|
669 | |
---|
670 | return nlines |
---|
671 | |
---|
672 | def realdatetime1_CFcompilant(time, Srefdate, tunits): |
---|
673 | """ Function to transform a matrix with a real time value ([year, month, day, |
---|
674 | hour, minute, second]) to a netCDF one |
---|
675 | time= matrix with time |
---|
676 | Srefdate= reference date ([YYYY][MM][DD][HH][MI][SS] format) |
---|
677 | tunits= units of time respect to Srefdate |
---|
678 | >>> realdatetime1_CFcompilant([1976, 2, 17, 8, 20, 0], '19491201000000', 'hours') |
---|
679 | 229784.33333333 |
---|
680 | """ |
---|
681 | |
---|
682 | import datetime as dt |
---|
683 | yrref=int(Srefdate[0:4]) |
---|
684 | monref=int(Srefdate[4:6]) |
---|
685 | dayref=int(Srefdate[6:8]) |
---|
686 | horref=int(Srefdate[8:10]) |
---|
687 | minref=int(Srefdate[10:12]) |
---|
688 | secref=int(Srefdate[12:14]) |
---|
689 | |
---|
690 | refdate=dt.datetime(yrref, monref, dayref, horref, minref, secref) |
---|
691 | |
---|
692 | if tunits == 'weeks': |
---|
693 | cfdate = dt.datetime(time[0],time[1],time[2],time[3],time[4],time[5])-refdate |
---|
694 | cfdates = (cfdate.days + cfdate.seconds/(3600.*24.))/7. |
---|
695 | elif tunits == 'days': |
---|
696 | cfdate = dt.datetime(time[0],time[1],time[2],time[3],time[4],time[5]) - refdate |
---|
697 | cfdates = cfdate.days + cfdate.seconds/(3600.*24.) |
---|
698 | elif tunits == 'hours': |
---|
699 | cfdate = dt.datetime(time[0],time[1],time[2],time[3],time[4],time[5]) - refdate |
---|
700 | cfdates = cfdate.days*24. + cfdate.seconds/3600. |
---|
701 | elif tunits == 'minutes': |
---|
702 | cfdate = dt.datetime(time[0],time[1],time[2],time[3],time[4],time[5]) - refdate |
---|
703 | cfdates = cfdate.days*24.*60. + cfdate.seconds/60. |
---|
704 | elif tunits == 'seconds': |
---|
705 | cfdate = dt.datetime(time[0],time[1],time[2],time[3],time[4],time[5]) - refdate |
---|
706 | cfdates = cfdate.days*24.*3600. + cfdate.seconds |
---|
707 | elif tunits == 'milliseconds': |
---|
708 | cfdate = dt.datetime(time[0],time[1],time[2],time[3],time[4],time[5]) - refdate |
---|
709 | cfdates = cfdate.days*1000.*24.*3600. + cfdate.seconds*1000. |
---|
710 | elif tunits == 'microseconds': |
---|
711 | cfdate = dt.datetime(time[0],time[1],time[2],time[3],time[4],times[5]) - refdate |
---|
712 | cfdates = cfdate.days*1000000.*24.*3600. + cfdate.seconds*1000000. |
---|
713 | else: |
---|
714 | print errormsg |
---|
715 | print ' ' + fname + ': time units "' + tunits + '" is not ready!!!' |
---|
716 | quit(-1) |
---|
717 | |
---|
718 | return cfdates |
---|
719 | |
---|
720 | def basicvardef(varobj, vstname, vlname, vunits): |
---|
721 | """ Function to give the basic attributes to a variable |
---|
722 | varobj= netCDF variable object |
---|
723 | vstname= standard name of the variable |
---|
724 | vlname= long name of the variable |
---|
725 | vunits= units of the variable |
---|
726 | """ |
---|
727 | attr = varobj.setncattr('standard_name', vstname) |
---|
728 | attr = varobj.setncattr('long_name', vlname) |
---|
729 | attr = varobj.setncattr('units', vunits) |
---|
730 | |
---|
731 | return |
---|
732 | |
---|
733 | def variables_values(varName): |
---|
734 | """ Function to provide values to plot the different variables values from ASCII file |
---|
735 | 'variables_values.dat' |
---|
736 | variables_values(varName) |
---|
737 | [varName]= name of the variable |
---|
738 | return: [var name], [std name], [minimum], [maximum], |
---|
739 | [long name]('|' for spaces), [units], [color palette] (following: |
---|
740 | http://matplotlib.org/1.3.1/examples/color/colormaps_reference.html) |
---|
741 | [varn]: original name of the variable |
---|
742 | NOTE: It might be better doing it with an external ASII file. But then we |
---|
743 | got an extra dependency... |
---|
744 | >>> variables_values('WRFght') |
---|
745 | ['z', 'geopotential_height', 0.0, 80000.0, 'geopotential|height', 'm2s-2', 'rainbow'] |
---|
746 | """ |
---|
747 | import subprocess as sub |
---|
748 | |
---|
749 | fname='variables_values' |
---|
750 | |
---|
751 | if varName == 'h': |
---|
752 | print fname + '_____________________________________________________________' |
---|
753 | print variables_values.__doc__ |
---|
754 | quit() |
---|
755 | |
---|
756 | # This does not work.... |
---|
757 | # folderins = sub.Popen(["pwd"], stdout=sub.PIPE) |
---|
758 | # folder = list(folderins.communicate())[0].replace('\n','') |
---|
759 | # From http://stackoverflow.com/questions/4934806/how-can-i-find-scripts-directory-with-python |
---|
760 | folder = os.path.dirname(os.path.realpath(__file__)) |
---|
761 | |
---|
762 | infile = folder + '/variables_values.dat' |
---|
763 | |
---|
764 | if not os.path.isfile(infile): |
---|
765 | print errormsg |
---|
766 | print ' ' + fname + ": File '" + infile + "' does not exist !!" |
---|
767 | quit(-1) |
---|
768 | |
---|
769 | # Variable name might come with a statistical surname... |
---|
770 | stats=['min','max','mean','stdv', 'sum'] |
---|
771 | |
---|
772 | # Variables with a statistical section on their name... |
---|
773 | NOstatsvars = ['zmaxth', 'zmax_th', 'lmax_th', 'lmaxth'] |
---|
774 | |
---|
775 | ifst = False |
---|
776 | if not searchInlist(NOstatsvars, varName.lower()): |
---|
777 | for st in stats: |
---|
778 | if varName.find(st) > -1: |
---|
779 | print ' '+ fname + ": varibale '" + varName + "' with a " + \ |
---|
780 | "statistical surname: '",st,"' !!" |
---|
781 | Lst = len(st) |
---|
782 | LvarName = len(varName) |
---|
783 | varn = varName[0:LvarName - Lst] |
---|
784 | ifst = True |
---|
785 | break |
---|
786 | if not ifst: |
---|
787 | varn = varName |
---|
788 | |
---|
789 | ncf = open(infile, 'r') |
---|
790 | |
---|
791 | for line in ncf: |
---|
792 | if line[0:1] != '#': |
---|
793 | values = line.replace('\n','').split(',') |
---|
794 | if len(values) != 8: |
---|
795 | print errormsg |
---|
796 | print "problem in varibale:'", values[0], \ |
---|
797 | 'it should have 8 values and it has',len(values) |
---|
798 | quit(-1) |
---|
799 | |
---|
800 | if varn[0:6] == 'varDIM': |
---|
801 | # Variable from a dimension (all with 'varDIM' prefix) |
---|
802 | Lvarn = len(varn) |
---|
803 | varvals = [varn[6:Lvarn+1], varn[6:Lvarn+1], 0., 1., \ |
---|
804 | "variable|from|size|of|dimension|'" + varn[6:Lvarn+1] + "'", '1', \ |
---|
805 | 'rainbow'] |
---|
806 | else: |
---|
807 | varvals = [values[1].replace(' ',''), values[2].replace(' ',''), \ |
---|
808 | np.float(values[3]), np.float(values[4]),values[5].replace(' ',''),\ |
---|
809 | values[6].replace(' ',''), values[7].replace(' ','')] |
---|
810 | if values[0] == varn: |
---|
811 | ncf.close() |
---|
812 | return varvals |
---|
813 | break |
---|
814 | |
---|
815 | print errormsg |
---|
816 | print ' ' + fname + ": variable '" + varn + "' not defined !!!" |
---|
817 | ncf.close() |
---|
818 | quit(-1) |
---|
819 | |
---|
820 | return |
---|
821 | |
---|
822 | def variables_values_old(varName): |
---|
823 | """ Function to provide values to plot the different variables |
---|
824 | variables_values(varName) |
---|
825 | [varName]= name of the variable |
---|
826 | return: [var name], [std name], [minimum], [maximum], |
---|
827 | [long name]('|' for spaces), [units], [color palette] (following: |
---|
828 | http://matplotlib.org/1.3.1/examples/color/colormaps_reference.html) |
---|
829 | [varn]: original name of the variable |
---|
830 | NOTE: It might be better doing it with an external ASII file. But then we |
---|
831 | got an extra dependency... |
---|
832 | >>> variables_values('WRFght') |
---|
833 | ['z', 'geopotential_height', 0.0, 80000.0, 'geopotential|height', 'm2s-2', 'rainbow'] |
---|
834 | """ |
---|
835 | fname='variables_values' |
---|
836 | |
---|
837 | if varName == 'h': |
---|
838 | print fname + '_____________________________________________________________' |
---|
839 | print variables_values.__doc__ |
---|
840 | quit() |
---|
841 | |
---|
842 | # Variable name might come with a statistical surname... |
---|
843 | stats=['min','max','mean','stdv', 'sum'] |
---|
844 | |
---|
845 | ifst = False |
---|
846 | for st in stats: |
---|
847 | if varName.find(st) > -1: |
---|
848 | print ' '+ fname + ": varibale '" + varName + "' with a statistical "+\ |
---|
849 | " surname: '",st,"' !!" |
---|
850 | Lst = len(st) |
---|
851 | LvarName = len(varName) |
---|
852 | varn = varName[0:LvarName - Lst] |
---|
853 | ifst = True |
---|
854 | break |
---|
855 | if not ifst: |
---|
856 | varn = varName |
---|
857 | |
---|
858 | if varn[0:6] == 'varDIM': |
---|
859 | # Variable from a dimension (all with 'varDIM' prefix) |
---|
860 | Lvarn = len(varn) |
---|
861 | varvals = [varn[6:Lvarn+1], varn[6:Lvarn+1], 0., 1., \ |
---|
862 | "variable|from|size|of|dimension|'" + varn[6:Lvarn+1] + "'", '1', 'rainbox'] |
---|
863 | elif varn == 'a_tht' or varn == 'LA_THT': |
---|
864 | varvals = ['ath', 'total_thermal_plume_cover', 0., 1., \ |
---|
865 | 'total|column|thermal|plume|cover', '1', 'YlGnBu'] |
---|
866 | elif varn == 'acprc' or varn == 'RAINC': |
---|
867 | varvals = ['acprc', 'accumulated_cmulus_precipitation', 0., 3.e4, \ |
---|
868 | 'accumulated|cmulus|precipitation', 'mm', 'Blues'] |
---|
869 | elif varn == 'acprnc' or varn == 'RAINNC': |
---|
870 | varvals = ['acprnc', 'accumulated_non-cmulus_precipitation', 0., 3.e4, \ |
---|
871 | 'accumulated|non-cmulus|precipitation', 'mm', 'Blues'] |
---|
872 | elif varn == 'bils' or varn == 'LBILS': |
---|
873 | varvals = ['bils', 'surface_total_heat_flux', -100., 100., \ |
---|
874 | 'surface|total|heat|flux', 'Wm-2', 'seismic'] |
---|
875 | elif varn == 'landcat' or varn == 'category': |
---|
876 | varvals = ['landcat', 'land_categories', 0., 22., 'land|categories', '1', \ |
---|
877 | 'rainbow'] |
---|
878 | elif varn == 'c' or varn == 'QCLOUD' or varn == 'oliq' or varn == 'OLIQ': |
---|
879 | varvals = ['c', 'condensed_water_mixing_ratio', 0., 3.e-4, \ |
---|
880 | 'condensed|water|mixing|ratio', 'kgkg-1', 'BuPu'] |
---|
881 | elif varn == 'ci' or varn == 'iwcon' or varn == 'LIWCON': |
---|
882 | varvals = ['ci', 'cloud_iced_water_mixing_ratio', 0., 0.0003, \ |
---|
883 | 'cloud|iced|water|mixing|ratio', 'kgkg-1', 'Purples'] |
---|
884 | elif varn == 'cl' or varn == 'lwcon' or varn == 'LLWCON': |
---|
885 | varvals = ['cl', 'cloud_liquidwater_mixing_ratio', 0., 0.0003, \ |
---|
886 | 'cloud|liquid|water|mixing|ratio', 'kgkg-1', 'Blues'] |
---|
887 | elif varn == 'cld' or varn == 'CLDFRA' or varn == 'rneb' or varn == 'lrneb' or \ |
---|
888 | varn == 'LRNEB': |
---|
889 | varvals = ['cld', 'cloud_area_fraction', 0., 1., 'cloud|fraction', '1', \ |
---|
890 | 'gist_gray'] |
---|
891 | elif varn == 'cldc' or varn == 'rnebcon' or varn == 'lrnebcon' or \ |
---|
892 | varn == 'LRNEBCON': |
---|
893 | varvals = ['cldc', 'convective_cloud_area_fraction', 0., 1., \ |
---|
894 | 'convective|cloud|fraction', '1', 'gist_gray'] |
---|
895 | elif varn == 'cldl' or varn == 'rnebls' or varn == 'lrnebls' or varn == 'LRNEBLS': |
---|
896 | varvals = ['cldl', 'large_scale_cloud_area_fraction', 0., 1., \ |
---|
897 | 'large|scale|cloud|fraction', '1', 'gist_gray'] |
---|
898 | elif varn == 'clt' or varn == 'CLT' or varn == 'cldt' or \ |
---|
899 | varn == 'Total cloudiness': |
---|
900 | varvals = ['clt', 'cloud_area_fraction', 0., 1., 'total|cloud|cover', '1', \ |
---|
901 | 'gist_gray'] |
---|
902 | elif varn == 'cll' or varn == 'cldl' or varn == 'LCLDL' or \ |
---|
903 | varn == 'Low-level cloudiness': |
---|
904 | varvals = ['cll', 'low_level_cloud_area_fraction', 0., 1., \ |
---|
905 | 'low|level|(p|>|680|hPa)|cloud|fraction', '1', 'gist_gray'] |
---|
906 | elif varn == 'clm' or varn == 'cldm' or varn == 'LCLDM' or \ |
---|
907 | varn == 'Mid-level cloudiness': |
---|
908 | varvals = ['clm', 'mid_level_cloud_area_fraction', 0., 1., \ |
---|
909 | 'medium|level|(440|<|p|<|680|hPa)|cloud|fraction', '1', 'gist_gray'] |
---|
910 | elif varn == 'clh' or varn == 'cldh' or varn == 'LCLDH' or \ |
---|
911 | varn == 'High-level cloudiness': |
---|
912 | varvals = ['clh', 'high_level_cloud_area_fraction', 0., 1., \ |
---|
913 | 'high|level|(p|<|440|hPa)|cloud|fraction', '1', 'gist_gray'] |
---|
914 | elif varn == 'clmf' or varn == 'fbase' or varn == 'LFBASE': |
---|
915 | varvals = ['clmf', 'cloud_base_max_flux', -0.3, 0.3, 'cloud|base|max|flux', \ |
---|
916 | 'kgm-2s-1', 'seismic'] |
---|
917 | elif varn == 'clp' or varn == 'pbase' or varn == 'LPBASE': |
---|
918 | varvals = ['clp', 'cloud_base_pressure', -0.3, 0.3, 'cloud|base|pressure', \ |
---|
919 | 'Pa', 'Reds'] |
---|
920 | elif varn == 'cpt' or varn == 'ptconv' or varn == 'LPTCONV': |
---|
921 | varvals = ['cpt', 'convective_point', 0., 1., 'convective|point', '1', \ |
---|
922 | 'seismic'] |
---|
923 | elif varn == 'dqajs' or varn == 'LDQAJS': |
---|
924 | varvals = ['dqajs', 'dry_adjustment_water_vapor_tendency', -0.0003, 0.0003, \ |
---|
925 | 'dry|adjustment|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
926 | elif varn == 'dqcon' or varn == 'LDQCON': |
---|
927 | varvals = ['dqcon', 'convective_water_vapor_tendency', -3e-8, 3.e-8, \ |
---|
928 | 'convective|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
929 | elif varn == 'dqdyn' or varn == 'LDQDYN': |
---|
930 | varvals = ['dqdyn', 'dynamics_water_vapor_tendency', -3.e-7, 3.e-7, \ |
---|
931 | 'dynamics|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
932 | elif varn == 'dqeva' or varn == 'LDQEVA': |
---|
933 | varvals = ['dqeva', 'evaporation_water_vapor_tendency', -3.e-6, 3.e-6, \ |
---|
934 | 'evaporation|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
935 | elif varn == 'dqlscst' or varn == 'LDQLSCST': |
---|
936 | varvals = ['dqlscst', 'stratocumulus_water_vapor_tendency', -3.e-7, 3.e-7, \ |
---|
937 | 'stratocumulus|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
938 | elif varn == 'dqlscth' or varn == 'LDQLSCTH': |
---|
939 | varvals = ['dqlscth', 'thermals_water_vapor_tendency', -3.e-7, 3.e-7, \ |
---|
940 | 'thermal|plumes|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
941 | elif varn == 'dqlsc' or varn == 'LDQLSC': |
---|
942 | varvals = ['dqlsc', 'condensation_water_vapor_tendency', -3.e-6, 3.e-6, \ |
---|
943 | 'condensation|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
944 | elif varn == 'dqphy' or varn == 'LDQPHY': |
---|
945 | varvals = ['dqphy', 'physics_water_vapor_tendency', -3.e-7, 3.e-7, \ |
---|
946 | 'physics|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
947 | elif varn == 'dqthe' or varn == 'LDQTHE': |
---|
948 | varvals = ['dqthe', 'thermals_water_vapor_tendency', -3.e-7, 3.e-7, \ |
---|
949 | 'thermal|plumes|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
950 | elif varn == 'dqvdf' or varn == 'LDQVDF': |
---|
951 | varvals = ['dqvdf', 'vertical_difussion_water_vapor_tendency', -3.e-8, 3.e-8,\ |
---|
952 | 'vertical|difussion|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
953 | elif varn == 'dqwak' or varn == 'LDQWAK': |
---|
954 | varvals = ['dqwak', 'wake_water_vapor_tendency', -3.e-7, 3.e-7, \ |
---|
955 | 'wake|water|vapor|tendency', 'kg/kg/s', 'seismic'] |
---|
956 | elif varn == 'dta' or varn == 'tnt' or varn == 'LTNT': |
---|
957 | varvals = ['dta', 'tendency_air_temperature', -3.e-3, 3.e-3, \ |
---|
958 | 'tendency|of|air|temperature', 'K/s', 'seismic'] |
---|
959 | elif varn == 'dtac' or varn == 'tntc' or varn == 'LTNTC': |
---|
960 | varvals = ['dtac', 'moist_convection_tendency_air_temperature', -3.e-3, \ |
---|
961 | 3.e-3, 'moist|convection|tendency|of|air|temperature', 'K/s', 'seismic'] |
---|
962 | elif varn == 'dtar' or varn == 'tntr' or varn == 'LTNTR': |
---|
963 | varvals = ['dtar', 'radiative_heating_tendency_air_temperature', -3.e-3, \ |
---|
964 | 3.e-3, 'radiative|heating|tendency|of|air|temperature', 'K/s', 'seismic'] |
---|
965 | elif varn == 'dtascpbl' or varn == 'tntscpbl' or varn == 'LTNTSCPBL': |
---|
966 | varvals = ['dtascpbl', \ |
---|
967 | 'stratiform_cloud_precipitation_BL_mixing_tendency_air_temperature', \ |
---|
968 | -3.e-6, 3.e-6, \ |
---|
969 | 'stratiform|cloud|precipitation|Boundary|Layer|mixing|tendency|air|' + |
---|
970 | 'temperature', 'K/s', 'seismic'] |
---|
971 | elif varn == 'dtajs' or varn == 'LDTAJS': |
---|
972 | varvals = ['dtajs', 'dry_adjustment_thermal_tendency', -3.e-5, 3.e-5, \ |
---|
973 | 'dry|adjustment|thermal|tendency', 'K/s', 'seismic'] |
---|
974 | elif varn == 'dtcon' or varn == 'LDTCON': |
---|
975 | varvals = ['dtcon', 'convective_thermal_tendency', -3.e-5, 3.e-5, \ |
---|
976 | 'convective|thermal|tendency', 'K/s', 'seismic'] |
---|
977 | elif varn == 'dtdyn' or varn == 'LDTDYN': |
---|
978 | varvals = ['dtdyn', 'dynamics_thermal_tendency', -3.e-4, 3.e-4, \ |
---|
979 | 'dynamics|thermal|tendency', 'K/s', 'seismic'] |
---|
980 | elif varn == 'dteva' or varn == 'LDTEVA': |
---|
981 | varvals = ['dteva', 'evaporation_thermal_tendency', -3.e-3, 3.e-3, \ |
---|
982 | 'evaporation|thermal|tendency', 'K/s', 'seismic'] |
---|
983 | elif varn == 'dtlscst' or varn == 'LDTLSCST': |
---|
984 | varvals = ['dtlscst', 'stratocumulus_thermal_tendency', -3.e-4, 3.e-4, \ |
---|
985 | 'stratocumulus|thermal|tendency', 'K/s', 'seismic'] |
---|
986 | elif varn == 'dtlscth' or varn == 'LDTLSCTH': |
---|
987 | varvals = ['dtlscth', 'thermals_thermal_tendency', -3.e-4, 3.e-4, \ |
---|
988 | 'thermal|plumes|thermal|tendency', 'K/s', 'seismic'] |
---|
989 | elif varn == 'dtlsc' or varn == 'LDTLSC': |
---|
990 | varvals = ['dtlsc', 'condensation_thermal_tendency', -3.e-3, 3.e-3, \ |
---|
991 | 'condensation|thermal|tendency', 'K/s', 'seismic'] |
---|
992 | elif varn == 'dtlwr' or varn == 'LDTLWR': |
---|
993 | varvals = ['dtlwr', 'long_wave_thermal_tendency', -3.e-3, 3.e-3, \ |
---|
994 | 'long|wave|radiation|thermal|tendency', 'K/s', 'seismic'] |
---|
995 | elif varn == 'dtphy' or varn == 'LDTPHY': |
---|
996 | varvals = ['dtphy', 'physics_thermal_tendency', -3.e-4, 3.e-4, \ |
---|
997 | 'physics|thermal|tendency', 'K/s', 'seismic'] |
---|
998 | elif varn == 'dtsw0' or varn == 'LDTSW0': |
---|
999 | varvals = ['dtsw0', 'cloudy_sky_short_wave_thermal_tendency', -3.e-4, 3.e-4, \ |
---|
1000 | 'cloudy|sky|short|wave|radiation|thermal|tendency', 'K/s', 'seismic'] |
---|
1001 | elif varn == 'dtthe' or varn == 'LDTTHE': |
---|
1002 | varvals = ['dtthe', 'thermals_thermal_tendency', -3.e-4, 3.e-4, \ |
---|
1003 | 'thermal|plumes|thermal|tendency', 'K/s', 'seismic'] |
---|
1004 | elif varn == 'dtvdf' or varn == 'LDTVDF': |
---|
1005 | varvals = ['dtvdf', 'vertical_difussion_thermal_tendency', -3.e-5, 3.e-5, \ |
---|
1006 | 'vertical|difussion|thermal|tendency', 'K/s', 'seismic'] |
---|
1007 | elif varn == 'dtwak' or varn == 'LDTWAK': |
---|
1008 | varvals = ['dtwak', 'wake_thermal_tendency', -3.e-4, 3.e-4, \ |
---|
1009 | 'wake|thermal|tendency', 'K/s', 'seismic'] |
---|
1010 | elif varn == 'ducon' or varn == 'LDUCON': |
---|
1011 | varvals = ['ducon', 'convective_eastward_wind_tendency', -3.e-3, 3.e-3, \ |
---|
1012 | 'convective|eastward|wind|tendency', 'ms-2', 'seismic'] |
---|
1013 | elif varn == 'dudyn' or varn == 'LDUDYN': |
---|
1014 | varvals = ['dudyn', 'dynamics_eastward_wind_tendency', -3.e-3, 3.e-3, \ |
---|
1015 | 'dynamics|eastward|wind|tendency', 'ms-2', 'seismic'] |
---|
1016 | elif varn == 'duvdf' or varn == 'LDUVDF': |
---|
1017 | varvals = ['duvdf', 'vertical_difussion_eastward_wind_tendency', -3.e-3, \ |
---|
1018 | 3.e-3, 'vertical|difussion|eastward|wind|tendency', 'ms-2', 'seismic'] |
---|
1019 | elif varn == 'dvcon' or varn == 'LDVCON': |
---|
1020 | varvals = ['dvcon', 'convective_difussion_northward_wind_tendency', -3.e-3, \ |
---|
1021 | 3.e-3, 'convective|northward|wind|tendency', 'ms-2', 'seismic'] |
---|
1022 | elif varn == 'dvdyn' or varn == 'LDVDYN': |
---|
1023 | varvals = ['dvdyn', 'dynamics_northward_wind_tendency', -3.e-3, \ |
---|
1024 | 3.e-3, 'dynamics|difussion|northward|wind|tendency', 'ms-2', 'seismic'] |
---|
1025 | elif varn == 'dvvdf' or varn == 'LDVVDF': |
---|
1026 | varvals = ['dvvdf', 'vertical_difussion_northward_wind_tendency', -3.e-3, \ |
---|
1027 | 3.e-3, 'vertical|difussion|northward|wind|tendency', 'ms-2', 'seismic'] |
---|
1028 | elif varn == 'etau' or varn == 'ZNU': |
---|
1029 | varvals = ['etau', 'etau', 0., 1, 'eta values on half (mass) levels', '-', \ |
---|
1030 | 'reds'] |
---|
1031 | elif varn == 'evspsbl' or varn == 'LEVAP' or varn == 'evap' or varn == 'SFCEVPde': |
---|
1032 | varvals = ['evspsbl', 'water_evaporation_flux', 0., 1.5e-4, \ |
---|
1033 | 'water|evaporation|flux', 'kgm-2s-1', 'Blues'] |
---|
1034 | elif varn == 'evspsbl' or varn == 'SFCEVPde': |
---|
1035 | varvals = ['evspsblac', 'water_evaporation_flux_ac', 0., 1.5e-4, \ |
---|
1036 | 'accumulated|water|evaporation|flux', 'kgm-2', 'Blues'] |
---|
1037 | elif varn == 'g' or varn == 'QGRAUPEL': |
---|
1038 | varvals = ['g', 'grauepl_mixing_ratio', 0., 0.0003, 'graupel|mixing|ratio', \ |
---|
1039 | 'kgkg-1', 'Purples'] |
---|
1040 | elif varn == 'h2o' or varn == 'LH2O': |
---|
1041 | varvals = ['h2o', 'water_mass_fraction', 0., 3.e-2, \ |
---|
1042 | 'mass|fraction|of|water', '1', 'Blues'] |
---|
1043 | elif varn == 'h' or varn == 'QHAIL': |
---|
1044 | varvals = ['h', 'hail_mixing_ratio', 0., 0.0003, 'hail|mixing|ratio', \ |
---|
1045 | 'kgkg-1', 'Purples'] |
---|
1046 | elif varn == 'hfls' or varn == 'LH' or varn == 'LFLAT' or varn == 'flat': |
---|
1047 | varvals = ['hfls', 'surface_upward_latent_heat_flux', -400., 400., \ |
---|
1048 | 'upward|latnt|heat|flux|at|the|surface', 'Wm-2', 'seismic'] |
---|
1049 | elif varn == 'hfss' or varn == 'LSENS' or varn == 'sens' or varn == 'HFX': |
---|
1050 | varvals = ['hfss', 'surface_upward_sensible_heat_flux', -150., 150., \ |
---|
1051 | 'upward|sensible|heat|flux|at|the|surface', 'Wm-2', 'seismic'] |
---|
1052 | elif varn == 'hfso' or varn == 'GRDFLX': |
---|
1053 | varvals = ['hfso', 'downward_heat_flux_in_soil', -150., 150., \ |
---|
1054 | 'Downward|soil|heat|flux', 'Wm-2', 'seismic'] |
---|
1055 | elif varn == 'hus' or varn == 'WRFrh' or varn == 'LMDZrh' or varn == 'rhum' or \ |
---|
1056 | varn == 'LRHUM': |
---|
1057 | varvals = ['hus', 'specific_humidity', 0., 1., 'specific|humidty', '1', \ |
---|
1058 | 'BuPu'] |
---|
1059 | elif varn == 'huss' or varn == 'WRFrhs' or varn == 'LMDZrhs' or varn == 'rh2m' or\ |
---|
1060 | varn == 'LRH2M': |
---|
1061 | varvals = ['huss', 'specific_humidity', 0., 1., 'specific|humidty|at|2m', \ |
---|
1062 | '1', 'BuPu'] |
---|
1063 | elif varn == 'i' or varn == 'QICE': |
---|
1064 | varvals = ['i', 'iced_water_mixing_ratio', 0., 0.0003, \ |
---|
1065 | 'iced|water|mixing|ratio', 'kgkg-1', 'Purples'] |
---|
1066 | elif varn == 'lat' or varn == 'XLAT' or varn == 'XLAT_M' or varn == 'latitude': |
---|
1067 | varvals = ['lat', 'latitude', -90., 90., 'latitude', 'degrees North', \ |
---|
1068 | 'seismic'] |
---|
1069 | elif varn == 'lcl' or varn == 's_lcl' or varn == 'ls_lcl' or varn == 'LS_LCL': |
---|
1070 | varvals = ['lcl', 'condensation_level', 0., 2500., 'level|of|condensation', \ |
---|
1071 | 'm', 'Greens'] |
---|
1072 | elif varn == 'lambdath' or varn == 'lambda_th' or varn == 'LLAMBDA_TH': |
---|
1073 | varvals = ['lambdath', 'thermal_plume_vertical_velocity', -30., 30., \ |
---|
1074 | 'thermal|plume|vertical|velocity', 'm/s', 'seismic'] |
---|
1075 | elif varn == 'lmaxth' or varn == 'LLMAXTH': |
---|
1076 | varvals = ['lmaxth', 'upper_level_thermals', 0., 100., 'upper|level|thermals'\ |
---|
1077 | , '1', 'Greens'] |
---|
1078 | elif varn == 'lon' or varn == 'XLONG' or varn == 'XLONG_M': |
---|
1079 | varvals = ['lon', 'longitude', -180., 180., 'longitude', 'degrees East', \ |
---|
1080 | 'seismic'] |
---|
1081 | elif varn == 'longitude': |
---|
1082 | varvals = ['lon', 'longitude', 0., 360., 'longitude', 'degrees East', \ |
---|
1083 | 'seismic'] |
---|
1084 | elif varn == 'orog' or varn == 'HGT' or varn == 'HGT_M': |
---|
1085 | varvals = ['orog', 'orography', 0., 3000., 'surface|altitude', 'm','terrain'] |
---|
1086 | elif varn == 'pfc' or varn == 'plfc' or varn == 'LPLFC': |
---|
1087 | varvals = ['pfc', 'pressure_free_convection', 100., 1100., \ |
---|
1088 | 'pressure|free|convection', 'hPa', 'BuPu'] |
---|
1089 | elif varn == 'plcl' or varn == 'LPLCL': |
---|
1090 | varvals = ['plcl', 'pressure_lifting_condensation_level', 700., 1100., \ |
---|
1091 | 'pressure|lifting|condensation|level', 'hPa', 'BuPu'] |
---|
1092 | elif varn == 'pr' or varn == 'RAINTOT' or varn == 'precip' or \ |
---|
1093 | varn == 'LPRECIP' or varn == 'Precip Totale liq+sol': |
---|
1094 | varvals = ['pr', 'precipitation_flux', 0., 1.e-4, 'precipitation|flux', \ |
---|
1095 | 'kgm-2s-1', 'BuPu'] |
---|
1096 | elif varn == 'prprof' or varn == 'vprecip' or varn == 'LVPRECIP': |
---|
1097 | varvals = ['prprof', 'precipitation_profile', 0., 1.e-3, \ |
---|
1098 | 'precipitation|profile', 'kg/m2/s', 'BuPu'] |
---|
1099 | elif varn == 'prprofci' or varn == 'pr_con_i' or varn == 'LPR_CON_I': |
---|
1100 | varvals = ['prprofci', 'precipitation_profile_convective_i', 0., 1.e-3, \ |
---|
1101 | 'precipitation|profile|convective|i', 'kg/m2/s', 'BuPu'] |
---|
1102 | elif varn == 'prprofcl' or varn == 'pr_con_l' or varn == 'LPR_CON_L': |
---|
1103 | varvals = ['prprofcl', 'precipitation_profile_convective_l', 0., 1.e-3, \ |
---|
1104 | 'precipitation|profile|convective|l', 'kg/m2/s', 'BuPu'] |
---|
1105 | elif varn == 'prprofli' or varn == 'pr_lsc_i' or varn == 'LPR_LSC_I': |
---|
1106 | varvals = ['prprofli', 'precipitation_profile_large_scale_i', 0., 1.e-3, \ |
---|
1107 | 'precipitation|profile|large|scale|i', 'kg/m2/s', 'BuPu'] |
---|
1108 | elif varn == 'prprofll' or varn == 'pr_lsc_l' or varn == 'LPR_LSC_L': |
---|
1109 | varvals = ['prprofll', 'precipitation_profile_large_scale_l', 0., 1.e-3, \ |
---|
1110 | 'precipitation|profile|large|scale|l', 'kg/m2/s', 'BuPu'] |
---|
1111 | elif varn == 'pracc' or varn == 'ACRAINTOT': |
---|
1112 | varvals = ['pracc', 'precipitation_amount', 0., 100., \ |
---|
1113 | 'accumulated|precipitation', 'kgm-2', 'BuPu'] |
---|
1114 | elif varn == 'prc' or varn == 'LPLUC' or varn == 'pluc' or varn == 'WRFprc' or \ |
---|
1115 | varn == 'RAINCde': |
---|
1116 | varvals = ['prc', 'convective_precipitation_flux', 0., 2.e-4, \ |
---|
1117 | 'convective|precipitation|flux', 'kgm-2s-1', 'Blues'] |
---|
1118 | elif varn == 'prci' or varn == 'pr_con_i' or varn == 'LPR_CON_I': |
---|
1119 | varvals = ['prci', 'convective_ice_precipitation_flux', 0., 0.003, \ |
---|
1120 | 'convective|ice|precipitation|flux', 'kgm-2s-1', 'Purples'] |
---|
1121 | elif varn == 'prcl' or varn == 'pr_con_l' or varn == 'LPR_CON_L': |
---|
1122 | varvals = ['prcl', 'convective_liquid_precipitation_flux', 0., 0.003, \ |
---|
1123 | 'convective|liquid|precipitation|flux', 'kgm-2s-1', 'Blues'] |
---|
1124 | elif varn == 'pres' or varn == 'presnivs' or varn == 'pressure' or \ |
---|
1125 | varn == 'lpres' or varn == 'LPRES': |
---|
1126 | varvals = ['pres', 'air_pressure', 0., 103000., 'air|pressure', 'Pa', \ |
---|
1127 | 'Blues'] |
---|
1128 | elif varn == 'prls' or varn == 'WRFprls' or varn == 'LPLUL' or varn == 'plul' or \ |
---|
1129 | varn == 'RAINNCde': |
---|
1130 | varvals = ['prls', 'large_scale_precipitation_flux', 0., 2.e-4, \ |
---|
1131 | 'large|scale|precipitation|flux', 'kgm-2s-1', 'Blues'] |
---|
1132 | elif varn == 'prsn' or varn == 'SNOW' or varn == 'snow' or varn == 'LSNOW': |
---|
1133 | varvals = ['prsn', 'snowfall', 0., 1.e-4, 'snowfall|flux', 'kgm-2s-1', 'BuPu'] |
---|
1134 | elif varn == 'prw' or varn == 'WRFprh': |
---|
1135 | varvals = ['prw', 'atmosphere_water_vapor_content', 0., 10., \ |
---|
1136 | 'water|vapor"path', 'kgm-2', 'Blues'] |
---|
1137 | elif varn == 'ps' or varn == 'psfc' or varn =='PSFC' or varn == 'psol' or \ |
---|
1138 | varn == 'Surface Pressure': |
---|
1139 | varvals=['ps', 'surface_air_pressure', 85000., 105400., 'surface|pressure', \ |
---|
1140 | 'hPa', 'cool'] |
---|
1141 | elif varn == 'psl' or varn == 'mslp' or varn =='WRFmslp': |
---|
1142 | varvals=['psl', 'air_pressure_at_sea_level', 85000., 104000., \ |
---|
1143 | 'mean|sea|level|pressure', 'Pa', 'Greens'] |
---|
1144 | elif varn == 'qth' or varn == 'q_th' or varn == 'LQ_TH': |
---|
1145 | varvals = ['qth', 'thermal_plume_total_water_content', 0., 25., \ |
---|
1146 | 'total|water|cotent|in|thermal|plume', 'mm', 'YlOrRd'] |
---|
1147 | elif varn == 'r' or varn == 'QVAPOR' or varn == 'ovap' or varn == 'LOVAP': |
---|
1148 | varvals = ['r', 'water_mixing_ratio', 0., 0.03, 'water|mixing|ratio', \ |
---|
1149 | 'kgkg-1', 'BuPu'] |
---|
1150 | elif varn == 'r2' or varn == 'Q2': |
---|
1151 | varvals = ['r2', 'water_mixing_ratio_at_2m', 0., 0.03, 'water|mixing|' + \ |
---|
1152 | 'ratio|at|2|m','kgkg-1', 'BuPu'] |
---|
1153 | elif varn == 'rsds' or varn == 'SWdnSFC' or varn == 'SWdn at surface' or \ |
---|
1154 | varn == 'SWDOWN': |
---|
1155 | varvals=['rsds', 'surface_downwelling_shortwave_flux_in_air', 0., 1200., \ |
---|
1156 | 'downward|SW|surface|radiation', 'Wm-2' ,'Reds'] |
---|
1157 | elif varn == 'rsdsacc': |
---|
1158 | varvals=['rsdsacc', 'accumulated_surface_downwelling_shortwave_flux_in_air', \ |
---|
1159 | 0., 1200., 'accumulated|downward|SW|surface|radiation', 'Wm-2' ,'Reds'] |
---|
1160 | elif varn == 'rvor' or varn == 'WRFrvor': |
---|
1161 | varvals = ['rvor', 'air_relative_vorticity', -2.5E-3, 2.5E-3, \ |
---|
1162 | 'air|relative|vorticity', 's-1', 'seismic'] |
---|
1163 | elif varn == 'rvors' or varn == 'WRFrvors': |
---|
1164 | varvals = ['rvors', 'surface_air_relative_vorticity', -2.5E-3, 2.5E-3, \ |
---|
1165 | 'surface|air|relative|vorticity', 's-1', 'seismic'] |
---|
1166 | elif varn == 's' or varn == 'QSNOW': |
---|
1167 | varvals = ['s', 'snow_mixing_ratio', 0., 0.0003, 'snow|mixing|ratio', \ |
---|
1168 | 'kgkg-1', 'Purples'] |
---|
1169 | elif varn == 'stherm' or varn == 'LS_THERM': |
---|
1170 | varvals = ['stherm', 'thermals_excess', 0., 0.8, 'thermals|excess', 'K', \ |
---|
1171 | 'Reds'] |
---|
1172 | elif varn == 'ta' or varn == 'WRFt' or varn == 'temp' or varn == 'LTEMP' or \ |
---|
1173 | varn == 'Air temperature': |
---|
1174 | varvals = ['ta', 'air_temperature', 195., 320., 'air|temperature', 'K', \ |
---|
1175 | 'YlOrRd'] |
---|
1176 | elif varn == 'tah' or varn == 'theta' or varn == 'LTHETA': |
---|
1177 | varvals = ['tah', 'potential_air_temperature', 195., 320., \ |
---|
1178 | 'potential|air|temperature', 'K', 'YlOrRd'] |
---|
1179 | elif varn == 'tas' or varn == 'T2' or varn == 't2m' or varn == 'T2M' or \ |
---|
1180 | varn == 'Temperature 2m': |
---|
1181 | varvals = ['tas', 'air_temperature', 240., 310., 'air|temperature|at|2m', ' \ |
---|
1182 | K', 'YlOrRd'] |
---|
1183 | elif varn == 'tds' or varn == 'TH2': |
---|
1184 | varvals = ['tds', 'air_dew_point_temperature', 240., 310., \ |
---|
1185 | 'air|dew|point|temperature|at|2m', 'K', 'YlGnBu'] |
---|
1186 | elif varn == 'tke' or varn == 'TKE' or varn == 'tke' or varn == 'LTKE': |
---|
1187 | varvals = ['tke', 'turbulent_kinetic_energy', 0., 0.003, \ |
---|
1188 | 'turbulent|kinetic|energy', 'm2/s2', 'Reds'] |
---|
1189 | elif varn == 'time'or varn == 'time_counter': |
---|
1190 | varvals = ['time', 'time', 0., 1000., 'time', \ |
---|
1191 | 'hours|since|1949/12/01|00:00:00', 'Reds'] |
---|
1192 | elif varn == 'tmla' or varn == 's_pblt' or varn == 'LS_PBLT': |
---|
1193 | varvals = ['tmla', 'atmosphere_top_boundary_layer_temperature', 250., 330., \ |
---|
1194 | 'atmosphere|top|boundary|layer|temperature', 'K', 'Reds'] |
---|
1195 | elif varn == 'ua' or varn == 'vitu' or varn == 'U' or varn == 'Zonal wind' or \ |
---|
1196 | varn == 'LVITU': |
---|
1197 | varvals = ['ua', 'eastward_wind', -30., 30., 'eastward|wind', 'ms-1', \ |
---|
1198 | 'seismic'] |
---|
1199 | elif varn == 'uas' or varn == 'u10m' or varn == 'U10' or varn =='Vent zonal 10m': |
---|
1200 | varvals = ['uas', 'eastward_wind', -30., 30., 'eastward|2m|wind', \ |
---|
1201 | 'ms-1', 'seismic'] |
---|
1202 | elif varn == 'va' or varn == 'vitv' or varn == 'V' or varn == 'Meridional wind' \ |
---|
1203 | or varn == 'LVITV': |
---|
1204 | varvals = ['va', 'northward_wind', -30., 30., 'northward|wind', 'ms-1', \ |
---|
1205 | 'seismic'] |
---|
1206 | elif varn == 'vas' or varn == 'v10m' or varn == 'V10' or \ |
---|
1207 | varn =='Vent meridien 10m': |
---|
1208 | varvals = ['vas', 'northward_wind', -30., 30., 'northward|2m|wind', 'ms-1', \ |
---|
1209 | 'seismic'] |
---|
1210 | elif varn == 'wakedeltaq' or varn == 'wake_deltaq' or varn == 'lwake_deltaq' or \ |
---|
1211 | varn == 'LWAKE_DELTAQ': |
---|
1212 | varvals = ['wakedeltaq', 'wake_delta_vapor', -0.003, 0.003, \ |
---|
1213 | 'wake|delta|mixing|ratio', '-', 'seismic'] |
---|
1214 | elif varn == 'wakedeltat' or varn == 'wake_deltat' or varn == 'lwake_deltat' or \ |
---|
1215 | varn == 'LWAKE_DELTAT': |
---|
1216 | varvals = ['wakedeltat', 'wake_delta_temp', -0.003, 0.003, \ |
---|
1217 | 'wake|delta|temperature', '-', 'seismic'] |
---|
1218 | elif varn == 'wakeh' or varn == 'wake_h' or varn == 'LWAKE_H': |
---|
1219 | varvals = ['wakeh', 'wake_height', 0., 1000., 'height|of|the|wakes', 'm', \ |
---|
1220 | 'YlOrRd'] |
---|
1221 | elif varn == 'wakeomg' or varn == 'wake_omg' or varn == 'lwake_omg' or \ |
---|
1222 | varn == 'LWAKE_OMG': |
---|
1223 | varvals = ['wakeomg', 'wake_omega', 0., 3., 'wake|omega', \ |
---|
1224 | '-', 'BuGn'] |
---|
1225 | elif varn == 'wakes' or varn == 'wake_s' or varn == 'LWAKE_S': |
---|
1226 | varvals = ['wakes', 'wake_area_fraction', 0., 0.5, 'wake|spatial|fraction', \ |
---|
1227 | '1', 'BuGn'] |
---|
1228 | elif varn == 'wa' or varn == 'W' or varn == 'Vertical wind': |
---|
1229 | varvals = ['wa', 'upward_wind', -10., 10., 'upward|wind', 'ms-1', \ |
---|
1230 | 'seismic'] |
---|
1231 | elif varn == 'wap' or varn == 'vitw' or varn == 'LVITW': |
---|
1232 | varvals = ['wap', 'upward_wind', -3.e-10, 3.e-10, 'upward|wind', 'mPa-1', \ |
---|
1233 | 'seismic'] |
---|
1234 | elif varn == 'wss' or varn == 'SPDUV': |
---|
1235 | varvals = ['wss', 'air_velocity', 0., 30., 'surface|horizontal|wind|speed', \ |
---|
1236 | 'ms-1', 'Reds'] |
---|
1237 | # Water budget |
---|
1238 | # Water budget de-accumulated |
---|
1239 | elif varn == 'ccond' or varn == 'CCOND' or varn == 'ACCCONDde': |
---|
1240 | varvals = ['ccond', 'cw_cond', 0., 30., \ |
---|
1241 | 'cloud|water|condensation', 'mm', 'Reds'] |
---|
1242 | elif varn == 'wbr' or varn == 'ACQVAPORde': |
---|
1243 | varvals = ['wbr', 'wbr', 0., 30., 'Water|Budget|water|wapor', 'mm', 'Blues'] |
---|
1244 | elif varn == 'diabh' or varn == 'DIABH' or varn == 'ACDIABHde': |
---|
1245 | varvals = ['diabh', 'diabh', 0., 30., 'diabatic|heating', 'K', 'Reds'] |
---|
1246 | elif varn == 'wbpw' or varn == 'WBPW' or varn == 'WBACPWde': |
---|
1247 | varvals = ['wbpw', 'water_budget_pw', 0., 30., 'Water|Budget|water|content',\ |
---|
1248 | 'mms-1', 'Reds'] |
---|
1249 | elif varn == 'wbf' or varn == 'WBACF' or varn == 'WBACFde': |
---|
1250 | varvals = ['wbf', 'water_budget_hfcqv', 0., 30., \ |
---|
1251 | 'Water|Budget|horizontal|convergence|of|water|vapour|(+,|' + \ |
---|
1252 | 'conv.;|-,|div.)', 'mms-1', 'Reds'] |
---|
1253 | elif varn == 'wbfc' or varn == 'WBFC' or varn == 'WBACFCde': |
---|
1254 | varvals = ['wbfc', 'water_budget_fc', 0., 30., \ |
---|
1255 | 'Water|Budget|horizontal|convergence|of|cloud|(+,|conv.;|-,|' +\ |
---|
1256 | 'div.)', 'mms-1', 'Reds'] |
---|
1257 | elif varn == 'wbfp' or varn == 'WBFP' or varn == 'WBACFPde': |
---|
1258 | varvals = ['wbfp', 'water_budget_cfp', 0., 30., \ |
---|
1259 | 'Water|Budget|horizontal|convergence|of|precipitation|(+,|' + \ |
---|
1260 | 'conv.;|-,|div.)', 'mms-1', 'Reds'] |
---|
1261 | elif varn == 'wbz' or varn == 'WBZ' or varn == 'WBACZde': |
---|
1262 | varvals = ['wbz', 'water_budget_z', 0., 30., \ |
---|
1263 | 'Water|Budget|vertical|convergence|of|water|vapour|(+,|conv.' +\ |
---|
1264 | ';|-,|div.)', 'mms-1', 'Reds'] |
---|
1265 | elif varn == 'wbc' or varn == 'WBC' or varn == 'WBACCde': |
---|
1266 | varvals = ['wbc', 'water_budget_c', 0., 30., \ |
---|
1267 | 'Water|Budget|Cloud|water|species','mms-1', 'Reds'] |
---|
1268 | elif varn == 'wbqvd' or varn == 'WBQVD' or varn == 'WBACQVDde': |
---|
1269 | varvals = ['wbqvd', 'water_budget_qvd', 0., 30., \ |
---|
1270 | 'Water|Budget|water|vapour|divergence', 'mms-1', 'Reds'] |
---|
1271 | elif varn == 'wbqvblten' or varn == 'WBQVBLTEN' or varn == 'WBACQVBLTENde': |
---|
1272 | varvals = ['wbqvblten', 'water_budget_qv_blten', 0., 30., \ |
---|
1273 | 'Water|Budget|QV|tendency|due|to|pbl|parameterization', \ |
---|
1274 | 'kg kg-1 s-1', 'Reds'] |
---|
1275 | elif varn == 'wbqvcuten' or varn == 'WBQVCUTEN' or varn == 'WBACQVCUTENde': |
---|
1276 | varvals = ['wbqvcuten', 'water_budget_qv_cuten', 0., 30., \ |
---|
1277 | 'Water|Budget|QV|tendency|due|to|cu|parameterization', \ |
---|
1278 | 'kg kg-1 s-1', 'Reds'] |
---|
1279 | elif varn == 'wbqvshten' or varn == 'WBQVSHTEN' or varn == 'WBACQVSHTENde': |
---|
1280 | varvals = ['wbqvshten', 'water_budget_qv_shten', 0., 30., \ |
---|
1281 | 'Water|Budget|QV|tendency|due|to|shallow|cu|parameterization', \ |
---|
1282 | 'kg kg-1 s-1', 'Reds'] |
---|
1283 | elif varn == 'wbpr' or varn == 'WBP' or varn == 'WBACPde': |
---|
1284 | varvals = ['wbpr', 'water_budget_pr', 0., 30., \ |
---|
1285 | 'Water|Budget|recipitation', 'mms-1', 'Reds'] |
---|
1286 | elif varn == 'wbpw' or varn == 'WBPW' or varn == 'WBACPWde': |
---|
1287 | varvals = ['wbpw', 'water_budget_pw', 0., 30., \ |
---|
1288 | 'Water|Budget|water|content', 'mms-1', 'Reds'] |
---|
1289 | elif varn == 'wbcondt' or varn == 'WBCONDT' or varn == 'WBACCONDTde': |
---|
1290 | varvals = ['wbcondt', 'water_budget_condt', 0., 30., \ |
---|
1291 | 'Water|Budget|condensation|and|deposition', 'mms-1', 'Reds'] |
---|
1292 | elif varn == 'wbqcm' or varn == 'WBQCM' or varn == 'WBACQCMde': |
---|
1293 | varvals = ['wbqcm', 'water_budget_qcm', 0., 30., \ |
---|
1294 | 'Water|Budget|hydrometeor|change|and|convergence', 'mms-1', 'Reds'] |
---|
1295 | elif varn == 'wbsi' or varn == 'WBSI' or varn == 'WBACSIde': |
---|
1296 | varvals = ['wbsi', 'water_budget_si', 0., 30., \ |
---|
1297 | 'Water|Budget|hydrometeor|sink', 'mms-1', 'Reds'] |
---|
1298 | elif varn == 'wbso' or varn == 'WBSO' or varn == 'WBACSOde': |
---|
1299 | varvals = ['wbso', 'water_budget_so', 0., 30., \ |
---|
1300 | 'Water|Budget|hydrometeor|source', 'mms-1', 'Reds'] |
---|
1301 | # Water Budget accumulated |
---|
1302 | elif varn == 'ccondac' or varn == 'ACCCOND': |
---|
1303 | varvals = ['ccondac', 'cw_cond_ac', 0., 30., \ |
---|
1304 | 'accumulated|cloud|water|condensation', 'mm', 'Reds'] |
---|
1305 | elif varn == 'rac' or varn == 'ACQVAPOR': |
---|
1306 | varvals = ['rac', 'ac_r', 0., 30., 'accumualted|water|wapor', 'mm', 'Blues'] |
---|
1307 | elif varn == 'diabhac' or varn == 'ACDIABH': |
---|
1308 | varvals = ['diabhac', 'diabh_ac', 0., 30., 'accumualted|diabatic|heating', \ |
---|
1309 | 'K', 'Reds'] |
---|
1310 | elif varn == 'wbpwac' or varn == 'WBACPW': |
---|
1311 | varvals = ['wbpwac', 'water_budget_pw_ac', 0., 30., \ |
---|
1312 | 'Water|Budget|accumulated|water|content', 'mm', 'Reds'] |
---|
1313 | elif varn == 'wbfac' or varn == 'WBACF': |
---|
1314 | varvals = ['wbfac', 'water_budget_hfcqv_ac', 0., 30., \ |
---|
1315 | 'Water|Budget|accumulated|horizontal|convergence|of|water|vapour|(+,|' + \ |
---|
1316 | 'conv.;|-,|div.)', 'mm', 'Reds'] |
---|
1317 | elif varn == 'wbfcac' or varn == 'WBACFC': |
---|
1318 | varvals = ['wbfcac', 'water_budget_fc_ac', 0., 30., \ |
---|
1319 | 'Water|Budget|accumulated|horizontal|convergence|of|cloud|(+,|conv.;|-,|' +\ |
---|
1320 | 'div.)', 'mm', 'Reds'] |
---|
1321 | elif varn == 'wbfpac' or varn == 'WBACFP': |
---|
1322 | varvals = ['wbfpac', 'water_budget_cfp_ac', 0., 30., \ |
---|
1323 | 'Water|Budget|accumulated|horizontal|convergence|of|precipitation|(+,|' + \ |
---|
1324 | 'conv.;|-,|div.)', 'mm', 'Reds'] |
---|
1325 | elif varn == 'wbzac' or varn == 'WBACZ': |
---|
1326 | varvals = ['wbzac', 'water_budget_z_ac', 0., 30., \ |
---|
1327 | 'Water|Budget|accumulated|vertical|convergence|of|water|vapour|(+,|conv.' +\ |
---|
1328 | ';|-,|div.)', 'mm', 'Reds'] |
---|
1329 | elif varn == 'wbcac' or varn == 'WBACC': |
---|
1330 | varvals = ['wbcac', 'water_budget_c_ac', 0., 30., \ |
---|
1331 | 'Water|Budget|accumulated|Cloud|water|species','mm', 'Reds'] |
---|
1332 | elif varn == 'wbqvdac' or varn == 'WBACQVD': |
---|
1333 | varvals = ['wbqvdac', 'water_budget_qvd_ac', 0., 30., \ |
---|
1334 | 'Water|Budget|accumulated|water|vapour|divergence', 'mm', 'Reds'] |
---|
1335 | elif varn == 'wbqvbltenac' or varn == 'WBACQVBLTEN': |
---|
1336 | varvals = ['wbqvbltenac', 'water_budget_qv_blten_ac', 0., 30., \ |
---|
1337 | 'Water|Budget|accumulated|QV|tendency|due|to|pbl|parameterization', \ |
---|
1338 | 'kg kg-1 s-1', 'Reds'] |
---|
1339 | elif varn == 'wbqvcutenac' or varn == 'WBACQVCUTEN': |
---|
1340 | varvals = ['wbqvcutenac', 'water_budget_qv_cuten_ac', 0., 30., \ |
---|
1341 | 'Water|Budget|accumulated|QV|tendency|due|to|cu|parameterization', \ |
---|
1342 | 'kg kg-1 s-1', 'Reds'] |
---|
1343 | elif varn == 'wbqvshtenac' or varn == 'WBACQVSHTEN': |
---|
1344 | varvals = ['wbqvshtenac', 'water_budget_qv_shten_ac', 0., 30., \ |
---|
1345 | 'Water|Budget|accumulated|QV|tendency|due|to|shallow|cu|parameterization', \ |
---|
1346 | 'kg kg-1 s-1', 'Reds'] |
---|
1347 | elif varn == 'wbprac' or varn == 'WBACP': |
---|
1348 | varvals = ['wbprac', 'water_budget_pr_ac', 0., 30., \ |
---|
1349 | 'Water|Budget|accumulated|precipitation', 'mm', 'Reds'] |
---|
1350 | elif varn == 'wbpwac' or varn == 'WBACPW': |
---|
1351 | varvals = ['wbpwac', 'water_budget_pw_ac', 0., 30., \ |
---|
1352 | 'Water|Budget|accumulated|water|content', 'mm', 'Reds'] |
---|
1353 | elif varn == 'wbcondtac' or varn == 'WBACCONDT': |
---|
1354 | varvals = ['wbcondtac', 'water_budget_condt_ac', 0., 30., \ |
---|
1355 | 'Water|Budget|accumulated|condensation|and|deposition', 'mm', 'Reds'] |
---|
1356 | elif varn == 'wbqcmac' or varn == 'WBACQCM': |
---|
1357 | varvals = ['wbqcmac', 'water_budget_qcm_ac', 0., 30., \ |
---|
1358 | 'Water|Budget|accumulated|hydrometeor|change|and|convergence', 'mm', 'Reds'] |
---|
1359 | elif varn == 'wbsiac' or varn == 'WBACSI': |
---|
1360 | varvals = ['wbsiac', 'water_budget_si_ac', 0., 30., \ |
---|
1361 | 'Water|Budget|accumulated|hydrometeor|sink', 'mm', 'Reds'] |
---|
1362 | elif varn == 'wbsoac' or varn == 'WBACSO': |
---|
1363 | varvals = ['wbsoac', 'water_budget_so_ac', 0., 30., \ |
---|
1364 | 'Water|Budget|accumulated|hydrometeor|source', 'mm', 'Reds'] |
---|
1365 | |
---|
1366 | elif varn == 'xtime' or varn == 'XTIME': |
---|
1367 | varvals = ['xtime', 'time', 0., 1.e5, 'time', \ |
---|
1368 | 'minutes|since|simulation|start', 'Reds'] |
---|
1369 | elif varn == 'x' or varn == 'X': |
---|
1370 | varvals = ['x', 'x', 0., 100., 'x', '-', 'Reds'] |
---|
1371 | elif varn == 'y' or varn == 'Y': |
---|
1372 | varvals = ['y', 'y', 0., 100., 'y', '-', 'Blues'] |
---|
1373 | elif varn == 'z' or varn == 'Z': |
---|
1374 | varvals = ['z', 'z', 0., 100., 'z', '-', 'Greens'] |
---|
1375 | elif varn == 'zg' or varn == 'WRFght' or varn == 'Geopotential height' or \ |
---|
1376 | varn == 'geop' or varn == 'LGEOP': |
---|
1377 | varvals = ['zg', 'geopotential_height', 0., 80000., 'geopotential|height', \ |
---|
1378 | 'm2s-2', 'rainbow'] |
---|
1379 | elif varn == 'zmaxth' or varn == 'zmax_th' or varn == 'LZMAX_TH': |
---|
1380 | varvals = ['zmaxth', 'thermal_plume_height', 0., 4000., \ |
---|
1381 | 'maximum|thermals|plume|height', 'm', 'YlOrRd'] |
---|
1382 | elif varn == 'zmla' or varn == 's_pblh' or varn == 'LS_PBLH': |
---|
1383 | varvals = ['zmla', 'atmosphere_boundary_layer_thickness', 0., 2500., \ |
---|
1384 | 'atmosphere|boundary|layer|thickness', 'm', 'Blues'] |
---|
1385 | else: |
---|
1386 | print errormsg |
---|
1387 | print ' ' + fname + ": variable '" + varn + "' not defined !!!" |
---|
1388 | quit(-1) |
---|
1389 | |
---|
1390 | return varvals |
---|
1391 | |
---|
1392 | def lonlat2D(lon,lat): |
---|
1393 | """ Function to return lon, lat 2D matrices from any lon,lat matrix |
---|
1394 | lon= matrix with longitude values |
---|
1395 | lat= matrix with latitude values |
---|
1396 | """ |
---|
1397 | fname = 'lonlat2D' |
---|
1398 | |
---|
1399 | if len(lon.shape) != len(lat.shape): |
---|
1400 | print errormsg |
---|
1401 | print ' ' + fname + ': longitude values with shape:', lon.shape, \ |
---|
1402 | 'is different that latitude values with shape:', lat.shape, '(dif. size) !!' |
---|
1403 | quit(-1) |
---|
1404 | |
---|
1405 | if len(lon.shape) == 3: |
---|
1406 | lonvv = lon[0,:,:] |
---|
1407 | latvv = lat[0,:,:] |
---|
1408 | elif len(lon.shape) == 2: |
---|
1409 | lonvv = lon[:] |
---|
1410 | latvv = lat[:] |
---|
1411 | elif len(lon.shape) == 1: |
---|
1412 | lonlatv = np.meshgrid(lon[:],lat[:]) |
---|
1413 | lonvv = lonlatv[0] |
---|
1414 | latvv = lonlatv[1] |
---|
1415 | |
---|
1416 | return lonvv, latvv |
---|
1417 | |
---|
1418 | ####### ####### ####### ####### ####### ####### ####### ####### ####### ####### |
---|
1419 | |
---|
1420 | def check_colorBar(cbarn): |
---|
1421 | """ Check if the given colorbar exists in matplotlib |
---|
1422 | """ |
---|
1423 | fname = 'check_colorBar' |
---|
1424 | |
---|
1425 | # Possible color bars |
---|
1426 | colorbars = ['binary', 'Blues', 'BuGn', 'BuPu', 'gist_yarg', 'GnBu', 'Greens', \ |
---|
1427 | 'Greys', 'Oranges', 'OrRd', 'PuBu', 'PuBuGn', 'PuRd', 'Purples', 'RdPu', \ |
---|
1428 | 'Reds', 'YlGn', 'YlGnBu', 'YlOrBr', 'YlOrRd', 'afmhot', 'autumn', 'bone', \ |
---|
1429 | 'cool', 'copper', 'gist_gray', 'gist_heat', 'gray', 'hot', 'pink', 'spring', \ |
---|
1430 | 'summer', 'winter', 'BrBG', 'bwr', 'coolwarm', 'PiYG', 'PRGn', 'PuOr', 'RdBu', \ |
---|
1431 | 'RdGy', 'RdYlBu', 'RdYlGn', 'seismic', 'Accent', 'Dark2', 'hsv', 'Paired', \ |
---|
1432 | 'Pastel1', 'Pastel2', 'Set1', 'Set2', 'Set3', 'spectral', 'gist_earth', \ |
---|
1433 | 'gist_ncar', 'gist_rainbow', 'gist_stern', 'jet', 'brg', 'CMRmap', 'cubehelix',\ |
---|
1434 | 'gnuplot', 'gnuplot2', 'ocean', 'rainbow', 'terrain', 'flag', 'prism'] |
---|
1435 | |
---|
1436 | if not searchInlist(colorbars,cbarn): |
---|
1437 | print warnmsg |
---|
1438 | print ' ' + fname + ' color bar: "' + cbarn + '" does not exist !!' |
---|
1439 | print ' a standard one will be use instead !!' |
---|
1440 | |
---|
1441 | return |
---|
1442 | |
---|
1443 | def units_lunits(u): |
---|
1444 | """ Fucntion to provide LaTeX equivalences from a given units |
---|
1445 | u= units to transform |
---|
1446 | >>> units_lunits('kgkg-1') |
---|
1447 | '$kgkg^{-1}$' |
---|
1448 | """ |
---|
1449 | fname = 'units_lunits' |
---|
1450 | |
---|
1451 | if u == 'h': |
---|
1452 | print fname + '_____________________________________________________________' |
---|
1453 | print units_lunits.__doc__ |
---|
1454 | quit() |
---|
1455 | |
---|
1456 | # Units which does not change |
---|
1457 | same = ['1', 'category', 'day', 'deg', 'degree', 'degrees', 'degrees East', \ |
---|
1458 | 'degrees Nord', 'degrees North', 'g', 'gpm', 'hour', 'hPa', 'K', 'Km', 'kg', \ |
---|
1459 | 'km', 'm', 'minute', 'mm', 'month', 'Pa', 's', 'second', 'um', 'year', '-'] |
---|
1460 | |
---|
1461 | if searchInlist(same,u): |
---|
1462 | lu = '$' + u + '$' |
---|
1463 | elif len(u.split(' ')) > 1 and u.split(' ')[1] == 'since': |
---|
1464 | uparts = u.split(' ') |
---|
1465 | ip=0 |
---|
1466 | for up in uparts: |
---|
1467 | if ip == 0: |
---|
1468 | lu = '$' + up |
---|
1469 | else: |
---|
1470 | lu = lu + '\ ' + up |
---|
1471 | ip=ip+1 |
---|
1472 | lu = lu + '$' |
---|
1473 | else: |
---|
1474 | if u == '': lu='-' |
---|
1475 | elif u == 'C': lu='$^{\circ}C$' |
---|
1476 | elif u == 'days': lu='$day$' |
---|
1477 | elif u == 'degrees_east': lu='$degrees\ East$' |
---|
1478 | elif u == 'degree_east': lu='$degrees\ East$' |
---|
1479 | elif u == 'degrees longitude': lu='$degrees\ East$' |
---|
1480 | elif u == 'degrees latitude': lu='$degrees\ North$' |
---|
1481 | elif u == 'degrees_north': lu='$degrees\ North$' |
---|
1482 | elif u == 'degree_north': lu='$degrees\ North$' |
---|
1483 | elif u == 'deg C': lu='$^{\circ}C$' |
---|
1484 | elif u == 'degC': lu='$^{\circ}C$' |
---|
1485 | elif u == 'deg K': lu='$K$' |
---|
1486 | elif u == 'degK': lu='$K$' |
---|
1487 | elif u == 'hours': lu='$hour$' |
---|
1488 | elif u == 'J/kg': lu='$Jkg^{-1}$' |
---|
1489 | elif u == 'Jkg-1': lu='$Jkg^{-1}$' |
---|
1490 | elif u == 'K/m': lu='$Km^{-1}$' |
---|
1491 | elif u == 'Km-1': lu='$Km^{-1}$' |
---|
1492 | elif u == 'K/s': lu='$Ks^{-1}$' |
---|
1493 | elif u == 'Ks-1': lu='$Ks^{-1}$' |
---|
1494 | elif u == 'K s-1': lu='$Ks^{-1}$' |
---|
1495 | elif u == 'kg/kg': lu='$kgkg^{-1}$' |
---|
1496 | elif u == 'kgkg-1': lu='$kgkg^{-1}$' |
---|
1497 | elif u == 'kg kg-1': lu='$kgkg^{-1}$' |
---|
1498 | elif u == '(kg/kg)/s': lu='$kgkg^{-1}s^{-1}$' |
---|
1499 | elif u == 'kgkg-1s-1': lu='$kgkg^{-1}s^{-1}$' |
---|
1500 | elif u == 'kg kg-1 s-1': lu='$kgkg^{-1}s^{-1}$' |
---|
1501 | elif u == 'kg/m2': lu='$kgm^{-2}$' |
---|
1502 | elif u == 'kgm-2': lu='$kgm^{-2}$' |
---|
1503 | elif u == 'kg m-2': lu='$kgm^{-2}$' |
---|
1504 | elif u == 'Kg m-2': lu='$kgm^{-2}$' |
---|
1505 | elif u == 'kg/m2/s': lu='$kgm^{-2}s^{-1}$' |
---|
1506 | elif u == 'kg/(m2*s)': lu='$kgm^{-2}s^{-1}$' |
---|
1507 | elif u == 'kg/(s*m2)': lu='$kgm^{-2}s^{-1}$' |
---|
1508 | elif u == 'kgm-2s-1': lu='$kgm^{-2}s^{-1}$' |
---|
1509 | elif u == 'kg m-2 s-1': lu='$kgm^{-2}s^{-1}$' |
---|
1510 | elif u == '1/m': lu='$m^{-1}$' |
---|
1511 | elif u == 'm-1': lu='$m^{-1}$' |
---|
1512 | elif u == 'm2/s': lu='$m2s^{-1}$' |
---|
1513 | elif u == 'm2s-1': lu='$m2s^{-1}$' |
---|
1514 | elif u == 'm2/s2': lu='$m2s^{-2}$' |
---|
1515 | elif u == 'm/s': lu='$ms^{-1}$' |
---|
1516 | elif u == 'mmh-3': lu='$mmh^{-3}$' |
---|
1517 | elif u == 'ms-1': lu='$ms^{-1}$' |
---|
1518 | elif u == 'm s-1': lu='$ms^{-1}$' |
---|
1519 | elif u == 'm/s2': lu='$ms^{-2}$' |
---|
1520 | elif u == 'ms-2': lu='$ms^{-2}$' |
---|
1521 | elif u == 'minutes': lu='$minute$' |
---|
1522 | elif u == 'Pa/s': lu='$Pas^{-1}$' |
---|
1523 | elif u == 'Pas-1': lu='$Pas^{-1}$' |
---|
1524 | elif u == 'W m-2': lu='$Wm^{-2}$' |
---|
1525 | elif u == 'Wm-2': lu='$Wm^{-2}$' |
---|
1526 | elif u == 'W/m2': lu='$Wm^{-2}$' |
---|
1527 | elif u == '1/s': lu='$s^{-1}$' |
---|
1528 | elif u == 's-1': lu='$s^{-1}$' |
---|
1529 | elif u == 'seconds': lu='$second$' |
---|
1530 | elif u == '%': lu='\%' |
---|
1531 | else: |
---|
1532 | print errormsg |
---|
1533 | print ' ' + fname + ': units "' + u + '" not ready!!!!' |
---|
1534 | quit(-1) |
---|
1535 | |
---|
1536 | return lu |
---|
1537 | |
---|
1538 | def ASCII_LaTeX(ln): |
---|
1539 | """ Function to transform from an ASCII line to LaTeX codification |
---|
1540 | >>> ASCII_LaTeX('Laboratoire de Météorologie Dynamique però Hovmöller') |
---|
1541 | Laboratoire de M\'et\'eorologie Dynamique per\`o Hovm\"oller |
---|
1542 | """ |
---|
1543 | fname='ASCII_LaTeX' |
---|
1544 | |
---|
1545 | if ln == 'h': |
---|
1546 | print fname + '_____________________________________________________________' |
---|
1547 | print ASCII_LaTeX.__doc__ |
---|
1548 | quit() |
---|
1549 | |
---|
1550 | newln = ln.replace('\\', '\\textbackslash') |
---|
1551 | |
---|
1552 | newln = newln.replace('á', "\\'a") |
---|
1553 | newln = newln.replace('é', "\\'e") |
---|
1554 | newln = newln.replace('Ã', "\\'i") |
---|
1555 | newln = newln.replace('ó', "\\'o") |
---|
1556 | newln = newln.replace('ú', "\\'u") |
---|
1557 | |
---|
1558 | newln = newln.replace('Ã ', "\\`a") |
---|
1559 | newln = newln.replace('Ú', "\\`e") |
---|
1560 | newln = newln.replace('ì', "\\`i") |
---|
1561 | newln = newln.replace('ò', "\\`o") |
---|
1562 | newln = newln.replace('ù', "\\`u") |
---|
1563 | |
---|
1564 | newln = newln.replace('â', "\\^a") |
---|
1565 | newln = newln.replace('ê', "\\^e") |
---|
1566 | newln = newln.replace('î', "\\^i") |
---|
1567 | newln = newln.replace('ÃŽ', "\\^o") |
---|
1568 | newln = newln.replace('û', "\\^u") |
---|
1569 | |
---|
1570 | newln = newln.replace('À', '\\"a') |
---|
1571 | newln = newln.replace('ë', '\\"e') |
---|
1572 | newln = newln.replace('ï', '\\"i') |
---|
1573 | newln = newln.replace('ö', '\\"o') |
---|
1574 | newln = newln.replace('Ì', '\\"u') |
---|
1575 | |
---|
1576 | newln = newln.replace('ç', '\c{c}') |
---|
1577 | newln = newln.replace('ñ', '\~{n}') |
---|
1578 | |
---|
1579 | newln = newln.replace('Ã', "\\'A") |
---|
1580 | newln = newln.replace('Ã', "\\'E") |
---|
1581 | newln = newln.replace('Ã', "\\'I") |
---|
1582 | newln = newln.replace('Ã', "\\'O") |
---|
1583 | newln = newln.replace('Ã', "\\'U") |
---|
1584 | |
---|
1585 | newln = newln.replace('Ã', "\\`A") |
---|
1586 | newln = newln.replace('Ã', "\\`E") |
---|
1587 | newln = newln.replace('Ã', "\\`I") |
---|
1588 | newln = newln.replace('Ã', "\\`O") |
---|
1589 | newln = newln.replace('Ã', "\\`U") |
---|
1590 | |
---|
1591 | newln = newln.replace('Ã', "\\^A") |
---|
1592 | newln = newln.replace('Ã', "\\^E") |
---|
1593 | newln = newln.replace('Ã', "\\^I") |
---|
1594 | newln = newln.replace('Ã', "\\^O") |
---|
1595 | newln = newln.replace('Ã', "\\^U") |
---|
1596 | |
---|
1597 | newln = newln.replace('Ã', '\\"A') |
---|
1598 | newln = newln.replace('Ã', '\\"E') |
---|
1599 | newln = newln.replace('Ã', '\\"I') |
---|
1600 | newln = newln.replace('Ã', '\\"O') |
---|
1601 | newln = newln.replace('Ã', '\\"U') |
---|
1602 | |
---|
1603 | newln = newln.replace('Ã', '\\c{C}') |
---|
1604 | newln = newln.replace('Ã', '\\~{N}') |
---|
1605 | |
---|
1606 | newln = newln.replace('¡', '!`') |
---|
1607 | newln = newln.replace('¿', '¿`') |
---|
1608 | newln = newln.replace('%', '\\%') |
---|
1609 | newln = newln.replace('#', '\\#') |
---|
1610 | newln = newln.replace('&', '\\&') |
---|
1611 | newln = newln.replace('$', '\\$') |
---|
1612 | newln = newln.replace('_', '\\_') |
---|
1613 | newln = newln.replace('·', '\\textperiodcentered') |
---|
1614 | newln = newln.replace('<', '$<$') |
---|
1615 | newln = newln.replace('>', '$>$') |
---|
1616 | newln = newln.replace('ï', '*') |
---|
1617 | # newln = newln.replace('º', '$^{\\circ}$') |
---|
1618 | newln = newln.replace('ª', '$^{a}$') |
---|
1619 | newln = newln.replace('º', '$^{o}$') |
---|
1620 | newln = newln.replace('°', '$^{\\circ}$') |
---|
1621 | newln = newln.replace('\n', '\\\\\n') |
---|
1622 | newln = newln.replace('\t', '\\medskip') |
---|
1623 | |
---|
1624 | return newln |
---|
1625 | |
---|
1626 | def pretty_int(minv,maxv,Nint): |
---|
1627 | """ Function to plot nice intervals |
---|
1628 | minv= minimum value |
---|
1629 | maxv= maximum value |
---|
1630 | Nint= number of intervals |
---|
1631 | >>> pretty_int(23.50,67.21,5) |
---|
1632 | [ 25. 30. 35. 40. 45. 50. 55. 60. 65.] |
---|
1633 | >>> pretty_int(-23.50,67.21,15) |
---|
1634 | [ 0. 20. 40. 60.] |
---|
1635 | pretty_int(14.75,25.25,5) |
---|
1636 | [ 16. 18. 20. 22. 24.] |
---|
1637 | """ |
---|
1638 | fname = 'pretty_int' |
---|
1639 | nice_int = [1,2,5] |
---|
1640 | |
---|
1641 | # print 'minv: ',minv,'maxv:',maxv,'Nint:',Nint |
---|
1642 | |
---|
1643 | interval = np.abs(maxv - minv) |
---|
1644 | |
---|
1645 | potinterval = np.log10(interval) |
---|
1646 | Ipotint = int(potinterval) |
---|
1647 | intvalue = np.float(interval / np.float(Nint)) |
---|
1648 | |
---|
1649 | # new |
---|
1650 | potinterval = np.log10(intvalue) |
---|
1651 | Ipotint = int(potinterval) |
---|
1652 | |
---|
1653 | # print 'interval:', interval, 'intavlue:', intvalue, 'potinterval:', potinterval, \ |
---|
1654 | # 'Ipotint:', Ipotint, 'intvalue:', intvalue |
---|
1655 | |
---|
1656 | mindist = 10.e15 |
---|
1657 | for inice in nice_int: |
---|
1658 | # print inice,':',inice*10.**Ipotint,np.abs(inice*10.**Ipotint - intvalue),mindist |
---|
1659 | if np.abs(inice*10.**Ipotint - intvalue) < mindist: |
---|
1660 | mindist = np.abs(inice*10.**Ipotint - intvalue) |
---|
1661 | closestint = inice |
---|
1662 | |
---|
1663 | Ibeg = int(minv / (closestint*10.**Ipotint)) |
---|
1664 | |
---|
1665 | values = [] |
---|
1666 | val = closestint*(Ibeg)*10.**(Ipotint) |
---|
1667 | |
---|
1668 | # print 'closestint:',closestint,'Ibeg:',Ibeg,'val:',val |
---|
1669 | |
---|
1670 | while val < maxv: |
---|
1671 | values.append(val) |
---|
1672 | val = val + closestint*10.**Ipotint |
---|
1673 | |
---|
1674 | return np.array(values, dtype=np.float) |
---|
1675 | |
---|
1676 | def DegGradSec_deg(grad,deg,sec): |
---|
1677 | """ Function to transform from a coordinate in grad deg sec to degrees (decimal) |
---|
1678 | >>> DegGradSec_deg(39.,49.,26.) |
---|
1679 | 39.8238888889 |
---|
1680 | """ |
---|
1681 | fname = 'DegGradSec_deg' |
---|
1682 | |
---|
1683 | if grad == 'h': |
---|
1684 | print fname + '_____________________________________________________________' |
---|
1685 | print DegGradSec_deg.__doc__ |
---|
1686 | quit() |
---|
1687 | |
---|
1688 | deg = grad + deg/60. + sec/3600. |
---|
1689 | |
---|
1690 | return deg |
---|
1691 | |
---|
1692 | def intT2dt(intT,tu): |
---|
1693 | """ Function to provide an 'timedelta' object from a given interval value |
---|
1694 | intT= interval value |
---|
1695 | tu= interval units, [tu]= 'd': day, 'w': week, 'h': hour, 'i': minute, 's': second, |
---|
1696 | 'l': milisecond |
---|
1697 | |
---|
1698 | >>> intT2dt(3.5,'s') |
---|
1699 | 0:00:03.500000 |
---|
1700 | |
---|
1701 | >>> intT2dt(3.5,'w') |
---|
1702 | 24 days, 12:00:00 |
---|
1703 | """ |
---|
1704 | import datetime as dt |
---|
1705 | |
---|
1706 | fname = 'intT2dt' |
---|
1707 | |
---|
1708 | if tu == 'w': |
---|
1709 | dtv = dt.timedelta(weeks=np.float(intT)) |
---|
1710 | elif tu == 'd': |
---|
1711 | dtv = dt.timedelta(days=np.float(intT)) |
---|
1712 | elif tu == 'h': |
---|
1713 | dtv = dt.timedelta(hours=np.float(intT)) |
---|
1714 | elif tu == 'i': |
---|
1715 | dtv = dt.timedelta(minutes=np.float(intT)) |
---|
1716 | elif tu == 's': |
---|
1717 | dtv = dt.timedelta(seconds=np.float(intT)) |
---|
1718 | elif tu == 'l': |
---|
1719 | dtv = dt.timedelta(milliseconds=np.float(intT)) |
---|
1720 | else: |
---|
1721 | print errormsg |
---|
1722 | print ' ' + fname + ': time units "' + tu + '" not ready!!!!' |
---|
1723 | quit(-1) |
---|
1724 | |
---|
1725 | return dtv |
---|
1726 | |
---|
1727 | def lonlat_values(mapfile,lonvn,latvn): |
---|
1728 | """ Function to obtain the lon/lat matrices from a given netCDF file |
---|
1729 | lonlat_values(mapfile,lonvn,latvn) |
---|
1730 | [mapfile]= netCDF file name |
---|
1731 | [lonvn]= variable name with the longitudes |
---|
1732 | [latvn]= variable name with the latitudes |
---|
1733 | """ |
---|
1734 | |
---|
1735 | fname = 'lonlat_values' |
---|
1736 | |
---|
1737 | if mapfile == 'h': |
---|
1738 | print fname + '_____________________________________________________________' |
---|
1739 | print lonlat_values.__doc__ |
---|
1740 | quit() |
---|
1741 | |
---|
1742 | if not os.path.isfile(mapfile): |
---|
1743 | print errormsg |
---|
1744 | print ' ' + fname + ": map file '" + mapfile + "' does not exist !!" |
---|
1745 | quit(-1) |
---|
1746 | |
---|
1747 | ncobj = NetCDFFile(mapfile, 'r') |
---|
1748 | lonobj = ncobj.variables[lonvn] |
---|
1749 | latobj = ncobj.variables[latvn] |
---|
1750 | |
---|
1751 | if len(lonobj.shape) == 3: |
---|
1752 | lonv = lonobj[0,:,:] |
---|
1753 | latv = latobj[0,:,:] |
---|
1754 | elif len(lonobj.shape) == 2: |
---|
1755 | lonv = lonobj[:,:] |
---|
1756 | latv = latobj[:,:] |
---|
1757 | elif len(lonobj.shape) == 1: |
---|
1758 | lon0 = lonobj[:] |
---|
1759 | lat0 = latobj[:] |
---|
1760 | lonv = np.zeros( (len(lat0),len(lon0)), dtype=np.float ) |
---|
1761 | latv = np.zeros( (len(lat0),len(lon0)), dtype=np.float ) |
---|
1762 | for iy in range(len(lat0)): |
---|
1763 | lonv[iy,:] = lon0 |
---|
1764 | for ix in range(len(lon0)): |
---|
1765 | latv[:,ix] = lat0 |
---|
1766 | else: |
---|
1767 | print errormsg |
---|
1768 | print ' ' + fname + ': lon/lat variables shape:',lonobj.shape,'not ready!!' |
---|
1769 | quit(-1) |
---|
1770 | |
---|
1771 | return lonv, latv |
---|
1772 | |
---|
1773 | def date_CFtime(ind,refd,tunits): |
---|
1774 | """ Function to transform from a given date object a CF-convention time |
---|
1775 | ind= date object to transform |
---|
1776 | refd= reference date |
---|
1777 | tunits= units for time |
---|
1778 | >>> date_CFtime(dt.datetime(1976,02,17,08,30,00), dt.datetime(1949,12,01,00,00,00), 'seconds') |
---|
1779 | 827224200.0 |
---|
1780 | """ |
---|
1781 | import datetime as dt |
---|
1782 | |
---|
1783 | fname = 'date_CFtime' |
---|
1784 | |
---|
1785 | dt = ind - refd |
---|
1786 | |
---|
1787 | if tunits == 'weeks': |
---|
1788 | value = dt.days/7. + dt.seconds/(3600.*24.*7.) |
---|
1789 | elif tunits == 'days': |
---|
1790 | value = dt.days + dt.seconds/(3600.*24.) |
---|
1791 | elif tunits == 'hours': |
---|
1792 | value = dt.days*24. + dt.seconds/(3600.) |
---|
1793 | elif tunits == 'minutes': |
---|
1794 | value = dt.days*24.*60. + dt.seconds/(60.) |
---|
1795 | elif tunits == 'seconds': |
---|
1796 | value = dt.days*24.*3600. + dt.seconds |
---|
1797 | elif tunits == 'milliseconds': |
---|
1798 | value = dt.days*24.*3600.*1000. + dt.seconds*1000. |
---|
1799 | else: |
---|
1800 | print errormsg |
---|
1801 | print ' ' + fname + ': reference time units "' + trefu + '" not ready!!!!' |
---|
1802 | quit(-1) |
---|
1803 | |
---|
1804 | return value |
---|
1805 | |
---|
1806 | def pot_values(values, uvals): |
---|
1807 | """ Function to modify a seies of values by their potency of 10 |
---|
1808 | pot_values(values, uvals) |
---|
1809 | values= values to modify |
---|
1810 | uvals= units of the values |
---|
1811 | >>> vals = np.sin(np.arange(20)*np.pi/5.+0.01)*10.e-5 |
---|
1812 | >>> pot_values(vals,'ms-1') |
---|
1813 | (array([ 0.00000000e+00, 5.87785252e-01, 9.51056516e-01, |
---|
1814 | 9.51056516e-01, 5.87785252e-01, 1.22464680e-16, |
---|
1815 | -5.87785252e-01, -9.51056516e-01, -9.51056516e-01, |
---|
1816 | -5.87785252e-01, -2.44929360e-16, 5.87785252e-01, |
---|
1817 | 9.51056516e-01, 9.51056516e-01, 5.87785252e-01, |
---|
1818 | 3.67394040e-16, -5.87785252e-01, -9.51056516e-01, |
---|
1819 | -9.51056516e-01, -5.87785252e-01]), -4, 'x10e-4 ms-1', 'x10e-4') |
---|
1820 | """ |
---|
1821 | |
---|
1822 | fname = 'pot_values' |
---|
1823 | |
---|
1824 | if np.min(values) != 0.: |
---|
1825 | potmin = int( np.log10( np.abs(np.min(values)) ) ) |
---|
1826 | else: |
---|
1827 | potmin = 0 |
---|
1828 | |
---|
1829 | if np.max(values) != 0.: |
---|
1830 | potmax = int( np.log10( np.abs(np.max(values)) ) ) |
---|
1831 | else: |
---|
1832 | potmax = 0 |
---|
1833 | |
---|
1834 | if potmin * potmax > 9: |
---|
1835 | potval = -np.min([np.abs(potmin), np.abs(potmax)]) * np.abs(potmin) / potmin |
---|
1836 | |
---|
1837 | newvalues = values*10.**potval |
---|
1838 | potvalue = - potval |
---|
1839 | potS = 'x10e' + str(potvalue) |
---|
1840 | newunits = potS + ' ' + uvals |
---|
1841 | else: |
---|
1842 | newvalues = values |
---|
1843 | potvalue = None |
---|
1844 | potS = '' |
---|
1845 | newunits = uvals |
---|
1846 | |
---|
1847 | return newvalues, potvalue, newunits, potS |
---|
1848 | |
---|
1849 | def CFtimes_plot(timev,units,kind,tfmt): |
---|
1850 | """ Function to provide a list of string values from a CF time values in order |
---|
1851 | to use them in a plot, according to the series of characteristics. |
---|
1852 | String outputs will be suited to the 'human-like' output |
---|
1853 | timev= time values (real values) |
---|
1854 | units= units string according to CF conventions ([tunits] since |
---|
1855 | [YYYY]-[MM]-[DD] [[HH]:[MI]:[SS]]) |
---|
1856 | kind= kind of output |
---|
1857 | 'Nval': according to a given number of values as 'Nval',[Nval] |
---|
1858 | 'exct': according to an exact time unit as 'exct',[tunit]; |
---|
1859 | tunit= [Nunits],[tu]; [tu]= 'c': centuries, 'y': year, 'm': month, |
---|
1860 | 'w': week, 'd': day, 'h': hour, 'i': minute, 's': second, |
---|
1861 | 'l': milisecond |
---|
1862 | tfmt= desired format |
---|
1863 | >>> CFtimes_plot(np.arange(100)*1.,'hours since 1979-12-01 00:00:00', 'Nval,5',"%Y/%m/%d %H:%M:%S") |
---|
1864 | 0.0 1979/12/01 00:00:00 |
---|
1865 | 24.75 1979/12/02 00:45:00 |
---|
1866 | 49.5 1979/12/03 01:30:00 |
---|
1867 | 74.25 1979/12/04 02:15:00 |
---|
1868 | 99.0 1979/12/05 03:00:00 |
---|
1869 | >>> CFtimes_plot(np.arange(100)*1.,'hours since 1979-12-01 00:00:00', 'exct,2,d',"%Y/%m/%d %H:%M:%S") |
---|
1870 | 0.0 1979/12/01 00:00:00 |
---|
1871 | 48.0 1979/12/03 00:00:00 |
---|
1872 | 96.0 1979/12/05 00:00:00 |
---|
1873 | 144.0 1979/12/07 00:00:00 |
---|
1874 | """ |
---|
1875 | import datetime as dt |
---|
1876 | |
---|
1877 | # Seconds between 0001 and 1901 Jan - 01 |
---|
1878 | secs0001_1901=59958144000. |
---|
1879 | |
---|
1880 | fname = 'CFtimes_plot' |
---|
1881 | |
---|
1882 | if timev == 'h': |
---|
1883 | print fname + '_____________________________________________________________' |
---|
1884 | print CFtimes_plot.__doc__ |
---|
1885 | quit() |
---|
1886 | |
---|
1887 | secsYear = 365.*24.*3600. |
---|
1888 | secsWeek = 7.*24.*3600. |
---|
1889 | secsDay = 24.*3600. |
---|
1890 | secsHour = 3600. |
---|
1891 | secsMinute = 60. |
---|
1892 | secsMilisecond = 1./1000. |
---|
1893 | secsMicrosecond = 1./1000000. |
---|
1894 | |
---|
1895 | # Does reference date contain a time value [YYYY]-[MM]-[DD] [HH]:[MI]:[SS] |
---|
1896 | ## |
---|
1897 | trefT = units.find(':') |
---|
1898 | txtunits = units.split(' ') |
---|
1899 | Ntxtunits = len(txtunits) |
---|
1900 | |
---|
1901 | if Ntxtunits == 3: |
---|
1902 | Srefdate = txtunits[Ntxtunits - 1] |
---|
1903 | else: |
---|
1904 | Srefdate = txtunits[Ntxtunits - 2] |
---|
1905 | |
---|
1906 | print 'Lluis Srefdate:',Srefdate, 'txtunits:',txtunits,'units:',units |
---|
1907 | if not trefT == -1: |
---|
1908 | # print ' ' + fname + ': refdate with time!' |
---|
1909 | if Ntxtunits == 3: |
---|
1910 | refdate = datetimeStr_datetime(Srefdate) |
---|
1911 | else: |
---|
1912 | refdate = datetimeStr_datetime(Srefdate + '_' + txtunits[Ntxtunits - 1]) |
---|
1913 | else: |
---|
1914 | refdate = datetimeStr_datetime(Srefdate + '_00:00:00') |
---|
1915 | |
---|
1916 | trefunits=units.split(' ')[0] |
---|
1917 | if trefunits == 'weeks': |
---|
1918 | trefu = 'w' |
---|
1919 | elif trefunits == 'days': |
---|
1920 | trefu = 'd' |
---|
1921 | elif trefunits == 'hours': |
---|
1922 | trefu = 'h' |
---|
1923 | elif trefunits == 'minutes': |
---|
1924 | trefu = 'm' |
---|
1925 | elif trefunits == 'seconds': |
---|
1926 | trefu = 's' |
---|
1927 | elif trefunits == 'milliseconds': |
---|
1928 | trefu = 'l' |
---|
1929 | else: |
---|
1930 | print errormsg |
---|
1931 | print ' ' + fname + ': reference time units "' + trefu + '" not ready!!!!' |
---|
1932 | quit(-1) |
---|
1933 | |
---|
1934 | okind=kind.split(',')[0] |
---|
1935 | dtv = len(timev) |
---|
1936 | |
---|
1937 | if refdate.year == 1: |
---|
1938 | print warnmsg |
---|
1939 | print ' ' + fname + ': changing reference date: ',refdate, \ |
---|
1940 | 'to 1901-01-01_00:00:00 !!!' |
---|
1941 | refdate = datetimeStr_datetime('1901-01-01_00:00:00') |
---|
1942 | if trefu == 'w': timev = timev - secs0001_1901/(7.*24.*3600.) |
---|
1943 | if trefu == 'd': timev = timev - secs0001_1901/(24.*3600.) |
---|
1944 | if trefu == 'h': timev = timev - secs0001_1901/(3600.) |
---|
1945 | if trefu == 'm': timev = timev - secs0001_1901/(60.) |
---|
1946 | if trefu == 's': timev = timev - secs0001_1901 |
---|
1947 | if trefu == 'l': timev = timev - secs0001_1901*1000. |
---|
1948 | |
---|
1949 | firstT = timev[0] |
---|
1950 | lastT = timev[dtv-1] |
---|
1951 | |
---|
1952 | # First and last times as datetime objects |
---|
1953 | firstTdt = timeref_datetime(refdate, firstT, trefunits) |
---|
1954 | lastTdt = timeref_datetime(refdate, lastT, trefunits) |
---|
1955 | |
---|
1956 | # First and last times as [year, mon, day, hour, minut, second] vectors |
---|
1957 | firstTvec = np.zeros((6), dtype= np.float) |
---|
1958 | lastTvec = np.zeros((6), dtype= np.float) |
---|
1959 | chTvec = np.zeros((6), dtype= bool) |
---|
1960 | |
---|
1961 | firstTvec = np.array([firstTdt.year, firstTdt.month, firstTdt.day, firstTdt.hour,\ |
---|
1962 | firstTdt.minute, firstTdt.second]) |
---|
1963 | lastTvec = np.array([lastTdt.year, lastTdt.month, lastTdt.day, lastTdt.hour, \ |
---|
1964 | lastTdt.minute, lastTdt.second]) |
---|
1965 | |
---|
1966 | chdate= lastTvec - firstTvec |
---|
1967 | chTvec = np.where (chdate != 0., True, False) |
---|
1968 | |
---|
1969 | TOTdt = lastTdt - firstTdt |
---|
1970 | TOTdtsecs = TOTdt.days*secsDay + TOTdt.seconds + TOTdt.microseconds*secsMicrosecond |
---|
1971 | |
---|
1972 | timeout = [] |
---|
1973 | if okind == 'Nval': |
---|
1974 | nvalues = int(kind.split(',')[1]) |
---|
1975 | intervT = (lastT - firstT)/(nvalues-1) |
---|
1976 | dtintervT = intT2dt(intervT, trefu) |
---|
1977 | |
---|
1978 | for it in range(nvalues): |
---|
1979 | timeout.append(firstTdt + dtintervT*it) |
---|
1980 | elif okind == 'exct': |
---|
1981 | Nunits = int(kind.split(',')[1]) |
---|
1982 | tu = kind.split(',')[2] |
---|
1983 | |
---|
1984 | # Generic incremental dt [seconds] according to all the possibilities ['c', 'y', 'm', |
---|
1985 | # 'w', 'd', 'h', 'i', 's', 'l'], some of them approximated (because they are not |
---|
1986 | # already necessary!) |
---|
1987 | basedt = np.zeros((9), dtype=np.float) |
---|
1988 | basedt[0] = (365.*100. + 25.)*24.*3600. |
---|
1989 | basedt[1] = secsYear |
---|
1990 | basedt[2] = 31.*24.*3600. |
---|
1991 | basedt[3] = secsWeek |
---|
1992 | basedt[4] = secsDay |
---|
1993 | basedt[5] = secsHour |
---|
1994 | basedt[6] = secsMinute |
---|
1995 | basedt[7] = 1. |
---|
1996 | basedt[8] = secsMilisecond |
---|
1997 | |
---|
1998 | # Increment according to the units of the CF dates |
---|
1999 | if trefunits == 'weeks': |
---|
2000 | basedt = basedt/(secsWeek) |
---|
2001 | elif trefunits == 'days': |
---|
2002 | basedt = basedt/(secsDay) |
---|
2003 | elif trefunits == 'hours': |
---|
2004 | basedt = basedt/(secsHour) |
---|
2005 | elif trefunits == 'minutes': |
---|
2006 | basedt = basedt/(secsMinute) |
---|
2007 | elif trefunits == 'seconds': |
---|
2008 | basedt = basedt |
---|
2009 | elif trefunits == 'milliseconds': |
---|
2010 | basedt = basedt*secsMilisecond |
---|
2011 | |
---|
2012 | if tu == 'c': |
---|
2013 | ti = firstTvec[0] |
---|
2014 | tf = lastTvec[0] |
---|
2015 | centi = firstTvec[0] / 100 |
---|
2016 | |
---|
2017 | datev = firstTdt |
---|
2018 | while datev < lastTdt: |
---|
2019 | yr = datev.year + Nunits*100 |
---|
2020 | mon = datev.month |
---|
2021 | datev = dt.datetime(yr, mon, 1, 0, 0, 0) |
---|
2022 | timeout.append(datev) |
---|
2023 | |
---|
2024 | elif tu == 'y': |
---|
2025 | ti = firstTvec[0] |
---|
2026 | tf = lastTvec[0] |
---|
2027 | yeari = firstTvec[0] |
---|
2028 | |
---|
2029 | TOTsteps = int(TOTdtsecs/(Nunits*31*secsDay)) + 1 |
---|
2030 | |
---|
2031 | datev = firstTdt |
---|
2032 | while datev < lastTdt: |
---|
2033 | yr = datev.year + Nunits |
---|
2034 | mon = datev.month |
---|
2035 | datev = dt.datetime(yr, mon, 1, 0, 0, 0) |
---|
2036 | timeout.append(datev) |
---|
2037 | |
---|
2038 | elif tu == 'm': |
---|
2039 | ti = firstTvec[1] |
---|
2040 | tf = lastTvec[1] |
---|
2041 | |
---|
2042 | yr = firstTvec[0] |
---|
2043 | mon = firstTvec[1] |
---|
2044 | |
---|
2045 | TOTsteps = int(TOTdtsecs/(Nunits*31*secsDay)) + 1 |
---|
2046 | |
---|
2047 | datev = firstTdt |
---|
2048 | while datev < lastTdt: |
---|
2049 | mon = datev.month + Nunits |
---|
2050 | if mon > 12: |
---|
2051 | yr = yr + 1 |
---|
2052 | mon = 1 |
---|
2053 | datev = dt.datetime(yr, mon, 1, 0, 0, 0) |
---|
2054 | timeout.append(datev) |
---|
2055 | |
---|
2056 | elif tu == 'w': |
---|
2057 | datev=firstTdt |
---|
2058 | it=0 |
---|
2059 | while datev <= lastTdt: |
---|
2060 | datev = firstTdt + dt.timedelta(days=7*Nunits*it) |
---|
2061 | timeout.append(datev) |
---|
2062 | it = it + 1 |
---|
2063 | elif tu == 'd': |
---|
2064 | # datev=firstTdt |
---|
2065 | yr = firstTvec[0] |
---|
2066 | mon = firstTvec[1] |
---|
2067 | day = firstTvec[2] |
---|
2068 | |
---|
2069 | Iunits = np.mod(hour,Nunits) |
---|
2070 | if np.sum(firstTvec[2:5]) > 0: |
---|
2071 | firstTdt = dt.datetime(yr, mon, day+1, 0, 0, 0) |
---|
2072 | datev = dt.datetime(yr, mon, day+1, 0, 0, 0) |
---|
2073 | elif Iunits != 0: |
---|
2074 | nNunits = int(day/Nunits) |
---|
2075 | firstTdt = dt.datetime(yr, mon, nNunits*Nunits, 0, 0, 0) |
---|
2076 | datev = dt.datetime(yr, mon, nNunits*Nunits, 0, 0, 0) |
---|
2077 | else: |
---|
2078 | firstTdt = dt.datetime(yr, mon, day, 0, 0, 0) |
---|
2079 | datev = dt.datetime(yr, mon, day, 0, 0, 0) |
---|
2080 | |
---|
2081 | it=0 |
---|
2082 | while datev <= lastTdt: |
---|
2083 | datev = firstTdt + dt.timedelta(days=Nunits*it) |
---|
2084 | timeout.append(datev) |
---|
2085 | it = it + 1 |
---|
2086 | |
---|
2087 | elif tu == 'h': |
---|
2088 | datev=firstTdt |
---|
2089 | yr = firstTvec[0] |
---|
2090 | mon = firstTvec[1] |
---|
2091 | day = firstTvec[2] |
---|
2092 | hour = firstTvec[3] |
---|
2093 | |
---|
2094 | Iunits = np.mod(hour,Nunits) |
---|
2095 | if np.sum(firstTvec[4:5]) > 0 or Iunits != 0: |
---|
2096 | tadvance = 2*Nunits |
---|
2097 | if tadvance >= 24: |
---|
2098 | firstTdt = dt.datetime(yr, mon, day+1, 0, 0, 0) |
---|
2099 | datev = dt.datetime(yr, mon, day+1, 0, 0, 0) |
---|
2100 | else: |
---|
2101 | nNunits = int(hour/Nunits) |
---|
2102 | firstTdt = dt.datetime(yr, mon, day, nNunits*Nunits, 0, 0) |
---|
2103 | datev = dt.datetime(yr, mon, day, nNunits*Nunits, 0, 0) |
---|
2104 | else: |
---|
2105 | firstTdt = dt.datetime(yr, mon, day, hour, 0, 0) |
---|
2106 | datev = dt.datetime(yr, mon, day, hour, 0, 0) |
---|
2107 | |
---|
2108 | it=0 |
---|
2109 | while datev <= lastTdt: |
---|
2110 | datev = firstTdt + dt.timedelta(seconds=Nunits*3600*it) |
---|
2111 | timeout.append(datev) |
---|
2112 | it = it + 1 |
---|
2113 | elif tu == 'i': |
---|
2114 | datev=firstTdt |
---|
2115 | yr = firstTvec[0] |
---|
2116 | mon = firstTvec[1] |
---|
2117 | day = firstTvec[2] |
---|
2118 | hour = firstTvec[3] |
---|
2119 | minu = firstTvec[4] |
---|
2120 | |
---|
2121 | Iunits = np.mod(minu,Nunits) |
---|
2122 | if firstTvec[5] > 0 or Iunits != 0: |
---|
2123 | tadvance = 2*Nunits |
---|
2124 | if tadvance >= 60: |
---|
2125 | firstTdt = dt.datetime(yr, mon, day, hour, 0, 0) |
---|
2126 | datev = dt.datetime(yr, mon, day, hour, 0, 0) |
---|
2127 | else: |
---|
2128 | nNunits = int(minu/Nunits) |
---|
2129 | firstTdt = dt.datetime(yr, mon, day, hour, nNunits*Nunits, 0) |
---|
2130 | datev = dt.datetime(yr, mon, day, hour, nNunits*Nunits, 0) |
---|
2131 | else: |
---|
2132 | firstTdt = dt.datetime(yr, mon, day, hour, minu, 0) |
---|
2133 | datev = dt.datetime(yr, mon, day, hour, minu, 0) |
---|
2134 | it=0 |
---|
2135 | while datev <= lastTdt: |
---|
2136 | datev = firstTdt + dt.timedelta(seconds=Nunits*60*it) |
---|
2137 | timeout.append(datev) |
---|
2138 | it = it + 1 |
---|
2139 | elif tu == 's': |
---|
2140 | datev=firstTdt |
---|
2141 | yr = firstTvec[0] |
---|
2142 | mon = firstTvec[1] |
---|
2143 | day = firstTvec[2] |
---|
2144 | hour = firstTvec[3] |
---|
2145 | min = firstTvec[4] |
---|
2146 | secu = firstTvec[5] |
---|
2147 | |
---|
2148 | Iunits = np.mod(secu,Nunits) |
---|
2149 | if firstTvec[5] > 0 or Iunits != 0: |
---|
2150 | tadvance = 2*Nunits |
---|
2151 | if tadvance >= 60: |
---|
2152 | firstTdt = dt.datetime(yr, mon, day, hour, min, 0) |
---|
2153 | datev = dt.datetime(yr, mon, day, hour, min, 0) |
---|
2154 | else: |
---|
2155 | nNunits = int(minu/Nunits) |
---|
2156 | firstTdt = dt.datetime(yr, mon, day, hour, min, nNunits*Nunits) |
---|
2157 | datev = dt.datetime(yr, mon, day, hour, min, nNunits*Nunits) |
---|
2158 | else: |
---|
2159 | firstTdt = dt.datetime(yr, mon, day, hour, min, secu) |
---|
2160 | datev = dt.datetime(yr, mon, day, hour, min, secu) |
---|
2161 | it=0 |
---|
2162 | while datev <= lastTdt: |
---|
2163 | datev = firstTdt + dt.timedelta(seconds=Nunits*it) |
---|
2164 | timeout.append(datev) |
---|
2165 | it = it + 1 |
---|
2166 | elif tu == 'l': |
---|
2167 | datev=firstTdt |
---|
2168 | it=0 |
---|
2169 | while datev <= lastTdt: |
---|
2170 | datev = firstTdt + dt.timedelta(seconds=Nunits*it/1000.) |
---|
2171 | timeout.append(datev) |
---|
2172 | it = it + 1 |
---|
2173 | else: |
---|
2174 | print errormsg |
---|
2175 | print ' ' + fname + ': exact units "' + tu + '" not ready!!!!!' |
---|
2176 | quit(-1) |
---|
2177 | |
---|
2178 | else: |
---|
2179 | print errormsg |
---|
2180 | print ' ' + fname + ': output kind "' + okind + '" not ready!!!!' |
---|
2181 | quit(-1) |
---|
2182 | |
---|
2183 | dtout = len(timeout) |
---|
2184 | |
---|
2185 | timeoutS = [] |
---|
2186 | timeoutv = np.zeros((dtout), dtype=np.float) |
---|
2187 | |
---|
2188 | for it in range(dtout): |
---|
2189 | timeoutS.append(timeout[it].strftime(tfmt)) |
---|
2190 | timeoutv[it] = date_CFtime(timeout[it], refdate, trefunits) |
---|
2191 | |
---|
2192 | # print it,':',timeoutv[it], timeoutS[it] |
---|
2193 | |
---|
2194 | if len(timeoutv) < 1 or len(timeoutS) < 1: |
---|
2195 | print errormsg |
---|
2196 | print ' ' + fname + ': no time values are generated!' |
---|
2197 | print ' values passed:',timev |
---|
2198 | print ' units:',units |
---|
2199 | print ' desired kind:',kind |
---|
2200 | print ' format:',tfmt |
---|
2201 | print ' function values ___ __ _' |
---|
2202 | print ' reference date:',refdate |
---|
2203 | print ' first date:',firstTdt |
---|
2204 | print ' last date:',lastTdt |
---|
2205 | print ' icrement:',basedt,trefunits |
---|
2206 | |
---|
2207 | quit(-1) |
---|
2208 | |
---|
2209 | return timeoutv, timeoutS |
---|
2210 | |
---|
2211 | def color_lines(Nlines): |
---|
2212 | """ Function to provide a color list to plot lines |
---|
2213 | color_lines(Nlines) |
---|
2214 | Nlines= number of lines |
---|
2215 | """ |
---|
2216 | |
---|
2217 | fname = 'color_lines' |
---|
2218 | |
---|
2219 | colors = ['r', 'b', 'g', 'p', 'g'] |
---|
2220 | |
---|
2221 | colorv = [] |
---|
2222 | |
---|
2223 | colorv.append('k') |
---|
2224 | for icol in range(Nlines): |
---|
2225 | colorv.append(colors[icol]) |
---|
2226 | |
---|
2227 | |
---|
2228 | return colorv |
---|
2229 | |
---|
2230 | def output_kind(kindf, namef, close): |
---|
2231 | """ Function to generate the output of the figure |
---|
2232 | kindf= kind of the output |
---|
2233 | null: show in screen |
---|
2234 | [jpg/pdf/png/ps]: standard output types |
---|
2235 | namef= name of the figure (without extension) |
---|
2236 | close= if the graph has to be close or not [True/False] |
---|
2237 | """ |
---|
2238 | fname = 'output_kind' |
---|
2239 | |
---|
2240 | if kindf == 'h': |
---|
2241 | print fname + '_____________________________________________________________' |
---|
2242 | print output_kind.__doc__ |
---|
2243 | quit() |
---|
2244 | |
---|
2245 | if kindf == 'null': |
---|
2246 | print 'showing figure...' |
---|
2247 | plt.show() |
---|
2248 | elif kindf == 'gif': |
---|
2249 | plt.savefig(namef + ".gif") |
---|
2250 | if close: print "Successfully generation of figure '" + namef + ".jpg' !!!" |
---|
2251 | elif kindf == 'jpg': |
---|
2252 | plt.savefig(namef + ".jpg") |
---|
2253 | if close: print "Successfully generation of figure '" + namef + ".jpg' !!!" |
---|
2254 | elif kindf == 'pdf': |
---|
2255 | plt.savefig(namef + ".pdf") |
---|
2256 | if close: print "Successfully generation of figure '" + namef + ".pdf' !!!" |
---|
2257 | elif kindf == 'png': |
---|
2258 | plt.savefig(namef + ".png") |
---|
2259 | if close: print "Successfully generation of figure '" + namef + ".png' !!!" |
---|
2260 | elif kindf == 'ps': |
---|
2261 | plt.savefig(namef + ".ps") |
---|
2262 | if close: print "Successfully generation of figure '" + namef + ".ps' !!!" |
---|
2263 | else: |
---|
2264 | print errormsg |
---|
2265 | print ' ' + fname + ' output format: "' + kindf + '" not ready !!' |
---|
2266 | print errormsg |
---|
2267 | quit(-1) |
---|
2268 | |
---|
2269 | if close: |
---|
2270 | plt.close() |
---|
2271 | |
---|
2272 | return |
---|
2273 | |
---|
2274 | def check_arguments(funcname,Nargs,args,char,expectargs): |
---|
2275 | """ Function to check the number of arguments if they are coincident |
---|
2276 | check_arguments(funcname,Nargs,args,char) |
---|
2277 | funcname= name of the function/program to check |
---|
2278 | Nargs= theoretical number of arguments |
---|
2279 | args= passed arguments |
---|
2280 | char= character used to split the arguments |
---|
2281 | """ |
---|
2282 | |
---|
2283 | fname = 'check_arguments' |
---|
2284 | |
---|
2285 | Nvals = len(args.split(char)) |
---|
2286 | if Nvals != Nargs: |
---|
2287 | print errormsg |
---|
2288 | print ' ' + fname + ': wrong number of arguments:',Nvals," passed to '", \ |
---|
2289 | funcname, "' which requires:",Nargs,'!!' |
---|
2290 | print ' given arguments:',args.split(char) |
---|
2291 | print ' expected arguments:',expectargs |
---|
2292 | quit(-1) |
---|
2293 | |
---|
2294 | return |
---|
2295 | |
---|
2296 | def Str_Bool(val): |
---|
2297 | """ Function to transform from a String value to a boolean one |
---|
2298 | >>> Str_Bool('True') |
---|
2299 | True |
---|
2300 | >>> Str_Bool('0') |
---|
2301 | False |
---|
2302 | >>> Str_Bool('no') |
---|
2303 | False |
---|
2304 | """ |
---|
2305 | |
---|
2306 | fname = 'Str_Bool' |
---|
2307 | |
---|
2308 | if val == 'True' or val == 'true' or val == '1' or val == 'yes': |
---|
2309 | boolv = True |
---|
2310 | elif val == 'False' or val == 'false' or val == '0' or val== 'no': |
---|
2311 | boolv = False |
---|
2312 | else: |
---|
2313 | print errormsg |
---|
2314 | print ' ' + fname + ": value '" + val + "' not ready!!" |
---|
2315 | quit(-1) |
---|
2316 | |
---|
2317 | return boolv |
---|
2318 | |
---|
2319 | def coincident_CFtimes(tvalB, tunitA, tunitB): |
---|
2320 | """ Function to make coincident times for two different sets of CFtimes |
---|
2321 | tvalB= time values B |
---|
2322 | tunitA= time units times A to which we want to make coincidence |
---|
2323 | tunitB= time units times B |
---|
2324 | >>> coincident_CFtimes(np.arange(10),'seconds since 1949-12-01 00:00:00', |
---|
2325 | 'hours since 1949-12-01 00:00:00') |
---|
2326 | [ 0. 3600. 7200. 10800. 14400. 18000. 21600. 25200. 28800. 32400.] |
---|
2327 | >>> coincident_CFtimes(np.arange(10),'seconds since 1949-12-01 00:00:00', |
---|
2328 | 'hours since 1979-12-01 00:00:00') |
---|
2329 | [ 9.46684800e+08 9.46688400e+08 9.46692000e+08 9.46695600e+08 |
---|
2330 | 9.46699200e+08 9.46702800e+08 9.46706400e+08 9.46710000e+08 |
---|
2331 | 9.46713600e+08 9.46717200e+08] |
---|
2332 | """ |
---|
2333 | import datetime as dt |
---|
2334 | fname = 'coincident_CFtimes' |
---|
2335 | |
---|
2336 | trefA = tunitA.split(' ')[2] + ' ' + tunitA.split(' ')[3] |
---|
2337 | trefB = tunitB.split(' ')[2] + ' ' + tunitB.split(' ')[3] |
---|
2338 | tuA = tunitA.split(' ')[0] |
---|
2339 | tuB = tunitB.split(' ')[0] |
---|
2340 | |
---|
2341 | if tuA != tuB: |
---|
2342 | if tuA == 'microseconds': |
---|
2343 | if tuB == 'microseconds': |
---|
2344 | tB = tvalB*1. |
---|
2345 | elif tuB == 'seconds': |
---|
2346 | tB = tvalB*10.e6 |
---|
2347 | elif tuB == 'minutes': |
---|
2348 | tB = tvalB*60.*10.e6 |
---|
2349 | elif tuB == 'hours': |
---|
2350 | tB = tvalB*3600.*10.e6 |
---|
2351 | elif tuB == 'days': |
---|
2352 | tB = tvalB*3600.*24.*10.e6 |
---|
2353 | else: |
---|
2354 | print errormsg |
---|
2355 | print ' ' + fname + ": combination of time untis: '" + tuA + \ |
---|
2356 | "' & '" + tuB + "' not ready !!" |
---|
2357 | quit(-1) |
---|
2358 | elif tuA == 'seconds': |
---|
2359 | if tuB == 'microseconds': |
---|
2360 | tB = tvalB/10.e6 |
---|
2361 | elif tuB == 'seconds': |
---|
2362 | tB = tvalB*1. |
---|
2363 | elif tuB == 'minutes': |
---|
2364 | tB = tvalB*60. |
---|
2365 | elif tuB == 'hours': |
---|
2366 | tB = tvalB*3600. |
---|
2367 | elif tuB == 'days': |
---|
2368 | tB = tvalB*3600.*24. |
---|
2369 | else: |
---|
2370 | print errormsg |
---|
2371 | print ' ' + fname + ": combination of time untis: '" + tuA + \ |
---|
2372 | "' & '" + tuB + "' not ready !!" |
---|
2373 | quit(-1) |
---|
2374 | elif tuA == 'minutes': |
---|
2375 | if tuB == 'microseconds': |
---|
2376 | tB = tvalB/(60.*10.e6) |
---|
2377 | elif tuB == 'seconds': |
---|
2378 | tB = tvalB/60. |
---|
2379 | elif tuB == 'minutes': |
---|
2380 | tB = tvalB*1. |
---|
2381 | elif tuB == 'hours': |
---|
2382 | tB = tvalB*60. |
---|
2383 | elif tuB == 'days': |
---|
2384 | tB = tvalB*60.*24. |
---|
2385 | else: |
---|
2386 | print errormsg |
---|
2387 | print ' ' + fname + ": combination of time untis: '" + tuA + \ |
---|
2388 | "' & '" + tuB + "' not ready !!" |
---|
2389 | quit(-1) |
---|
2390 | elif tuA == 'hours': |
---|
2391 | if tuB == 'microseconds': |
---|
2392 | tB = tvalB/(3600.*10.e6) |
---|
2393 | elif tuB == 'seconds': |
---|
2394 | tB = tvalB/3600. |
---|
2395 | elif tuB == 'minutes': |
---|
2396 | tB = tvalB/60. |
---|
2397 | elif tuB == 'hours': |
---|
2398 | tB = tvalB*1. |
---|
2399 | elif tuB == 'days': |
---|
2400 | tB = tvalB*24. |
---|
2401 | else: |
---|
2402 | print errormsg |
---|
2403 | print ' ' + fname + ": combination of time untis: '" + tuA + \ |
---|
2404 | "' & '" + tuB + "' not ready !!" |
---|
2405 | quit(-1) |
---|
2406 | elif tuA == 'days': |
---|
2407 | if tuB == 'microseconds': |
---|
2408 | tB = tvalB/(24.*3600.*10.e6) |
---|
2409 | elif tuB == 'seconds': |
---|
2410 | tB = tvalB/(24.*3600.) |
---|
2411 | elif tuB == 'minutes': |
---|
2412 | tB = tvalB/(24.*60.) |
---|
2413 | elif tuB == 'hours': |
---|
2414 | tB = tvalB/24. |
---|
2415 | elif tuB == 'days': |
---|
2416 | tB = tvalB*1. |
---|
2417 | else: |
---|
2418 | print errormsg |
---|
2419 | print ' ' + fname + ": combination of time untis: '" + tuA + \ |
---|
2420 | "' & '" + tuB + "' not ready !!" |
---|
2421 | quit(-1) |
---|
2422 | else: |
---|
2423 | print errormsg |
---|
2424 | print ' ' + fname + ": time untis: '" + tuA + "' not ready !!" |
---|
2425 | quit(-1) |
---|
2426 | else: |
---|
2427 | tB = tvalB*1. |
---|
2428 | |
---|
2429 | if trefA != trefB: |
---|
2430 | trefTA = dt.datetime.strptime(trefA, '%Y-%m-%d %H:%M:%S') |
---|
2431 | trefTB = dt.datetime.strptime(trefB, '%Y-%m-%d %H:%M:%S') |
---|
2432 | |
---|
2433 | difft = trefTB - trefTA |
---|
2434 | diffv = difft.days*24.*3600.*10.e6 + difft.seconds*10.e6 + difft.microseconds |
---|
2435 | print ' ' + fname + ': different reference refA:',trefTA,'refB',trefTB |
---|
2436 | print ' difference:',difft,':',diffv,'microseconds' |
---|
2437 | |
---|
2438 | if tuA == 'microseconds': |
---|
2439 | tB = tB + diffv |
---|
2440 | elif tuA == 'seconds': |
---|
2441 | tB = tB + diffv/10.e6 |
---|
2442 | elif tuA == 'minutes': |
---|
2443 | tB = tB + diffv/(60.*10.e6) |
---|
2444 | elif tuA == 'hours': |
---|
2445 | tB = tB + diffv/(3600.*10.e6) |
---|
2446 | elif tuA == 'dayss': |
---|
2447 | tB = tB + diffv/(24.*3600.*10.e6) |
---|
2448 | else: |
---|
2449 | print errormsg |
---|
2450 | print ' ' + fname + ": time untis: '" + tuA + "' not ready !!" |
---|
2451 | quit(-1) |
---|
2452 | |
---|
2453 | return tB |
---|
2454 | |
---|
2455 | ####### ###### ##### #### ### ## # |
---|
2456 | |
---|
2457 | def plot_TimeSeries(valtimes, vunits, tunits, hfileout, vtit, ttit, tkind, tformat, \ |
---|
2458 | tit, linesn, lloc, kfig,coll,ptl): |
---|
2459 | """ Function to draw time-series |
---|
2460 | valtimes= list of arrays to plot [vals1[1values, 1times], [...,valsM[Mvals,Mtimes]]) |
---|
2461 | vunits= units of the values |
---|
2462 | tunits= units of the times |
---|
2463 | hfileout= header of the output figure. Final name: [hfileout]_[vtit].[kfig] |
---|
2464 | vtit= variable title to be used in the graph |
---|
2465 | ttit= time title to be used in the graph |
---|
2466 | tkind= kind of time values to appear in the x-axis |
---|
2467 | 'Nval': according to a given number of values as 'Nval',[Nval] |
---|
2468 | 'exct': according to an exact time unit as 'exct',[tunit]; |
---|
2469 | tunit= [Nunits],[tu]; [tu]= 'c': centuries, 'y': year, 'm': month, |
---|
2470 | 'w': week, 'd': day, 'h': hour, 'i': minute, 's': second, |
---|
2471 | 'l': milisecond |
---|
2472 | tformat= desired format of times |
---|
2473 | tit= title of the graph |
---|
2474 | linesn= list of values fot the legend |
---|
2475 | lloc= location of the legend (0, autmoatic) |
---|
2476 | 1: 'upper right', 2: 'upper left', 3: 'lower left', 4: 'lower right', |
---|
2477 | 5: 'right', 6: 'center left', 7: 'center right', 8: 'lower center', |
---|
2478 | 9: 'upper center', 10: 'center' |
---|
2479 | kfig= type of figure: jpg, png, pds, ps |
---|
2480 | coll= ',' list of colors for the lines, None for automatic, single |
---|
2481 | value all the same |
---|
2482 | ptl= ',' list of type of points for the lines, None for automatic, single |
---|
2483 | value all the same |
---|
2484 | """ |
---|
2485 | fname = 'plot_TimeSeries' |
---|
2486 | |
---|
2487 | if valtimes == 'h': |
---|
2488 | print fname + '_____________________________________________________________' |
---|
2489 | print plot_TimeSeries.__doc__ |
---|
2490 | quit() |
---|
2491 | |
---|
2492 | Nlines = len(linesn) |
---|
2493 | # Canging line kinds every 7 lines (end of standard colors) |
---|
2494 | linekinds = [] |
---|
2495 | if ptl is None: |
---|
2496 | linekindsauto=['.-','x-','o-'] |
---|
2497 | for ptype in range(4): |
---|
2498 | for ip in range(7): |
---|
2499 | linekinds.append(linekindsauto[ptype]) |
---|
2500 | else: |
---|
2501 | if len(ptl) > 1: |
---|
2502 | linekinds = ptl |
---|
2503 | else: |
---|
2504 | for il in range(Nlines): |
---|
2505 | linekinds.append(ptl+'-') |
---|
2506 | |
---|
2507 | Nvalues = [] |
---|
2508 | Ntimes = [] |
---|
2509 | |
---|
2510 | for il in range(Nlines): |
---|
2511 | array = valtimes[il] |
---|
2512 | |
---|
2513 | if Nlines == 1: |
---|
2514 | print warnmsg |
---|
2515 | print ' ' + fname + ': drawing only one line!' |
---|
2516 | |
---|
2517 | Nvalues.append(array.shape[1]) |
---|
2518 | Ntimes.append(array.shape[0]) |
---|
2519 | tmin = np.min(array[1]) |
---|
2520 | tmax = np.max(array[1]) |
---|
2521 | vmin = np.min(array[0]) |
---|
2522 | vmax = np.max(array[0]) |
---|
2523 | else: |
---|
2524 | Nvalues.append(array.shape[1]) |
---|
2525 | Ntimes.append(array.shape[0]) |
---|
2526 | tmin = np.min(array[1,:]) |
---|
2527 | tmax = np.max(array[1,:]) |
---|
2528 | vmin = np.min(array[0,:]) |
---|
2529 | vmax = np.max(array[0,:]) |
---|
2530 | |
---|
2531 | if il == 0: |
---|
2532 | xmin = tmin |
---|
2533 | xmax = tmax |
---|
2534 | ymin = vmin |
---|
2535 | ymax = vmax |
---|
2536 | else: |
---|
2537 | if tmin < xmin: xmin = tmin |
---|
2538 | if tmax > xmax: xmax = tmax |
---|
2539 | if vmin < ymin: ymin = vmin |
---|
2540 | if vmax > ymax: ymax = vmax |
---|
2541 | print il,'Lluis: ymin;',ymin,'ymax;',ymax |
---|
2542 | |
---|
2543 | dx = np.max(Ntimes) |
---|
2544 | dy = np.min(Nvalues) |
---|
2545 | |
---|
2546 | plt.rc('text', usetex=True) |
---|
2547 | |
---|
2548 | print vtit |
---|
2549 | if vtit == 'ps': |
---|
2550 | plt.ylim(98000.,ymax) |
---|
2551 | else: |
---|
2552 | plt.ylim(ymin,ymax) |
---|
2553 | |
---|
2554 | plt.xlim(xmin,xmax) |
---|
2555 | # print 'x lim:',xmin,xmax |
---|
2556 | # print 'y lim:',ymin,ymax |
---|
2557 | |
---|
2558 | N7lines=0 |
---|
2559 | for il in range(Nlines): |
---|
2560 | array = valtimes[il] |
---|
2561 | if vtit == 'ps': |
---|
2562 | array[0,:] = np.where(array[0,:] < 98000., None, array[0,:]) |
---|
2563 | |
---|
2564 | if coll is None: |
---|
2565 | plt.plot(array[1,:],array[0,:], linekinds[il], label= linesn[il]) |
---|
2566 | else: |
---|
2567 | plt.plot(array[1,:],array[0,:], linekinds[il], label= linesn[il], \ |
---|
2568 | color=coll[il]) |
---|
2569 | |
---|
2570 | timevals = np.arange(xmin,xmax)*1. |
---|
2571 | |
---|
2572 | print 'Lluis tunits:',tunits |
---|
2573 | tpos, tlabels = CFtimes_plot(timevals, tunits, tkind, tformat) |
---|
2574 | |
---|
2575 | if len(tpos) > 10: |
---|
2576 | print warnmsg |
---|
2577 | print ' ' + fname + ': with "' + tkind + '" there are', len(tpos), 'xticks !' |
---|
2578 | |
---|
2579 | plt.xticks(tpos, tlabels) |
---|
2580 | # plt.Axes.set_xticklabels(tlabels) |
---|
2581 | |
---|
2582 | plt.legend(loc=lloc) |
---|
2583 | plt.xlabel(ttit) |
---|
2584 | plt.ylabel(vtit + " (" + vunits + ")") |
---|
2585 | plt.title(tit.replace('_','\_').replace('&','\&')) |
---|
2586 | |
---|
2587 | figname = hfileout + '_' + vtit |
---|
2588 | |
---|
2589 | output_kind(kfig, figname, True) |
---|
2590 | |
---|
2591 | return |
---|
2592 | |
---|
2593 | #Nt = 50 |
---|
2594 | #Nlines = 3 |
---|
2595 | |
---|
2596 | #vtvalsv = [] |
---|
2597 | |
---|
2598 | #valsv = np.zeros((2,Nt), dtype=np.float) |
---|
2599 | ## First |
---|
2600 | #valsv[0,:] = np.arange(Nt) |
---|
2601 | #valsv[1,:] = np.arange(Nt)*180. |
---|
2602 | #vtvalsv.append(valsv) |
---|
2603 | #del(valsv) |
---|
2604 | |
---|
2605 | #valsv = np.zeros((2,Nt/2), dtype=np.float) |
---|
2606 | ## Second |
---|
2607 | #valsv[0,:] = np.arange(Nt/2) |
---|
2608 | #valsv[1,:] = np.arange(Nt/2)*180.*2. |
---|
2609 | #vtvalsv.append(valsv) |
---|
2610 | #del(valsv) |
---|
2611 | |
---|
2612 | #valsv = np.zeros((2,Nt/4), dtype=np.float) |
---|
2613 | ## Third |
---|
2614 | #valsv[0,:] = np.arange(Nt/4) |
---|
2615 | #valsv[1,:] = np.arange(Nt/4)*180.*4. |
---|
2616 | #vtvalsv.append(valsv) |
---|
2617 | #del(valsv) |
---|
2618 | |
---|
2619 | #varu='mm' |
---|
2620 | #timeu='seconds' |
---|
2621 | |
---|
2622 | #title='test' |
---|
2623 | #linesname = ['line 1', 'line 2', 'line 3'] |
---|
2624 | |
---|
2625 | #plot_TimeSeries(vtvalsv, units_lunits(varu), timeu, 'test', 'vartest', 'time', title, linesname, 'png') |
---|
2626 | #quit() |
---|
2627 | |
---|
2628 | def plot_points(xval, yval, vlon, vlat, extravals, extrapar, vtit, mapv, figk, color,\ |
---|
2629 | labels, lloc, kfig, figname): |
---|
2630 | """ plotting points |
---|
2631 | [x/yval]: x,y values to plot |
---|
2632 | vlon= 2D-matrix with the longitudes |
---|
2633 | vlat= 2D-matrix with the latitudes |
---|
2634 | extravals= extra values to be added into the plot (None for nothing) |
---|
2635 | extrapar= [varname, min, max, cbar, varunits] of the extra variable |
---|
2636 | vtit= title of the graph ('|' for spaces) |
---|
2637 | mapv= map characteristics: [proj],[res] |
---|
2638 | see full documentation: http://matplotlib.org/basemap/ |
---|
2639 | [proj]: projection |
---|
2640 | * 'cyl', cilindric |
---|
2641 | * 'lcc', lambert-conformal |
---|
2642 | [res]: resolution: |
---|
2643 | * 'c', crude |
---|
2644 | * 'l', low |
---|
2645 | * 'i', intermediate |
---|
2646 | * 'h', high |
---|
2647 | * 'f', full |
---|
2648 | figK= kind of figure |
---|
2649 | 'legend': only points in the map with the legend with the names |
---|
2650 | 'labelled',[txtsize],[txtcol]: points with the names and size, color of text |
---|
2651 | color= color for the points/labels ('auto', for "red") |
---|
2652 | labels= list of labels for the points (None, no labels) |
---|
2653 | lloc = localisation of the legend |
---|
2654 | kfig= kind of figure (jpg, pdf, png) |
---|
2655 | figname= name of the figure |
---|
2656 | |
---|
2657 | """ |
---|
2658 | fname = 'plot_points' |
---|
2659 | # Canging line kinds every 7 pts (end of standard colors) |
---|
2660 | ptkinds=['.','x','o','*','+','8','>','D','h','p','s'] |
---|
2661 | |
---|
2662 | Npts = len(xval) |
---|
2663 | if Npts > len(ptkinds)*7: |
---|
2664 | print errormsg |
---|
2665 | print ' ' + fname + ': too many',Npts,'points!!' |
---|
2666 | print " enlarge 'ptkinds' list" |
---|
2667 | quit(-1) |
---|
2668 | |
---|
2669 | N7pts = 0 |
---|
2670 | |
---|
2671 | if color == 'auto': |
---|
2672 | ptcol = "red" |
---|
2673 | else: |
---|
2674 | ptcol = color |
---|
2675 | |
---|
2676 | dx=vlon.shape[1] |
---|
2677 | dy=vlat.shape[0] |
---|
2678 | |
---|
2679 | plt.rc('text', usetex=True) |
---|
2680 | |
---|
2681 | if not mapv is None: |
---|
2682 | # vlon = np.where(vlon[:] < 0., 360. + vlon[:], vlon[:]) |
---|
2683 | # xvala = np.array(xval) |
---|
2684 | # xvala = np.where(xvala < 0., 360. + xvala, xvala) |
---|
2685 | # xval = list(xvala) |
---|
2686 | |
---|
2687 | map_proj=mapv.split(',')[0] |
---|
2688 | map_res=mapv.split(',')[1] |
---|
2689 | |
---|
2690 | nlon = np.min(vlon) |
---|
2691 | xlon = np.max(vlon) |
---|
2692 | nlat = np.min(vlat) |
---|
2693 | xlat = np.max(vlat) |
---|
2694 | |
---|
2695 | lon2 = vlon[dy/2,dx/2] |
---|
2696 | lat2 = vlat[dy/2,dx/2] |
---|
2697 | |
---|
2698 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
2699 | xlon, ',', xlat |
---|
2700 | |
---|
2701 | if map_proj == 'cyl': |
---|
2702 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
2703 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
2704 | elif map_proj == 'lcc': |
---|
2705 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
2706 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
2707 | else: |
---|
2708 | print errormsg |
---|
2709 | print ' ' + fname + ": map projecion '" + map_proj + "' not ready!!" |
---|
2710 | print ' available: cyl, lcc' |
---|
2711 | quit(-1) |
---|
2712 | |
---|
2713 | # lons, lats = np.meshgrid(vlon, vlat) |
---|
2714 | # lons = np.where(lons < 0., lons + 360., lons) |
---|
2715 | |
---|
2716 | x,y = m(vlon,vlat) |
---|
2717 | |
---|
2718 | m.drawcoastlines() |
---|
2719 | |
---|
2720 | meridians = pretty_int(nlon,xlon,5) |
---|
2721 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
2722 | |
---|
2723 | parallels = pretty_int(nlat,xlat,5) |
---|
2724 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
2725 | else: |
---|
2726 | x = vlon |
---|
2727 | y = vlat |
---|
2728 | # plt.xlim(0,dx-1) |
---|
2729 | # plt.ylim(0,dy-1) |
---|
2730 | |
---|
2731 | # Extra values |
---|
2732 | if extravals is not None: |
---|
2733 | plt.pcolormesh(x, y, extravals, cmap=plt.get_cmap(extrapar[3]), \ |
---|
2734 | vmin=extrapar[1], vmax=extrapar[2]) |
---|
2735 | cbar = plt.colorbar() |
---|
2736 | cbar.set_label(extrapar[0].replace('_','\_') +'('+ units_lunits(extrapar[4])+\ |
---|
2737 | ')') |
---|
2738 | |
---|
2739 | if labels is not None: |
---|
2740 | for iv in range(len(xval)): |
---|
2741 | if np.mod(iv,7) == 0: N7pts = N7pts + 1 |
---|
2742 | # print iv,xval[iv],yval[iv],labels[iv],ptkinds[N7pts] |
---|
2743 | plt.plot(xval[iv],yval[iv], ptkinds[N7pts],label=labels[iv]) |
---|
2744 | |
---|
2745 | if figk[0:8] == 'labelled': |
---|
2746 | txtsize=int(figk.split(',')[1]) |
---|
2747 | txtcol=figk.split(',')[2] |
---|
2748 | for iv in range(len(xval)): |
---|
2749 | plt.annotate(labels[iv], xy=(xval[iv],yval[iv]), xycoords='data', \ |
---|
2750 | fontsize=txtsize, color=txtcol) |
---|
2751 | elif figk == 'legend': |
---|
2752 | plt.legend(loc=lloc) |
---|
2753 | |
---|
2754 | else: |
---|
2755 | plt.plot(xval, yval, '.', color=ptcol) |
---|
2756 | |
---|
2757 | graphtit = vtit.replace('_','\_').replace('&','\&') |
---|
2758 | |
---|
2759 | plt.title(graphtit.replace('|', ' ')) |
---|
2760 | |
---|
2761 | output_kind(kfig, figname, True) |
---|
2762 | |
---|
2763 | return |
---|
2764 | |
---|
2765 | def plot_2Dfield(varv,dimn,colorbar,vn,vx,unit,olon,olat,ifile,vtit,zvalue,time,tk, \ |
---|
2766 | tkt,tobj,tvals,tind,kfig,mapv,reva): |
---|
2767 | """ Adding labels and other staff to the graph |
---|
2768 | varv= 2D values to plot |
---|
2769 | dimn= dimension names to plot |
---|
2770 | colorbar= name of the color bar to use |
---|
2771 | vn,vm= minmum and maximum values to plot |
---|
2772 | unit= units of the variable |
---|
2773 | olon,olat= longitude, latitude objects |
---|
2774 | ifile= name of the input file |
---|
2775 | vtit= title of the variable |
---|
2776 | zvalue= value on the z axis |
---|
2777 | time= value on the time axis |
---|
2778 | tk= kind of time (WRF) |
---|
2779 | tkt= kind of time taken |
---|
2780 | tobj= tim object |
---|
2781 | tvals= values of the time variable |
---|
2782 | tind= time index |
---|
2783 | kfig= kind of figure (jpg, pdf, png) |
---|
2784 | mapv= map characteristics: [proj],[res] |
---|
2785 | see full documentation: http://matplotlib.org/basemap/ |
---|
2786 | [proj]: projection |
---|
2787 | * 'cyl', cilindric |
---|
2788 | [res]: resolution: |
---|
2789 | * 'c', crude |
---|
2790 | * 'l', low |
---|
2791 | * 'i', intermediate |
---|
2792 | * 'h', high |
---|
2793 | * 'f', full |
---|
2794 | reva= reverse the axes (x-->y, y-->x) |
---|
2795 | """ |
---|
2796 | ## import matplotlib as mpl |
---|
2797 | ## mpl.use('Agg') |
---|
2798 | ## import matplotlib.pyplot as plt |
---|
2799 | |
---|
2800 | if reva: |
---|
2801 | print ' reversing the axes of the figure (x-->y, y-->x)!!' |
---|
2802 | varv = np.transpose(varv) |
---|
2803 | dimn0 = [] |
---|
2804 | dimn0.append(dimn[1] + '') |
---|
2805 | dimn0.append(dimn[0] + '') |
---|
2806 | dimn = dimn0 |
---|
2807 | |
---|
2808 | fname = 'plot_2Dfield' |
---|
2809 | dx=varv.shape[1] |
---|
2810 | dy=varv.shape[0] |
---|
2811 | |
---|
2812 | plt.rc('text', usetex=True) |
---|
2813 | # plt.rc('font', family='serif') |
---|
2814 | |
---|
2815 | if not mapv is None: |
---|
2816 | if len(olon[:].shape) == 3: |
---|
2817 | lon0 = np.where(olon[0,] < 0., 360. + olon[0,], olon[0,]) |
---|
2818 | lat0 = olat[0,] |
---|
2819 | elif len(olon[:].shape) == 2: |
---|
2820 | lon0 = np.where(olon[:] < 0., 360. + olon[:], olon[:]) |
---|
2821 | lat0 = olat[:] |
---|
2822 | elif len(olon[:].shape) == 1: |
---|
2823 | lon00 = np.where(olon[:] < 0., 360. + olon[:], olon[:]) |
---|
2824 | lat00 = olat[:] |
---|
2825 | lon0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
2826 | lat0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
2827 | |
---|
2828 | for iy in range(len(lat00)): |
---|
2829 | lon0[iy,:] = lon00 |
---|
2830 | for ix in range(len(lon00)): |
---|
2831 | lat0[:,ix] = lat00 |
---|
2832 | |
---|
2833 | map_proj=mapv.split(',')[0] |
---|
2834 | map_res=mapv.split(',')[1] |
---|
2835 | |
---|
2836 | nlon = lon0[0,0] |
---|
2837 | xlon = lon0[dy-1,dx-1] |
---|
2838 | nlat = lat0[0,0] |
---|
2839 | xlat = lat0[dy-1,dx-1] |
---|
2840 | |
---|
2841 | lon2 = lon0[dy/2,dx/2] |
---|
2842 | lat2 = lat0[dy/2,dx/2] |
---|
2843 | |
---|
2844 | print ' lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
2845 | xlon, ',', xlat |
---|
2846 | |
---|
2847 | if map_proj == 'cyl': |
---|
2848 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
2849 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
2850 | elif map_proj == 'lcc': |
---|
2851 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
2852 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
2853 | |
---|
2854 | if len(olon[:].shape) == 1: |
---|
2855 | lons, lats = np.meshgrid(olon[:], olat[:]) |
---|
2856 | else: |
---|
2857 | lons = olon[0,:] |
---|
2858 | lats = olat[:,0] |
---|
2859 | |
---|
2860 | lons = np.where(lons < 0., lons + 360., lons) |
---|
2861 | |
---|
2862 | x,y = m(lons,lats) |
---|
2863 | plt.pcolormesh(x,y,varv, cmap=plt.get_cmap(colorbar), vmin=vn, vmax=vx) |
---|
2864 | cbar = plt.colorbar() |
---|
2865 | |
---|
2866 | m.drawcoastlines() |
---|
2867 | # if (nlon > 180. or xlon > 180.): |
---|
2868 | # nlon0 = nlon |
---|
2869 | # xlon0 = xlon |
---|
2870 | # if (nlon > 180.): nlon0 = nlon - 360. |
---|
2871 | # if (xlon > 180.): xlon0 = xlon - 360. |
---|
2872 | # meridians = pretty_int(nlon0,xlon0,5) |
---|
2873 | # meridians = np.where(meridians < 0., meridians + 360., meridians) |
---|
2874 | # else: |
---|
2875 | # meridians = pretty_int(nlon,xlon,5) |
---|
2876 | |
---|
2877 | meridians = pretty_int(nlon,xlon,5) |
---|
2878 | |
---|
2879 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
2880 | parallels = pretty_int(nlat,xlat,5) |
---|
2881 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
2882 | |
---|
2883 | else: |
---|
2884 | plt.xlim(0,dx-1) |
---|
2885 | plt.ylim(0,dy-1) |
---|
2886 | |
---|
2887 | plt.pcolormesh(varv, cmap=plt.get_cmap(colorbar), vmin=vn, vmax=vx) |
---|
2888 | cbar = plt.colorbar() |
---|
2889 | |
---|
2890 | plt.xlabel(dimn[1].replace('_','\_')) |
---|
2891 | plt.ylabel(dimn[0].replace('_','\_')) |
---|
2892 | |
---|
2893 | # set the limits of the plot to the limits of the data |
---|
2894 | # plt.axis([x.min(), x.max(), y.min(), y.max()]) |
---|
2895 | |
---|
2896 | # plt.plot(varv) |
---|
2897 | cbar.set_label(unit) |
---|
2898 | |
---|
2899 | figname = ifile.replace('.','_') + '_' + vtit |
---|
2900 | graphtit = vtit.replace('_','\_').replace('&','\&') |
---|
2901 | |
---|
2902 | if zvalue != 'null': |
---|
2903 | graphtit = graphtit + ' at z= ' + zvalue |
---|
2904 | figname = figname + '_z' + zvalue |
---|
2905 | if tkt == 'tstep': |
---|
2906 | graphtit = graphtit + ' at time-step= ' + time.split(',')[1] |
---|
2907 | figname = figname + '_t' + time.split(',')[1].zfill(4) |
---|
2908 | elif tkt == 'CFdate': |
---|
2909 | graphtit = graphtit + ' at ' + tobj.strfmt("%Y%m%d%H%M%S") |
---|
2910 | figname = figname + '_t' + tobj.strfmt("%Y%m%d%H%M%S") |
---|
2911 | |
---|
2912 | if tk == 'WRF': |
---|
2913 | # datev = str(timevals[timeind][0:9]) |
---|
2914 | datev = tvals[tind][0] + tvals[tind][1] + tvals[tind][2] + \ |
---|
2915 | timevals[timeind][3] + timevals[timeind][4] + timevals[timeind][5] + \ |
---|
2916 | timevals[timeind][6] + timevals[timeind][7] + timevals[timeind][8] + \ |
---|
2917 | timevals[timeind][9] |
---|
2918 | # timev = str(timevals[timeind][11:18]) |
---|
2919 | timev = timevals[timeind][11] + timevals[timeind][12] + \ |
---|
2920 | timevals[timeind][13] + timevals[timeind][14] + timevals[timeind][15] + \ |
---|
2921 | timevals[timeind][16] + timevals[timeind][17] + timevals[timeind][18] |
---|
2922 | graphtit = vtit.replace('_','\_') + ' (' + datev + ' ' + timev + ')' |
---|
2923 | |
---|
2924 | plt.title(graphtit) |
---|
2925 | |
---|
2926 | output_kind(kfig, figname, True) |
---|
2927 | |
---|
2928 | return |
---|
2929 | |
---|
2930 | def plot_2Dfield_easy(varv,dimxv,dimyv,dimn,colorbar,vn,vx,unit,ifile,vtit,kfig,reva): |
---|
2931 | """ Adding labels and other staff to the graph |
---|
2932 | varv= 2D values to plot |
---|
2933 | dim[x/y]v = values at the axes of x and y |
---|
2934 | dimn= dimension names to plot |
---|
2935 | colorbar= name of the color bar to use |
---|
2936 | vn,vm= minmum and maximum values to plot |
---|
2937 | unit= units of the variable |
---|
2938 | ifile= name of the input file |
---|
2939 | vtit= title of the variable |
---|
2940 | kfig= kind of figure (jpg, pdf, png) |
---|
2941 | reva= reverse the axes (x-->y, y-->x) |
---|
2942 | """ |
---|
2943 | ## import matplotlib as mpl |
---|
2944 | ## mpl.use('Agg') |
---|
2945 | ## import matplotlib.pyplot as plt |
---|
2946 | fname = 'plot_2Dfield' |
---|
2947 | |
---|
2948 | if reva: |
---|
2949 | print ' reversing the axes of the figure (x-->y, y-->x)!!' |
---|
2950 | varv = np.transpose(varv) |
---|
2951 | dimn0 = [] |
---|
2952 | dimn0.append(dimn[1] + '') |
---|
2953 | dimn0.append(dimn[0] + '') |
---|
2954 | dimn = dimn0 |
---|
2955 | if len(dimyv.shape) == 2: |
---|
2956 | x = np.transpose(dimyv) |
---|
2957 | else: |
---|
2958 | if len(dimxv.shape) == 2: |
---|
2959 | ddx = len(dimyv) |
---|
2960 | ddy = dimxv.shape[1] |
---|
2961 | else: |
---|
2962 | ddx = len(dimyv) |
---|
2963 | ddy = len(dimxv) |
---|
2964 | |
---|
2965 | x = np.zeros((ddy,ddx), dtype=np.float) |
---|
2966 | for j in range(ddy): |
---|
2967 | x[j,:] = dimyv |
---|
2968 | |
---|
2969 | if len(dimxv.shape) == 2: |
---|
2970 | y = np.transpose(dimxv) |
---|
2971 | else: |
---|
2972 | if len(dimyv.shape) == 2: |
---|
2973 | ddx = dimyv.shape[0] |
---|
2974 | ddy = len(dimxv) |
---|
2975 | else: |
---|
2976 | ddx = len(dimyv) |
---|
2977 | ddy = len(dimxv) |
---|
2978 | |
---|
2979 | y = np.zeros((ddy,ddx), dtype=np.float) |
---|
2980 | for i in range(ddx): |
---|
2981 | y[:,i] = dimxv |
---|
2982 | else: |
---|
2983 | if len(dimxv.shape) == 2: |
---|
2984 | x = dimxv |
---|
2985 | else: |
---|
2986 | x = np.zeros((len(dimyv),len(dimxv)), dtype=np.float) |
---|
2987 | for j in range(len(dimyv)): |
---|
2988 | x[j,:] = dimxv |
---|
2989 | |
---|
2990 | if len(dimyv.shape) == 2: |
---|
2991 | y = dimyv |
---|
2992 | else: |
---|
2993 | y = np.zeros((len(dimyv),len(dimxv)), dtype=np.float) |
---|
2994 | for i in range(len(dimxv)): |
---|
2995 | x[:,i] = dimyv |
---|
2996 | |
---|
2997 | dx=varv.shape[1] |
---|
2998 | dy=varv.shape[0] |
---|
2999 | |
---|
3000 | plt.rc('text', usetex=True) |
---|
3001 | plt.xlim(0,dx-1) |
---|
3002 | plt.ylim(0,dy-1) |
---|
3003 | |
---|
3004 | plt.pcolormesh(x, y, varv, cmap=plt.get_cmap(colorbar), vmin=vn, vmax=vx) |
---|
3005 | # plt.pcolormesh(varv, cmap=plt.get_cmap(colorbar), vmin=vn, vmax=vx) |
---|
3006 | cbar = plt.colorbar() |
---|
3007 | |
---|
3008 | plt.xlabel(dimn[1].replace('_','\_')) |
---|
3009 | plt.ylabel(dimn[0].replace('_','\_')) |
---|
3010 | |
---|
3011 | # set the limits of the plot to the limits of the data |
---|
3012 | plt.axis([x.min(), x.max(), y.min(), y.max()]) |
---|
3013 | # if varv.shape[1] / varv.shape[0] > 10: |
---|
3014 | # plt.axes().set_aspect(0.001) |
---|
3015 | # else: |
---|
3016 | # plt.axes().set_aspect(np.float(varv.shape[0])/np.float(varv.shape[1])) |
---|
3017 | |
---|
3018 | cbar.set_label(unit) |
---|
3019 | |
---|
3020 | figname = ifile.replace('.','_') + '_' + vtit |
---|
3021 | graphtit = vtit.replace('_','\_').replace('&','\&') |
---|
3022 | |
---|
3023 | plt.title(graphtit) |
---|
3024 | |
---|
3025 | output_kind(kfig, figname, True) |
---|
3026 | |
---|
3027 | return |
---|
3028 | |
---|
3029 | def plot_Trajectories(lonval, latval, linesn, olon, olat, lonlatLims, gtit, kfig, \ |
---|
3030 | mapv, obsname): |
---|
3031 | """ plotting points |
---|
3032 | [lon/latval]= lon,lat values to plot (as list of vectors) |
---|
3033 | linesn: name of the lines |
---|
3034 | o[lon/lat]= object with the longitudes and the latitudes of the map to plot |
---|
3035 | lonlatLims: limits of longitudes and latitudes [lonmin, latmin, lonmax, latmax] |
---|
3036 | gtit= title of the graph |
---|
3037 | kfig= kind of figure (jpg, pdf, png) |
---|
3038 | mapv= map characteristics: [proj],[res] |
---|
3039 | see full documentation: http://matplotlib.org/basemap/ |
---|
3040 | [proj]: projection |
---|
3041 | * 'cyl', cilindric |
---|
3042 | * 'lcc', lambert conformal |
---|
3043 | [res]: resolution: |
---|
3044 | * 'c', crude |
---|
3045 | * 'l', low |
---|
3046 | * 'i', intermediate |
---|
3047 | * 'h', high |
---|
3048 | * 'f', full |
---|
3049 | obsname= name of the observations in graph (can be None for without). |
---|
3050 | Observational trajectory would be the last one |
---|
3051 | """ |
---|
3052 | fname = 'plot_Trajectories' |
---|
3053 | |
---|
3054 | if lonval == 'h': |
---|
3055 | print fname + '_____________________________________________________________' |
---|
3056 | print plot_Trajectories.__doc__ |
---|
3057 | quit() |
---|
3058 | |
---|
3059 | # Canging line kinds every 7 lines (end of standard colors) |
---|
3060 | linekinds=['.-','x-','o-'] |
---|
3061 | |
---|
3062 | Ntraj = len(lonval) |
---|
3063 | |
---|
3064 | if obsname is not None: |
---|
3065 | Ntraj = Ntraj - 1 |
---|
3066 | |
---|
3067 | N7lines = 0 |
---|
3068 | |
---|
3069 | plt.rc('text', usetex=True) |
---|
3070 | |
---|
3071 | if not mapv is None: |
---|
3072 | if len(olon[:].shape) == 3: |
---|
3073 | # lon0 = np.where(olon[0,] < 0., 360. + olon[0,], olon[0,]) |
---|
3074 | lon0 = olon[0,] |
---|
3075 | lat0 = olat[0,] |
---|
3076 | elif len(olon[:].shape) == 2: |
---|
3077 | # lon0 = np.where(olon[:] < 0., 360. + olon[:], olon[:]) |
---|
3078 | lon0 = olon[:] |
---|
3079 | lat0 = olat[:] |
---|
3080 | elif len(olon[:].shape) == 1: |
---|
3081 | # lon00 = np.where(olon[:] < 0., 360. + olon[:], olon[:]) |
---|
3082 | lon00 = olon[:] |
---|
3083 | lat00 = olat[:] |
---|
3084 | lon0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
3085 | lat0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
3086 | |
---|
3087 | for iy in range(len(lat00)): |
---|
3088 | lon0[iy,:] = lon00 |
---|
3089 | for ix in range(len(lon00)): |
---|
3090 | lat0[:,ix] = lat00 |
---|
3091 | |
---|
3092 | map_proj=mapv.split(',')[0] |
---|
3093 | map_res=mapv.split(',')[1] |
---|
3094 | |
---|
3095 | dx = lon0.shape[1] |
---|
3096 | dy = lon0.shape[0] |
---|
3097 | |
---|
3098 | nlon = lon0[0,0] |
---|
3099 | xlon = lon0[dy-1,dx-1] |
---|
3100 | nlat = lat0[0,0] |
---|
3101 | xlat = lat0[dy-1,dx-1] |
---|
3102 | |
---|
3103 | lon2 = lon0[dy/2,dx/2] |
---|
3104 | lat2 = lat0[dy/2,dx/2] |
---|
3105 | |
---|
3106 | if lonlatLims is not None: |
---|
3107 | plt.xlim(lonlatLims[0], lonlatLims[2]) |
---|
3108 | plt.ylim(lonlatLims[1], lonlatLims[3]) |
---|
3109 | if map_proj == 'cyl': |
---|
3110 | nlon = lonlatLims[0] |
---|
3111 | nlat = lonlatLims[1] |
---|
3112 | xlon = lonlatLims[2] |
---|
3113 | xlat = lonlatLims[3] |
---|
3114 | |
---|
3115 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
3116 | xlon, ',', xlat |
---|
3117 | |
---|
3118 | if map_proj == 'cyl': |
---|
3119 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
3120 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
3121 | elif map_proj == 'lcc': |
---|
3122 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
3123 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
3124 | |
---|
3125 | if len(olon.shape) == 3: |
---|
3126 | # lons, lats = np.meshgrid(olon[0,:,:], olat[0,:,:]) |
---|
3127 | lons = olon[0,:,:] |
---|
3128 | lats = olat[0,:,:] |
---|
3129 | |
---|
3130 | elif len(olon.shape) == 2: |
---|
3131 | # lons, lats = np.meshgrid(olon[:,:], olat[:,:]) |
---|
3132 | lons = olon[:,:] |
---|
3133 | lats = olat[:,:] |
---|
3134 | else: |
---|
3135 | dx = olon.shape |
---|
3136 | dy = olat.shape |
---|
3137 | # print errormsg |
---|
3138 | # print ' ' + fname + ': shapes of lon/lat objects', olon.shape, \ |
---|
3139 | # 'not ready!!!' |
---|
3140 | |
---|
3141 | for il in range(Ntraj): |
---|
3142 | plt.plot(lonval[il], latval[il], linekinds[N7lines], label= linesn[il]) |
---|
3143 | if il == 6: N7lines = N7lines + 1 |
---|
3144 | |
---|
3145 | m.drawcoastlines() |
---|
3146 | |
---|
3147 | meridians = pretty_int(nlon,xlon,5) |
---|
3148 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
3149 | |
---|
3150 | parallels = pretty_int(nlat,xlat,5) |
---|
3151 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
3152 | |
---|
3153 | plt.xlabel('W-E') |
---|
3154 | plt.ylabel('S-N') |
---|
3155 | |
---|
3156 | else: |
---|
3157 | if len(olon.shape) == 3: |
---|
3158 | dx = olon.shape[2] |
---|
3159 | dy = olon.shape[1] |
---|
3160 | elif len(olon.shape) == 2: |
---|
3161 | dx = olon.shape[1] |
---|
3162 | dy = olon.shape[0] |
---|
3163 | else: |
---|
3164 | dx = olon.shape |
---|
3165 | dy = olat.shape |
---|
3166 | # print errormsg |
---|
3167 | # print ' ' + fname + ': shapes of lon/lat objects', olon.shape, \ |
---|
3168 | # 'not ready!!!' |
---|
3169 | |
---|
3170 | if lonlatLims is not None: |
---|
3171 | plt.xlim(lonlatLims[0], lonlatLims[2]) |
---|
3172 | plt.ylim(lonlatLims[1], lonlatLims[3]) |
---|
3173 | else: |
---|
3174 | plt.xlim(np.min(olon[:]),np.max(olon[:])) |
---|
3175 | plt.ylim(np.min(olat[:]),np.max(olat[:])) |
---|
3176 | |
---|
3177 | for il in range(Ntraj): |
---|
3178 | plt.plot(lonval[il], latval[il], linekinds[N7lines], label= linesn[il]) |
---|
3179 | if il == 6: N7lines = N7lines + 1 |
---|
3180 | |
---|
3181 | plt.xlabel('x-axis') |
---|
3182 | plt.ylabel('y-axis') |
---|
3183 | |
---|
3184 | figname = 'trajectories' |
---|
3185 | graphtit = gtit |
---|
3186 | |
---|
3187 | if obsname is not None: |
---|
3188 | plt.plot(lonval[Ntraj], latval[Ntraj], linestyle='-', color='k', \ |
---|
3189 | linewidth=3, label= obsname) |
---|
3190 | |
---|
3191 | plt.title(graphtit.replace('_','\_').replace('&','\&')) |
---|
3192 | plt.legend() |
---|
3193 | |
---|
3194 | output_kind(kfig, figname, True) |
---|
3195 | |
---|
3196 | return |
---|
3197 | |
---|
3198 | def plot_topo_geogrid(varv, olon, olat, mint, maxt, lonlatLims, gtit, kfig, mapv, \ |
---|
3199 | closeif): |
---|
3200 | """ plotting geo_em.d[nn].nc topography from WPS files |
---|
3201 | plot_topo_geogrid(domf, mint, maxt, gtit, kfig, mapv) |
---|
3202 | varv= topography values |
---|
3203 | o[lon/lat]= longitude and latitude objects |
---|
3204 | [min/max]t: minimum and maximum values of topography to draw |
---|
3205 | lonlatLims: limits of longitudes and latitudes [lonmin, latmin, lonmax, latmax] |
---|
3206 | gtit= title of the graph |
---|
3207 | kfig= kind of figure (jpg, pdf, png) |
---|
3208 | mapv= map characteristics: [proj],[res] |
---|
3209 | see full documentation: http://matplotlib.org/basemap/ |
---|
3210 | [proj]: projection |
---|
3211 | * 'cyl', cilindric |
---|
3212 | * 'lcc', lamvbert conformal |
---|
3213 | [res]: resolution: |
---|
3214 | * 'c', crude |
---|
3215 | * 'l', low |
---|
3216 | * 'i', intermediate |
---|
3217 | * 'h', high |
---|
3218 | * 'f', full |
---|
3219 | closeif= Boolean value if the figure has to be closed |
---|
3220 | """ |
---|
3221 | fname = 'plot_topo_geogrid' |
---|
3222 | |
---|
3223 | if varv == 'h': |
---|
3224 | print fname + '_____________________________________________________________' |
---|
3225 | print plot_topo_geogrid.__doc__ |
---|
3226 | quit() |
---|
3227 | |
---|
3228 | dx=varv.shape[1] |
---|
3229 | dy=varv.shape[0] |
---|
3230 | |
---|
3231 | plt.rc('text', usetex=True) |
---|
3232 | # plt.rc('font', family='serif') |
---|
3233 | |
---|
3234 | if not mapv is None: |
---|
3235 | if len(olon[:].shape) == 3: |
---|
3236 | lon0 = olon[0,] |
---|
3237 | lat0 = olat[0,] |
---|
3238 | elif len(olon[:].shape) == 2: |
---|
3239 | lon0 = olon[:] |
---|
3240 | lat0 = olat[:] |
---|
3241 | elif len(olon[:].shape) == 1: |
---|
3242 | lon00 = olon[:] |
---|
3243 | lat00 = olat[:] |
---|
3244 | lon0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
3245 | lat0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
3246 | |
---|
3247 | for iy in range(len(lat00)): |
---|
3248 | lon0[iy,:] = lon00 |
---|
3249 | for ix in range(len(lon00)): |
---|
3250 | lat0[:,ix] = lat00 |
---|
3251 | |
---|
3252 | map_proj=mapv.split(',')[0] |
---|
3253 | map_res=mapv.split(',')[1] |
---|
3254 | dx = lon0.shape[1] |
---|
3255 | dy = lon0.shape[0] |
---|
3256 | |
---|
3257 | if lonlatLims is not None: |
---|
3258 | print ' ' + fname + ': cutting the domain to plot !!!!' |
---|
3259 | print ' limits: W-E', lonlatLims[0], lonlatLims[2] |
---|
3260 | print ' limits: N-S', lonlatLims[1], lonlatLims[3] |
---|
3261 | nlon = lonlatLims[0] |
---|
3262 | xlon = lonlatLims[2] |
---|
3263 | nlat = lonlatLims[1] |
---|
3264 | xlat = lonlatLims[3] |
---|
3265 | |
---|
3266 | if map_proj == 'lcc': |
---|
3267 | lon2 = (lonlatLims[0] + lonlatLims[2])/2. |
---|
3268 | lat2 = (lonlatLims[1] + lonlatLims[3])/2. |
---|
3269 | else: |
---|
3270 | nlon = lon0[0,0] |
---|
3271 | xlon = lon0[dy-1,dx-1] |
---|
3272 | nlat = lat0[0,0] |
---|
3273 | xlat = lat0[dy-1,dx-1] |
---|
3274 | lon2 = lon0[dy/2,dx/2] |
---|
3275 | lat2 = lat0[dy/2,dx/2] |
---|
3276 | |
---|
3277 | plt.xlim(nlon, xlon) |
---|
3278 | plt.ylim(nlat, xlat) |
---|
3279 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
3280 | xlon, ',', xlat |
---|
3281 | |
---|
3282 | if map_proj == 'cyl': |
---|
3283 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
3284 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
3285 | elif map_proj == 'lcc': |
---|
3286 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
3287 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
3288 | else: |
---|
3289 | print errormsg |
---|
3290 | print ' ' + fname + ": map projection '" + map_proj + "' not ready !!" |
---|
3291 | quit(-1) |
---|
3292 | |
---|
3293 | if len(olon[:].shape) == 1: |
---|
3294 | lons, lats = np.meshgrid(olon[:], olat[:]) |
---|
3295 | else: |
---|
3296 | if len(olon[:].shape) == 3: |
---|
3297 | lons = olon[0,:,:] |
---|
3298 | lats = olat[0,:,:] |
---|
3299 | else: |
---|
3300 | lons = olon[:] |
---|
3301 | lats = olat[:] |
---|
3302 | |
---|
3303 | x,y = m(lons,lats) |
---|
3304 | |
---|
3305 | plt.pcolormesh(x,y,varv, cmap=plt.get_cmap('terrain'), vmin=mint, vmax=maxt) |
---|
3306 | cbar = plt.colorbar() |
---|
3307 | |
---|
3308 | m.drawcoastlines() |
---|
3309 | |
---|
3310 | meridians = pretty_int(nlon,xlon,5) |
---|
3311 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
3312 | |
---|
3313 | parallels = pretty_int(nlat,xlat,5) |
---|
3314 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
3315 | |
---|
3316 | plt.xlabel('W-E') |
---|
3317 | plt.ylabel('S-N') |
---|
3318 | else: |
---|
3319 | print emsg |
---|
3320 | print ' ' + fname + ': A projection parameter is needed None given !!' |
---|
3321 | quit(-1) |
---|
3322 | |
---|
3323 | figname = 'domain' |
---|
3324 | graphtit = gtit.replace('_','\_') |
---|
3325 | cbar.set_label('height ($m$)') |
---|
3326 | |
---|
3327 | plt.title(graphtit.replace('_','\_').replace('&','\&')) |
---|
3328 | |
---|
3329 | output_kind(kfig, figname, closeif) |
---|
3330 | |
---|
3331 | return |
---|
3332 | |
---|
3333 | def plot_topo_geogrid_boxes(varv, boxesX, boxesY, boxlabels, olon, olat, mint, maxt, \ |
---|
3334 | lonlatLims, gtit, kfig, mapv, gloc, closeif): |
---|
3335 | """ plotting geo_em.d[nn].nc topography from WPS files |
---|
3336 | plot_topo_geogrid(domf, mint, maxt, gtit, kfig, mapv) |
---|
3337 | varv= topography values |
---|
3338 | boxesX/Y= 4-line sets to draw the boxes |
---|
3339 | boxlabels= labels for the legend of the boxes |
---|
3340 | o[lon/lat]= longitude and latitude objects |
---|
3341 | [min/max]t: minimum and maximum values of topography to draw |
---|
3342 | lonlatLims: limits of longitudes and latitudes [lonmin, latmin, lonmax, latmax] |
---|
3343 | gtit= title of the graph |
---|
3344 | kfig= kind of figure (jpg, pdf, png) |
---|
3345 | mapv= map characteristics: [proj],[res] |
---|
3346 | see full documentation: http://matplotlib.org/basemap/ |
---|
3347 | [proj]: projection |
---|
3348 | * 'cyl', cilindric |
---|
3349 | * 'lcc', lamvbert conformal |
---|
3350 | [res]: resolution: |
---|
3351 | * 'c', crude |
---|
3352 | * 'l', low |
---|
3353 | * 'i', intermediate |
---|
3354 | * 'h', high |
---|
3355 | * 'f', full |
---|
3356 | gloc= location of the legend (0, autmoatic) |
---|
3357 | 1: 'upper right', 2: 'upper left', 3: 'lower left', 4: 'lower right', |
---|
3358 | 5: 'right', 6: 'center left', 7: 'center right', 8: 'lower center', |
---|
3359 | 9: 'upper center', 10: 'center' |
---|
3360 | closeif= Boolean value if the figure has to be closed |
---|
3361 | """ |
---|
3362 | fname = 'plot_topo_geogrid' |
---|
3363 | |
---|
3364 | if varv == 'h': |
---|
3365 | print fname + '_____________________________________________________________' |
---|
3366 | print plot_topo_geogrid.__doc__ |
---|
3367 | quit() |
---|
3368 | |
---|
3369 | cols = color_lines(len(boxlabels)) |
---|
3370 | |
---|
3371 | dx=varv.shape[1] |
---|
3372 | dy=varv.shape[0] |
---|
3373 | |
---|
3374 | plt.rc('text', usetex=True) |
---|
3375 | # plt.rc('font', family='serif') |
---|
3376 | |
---|
3377 | if not mapv is None: |
---|
3378 | if len(olon[:].shape) == 3: |
---|
3379 | lon0 = olon[0,] |
---|
3380 | lat0 = olat[0,] |
---|
3381 | elif len(olon[:].shape) == 2: |
---|
3382 | lon0 = olon[:] |
---|
3383 | lat0 = olat[:] |
---|
3384 | elif len(olon[:].shape) == 1: |
---|
3385 | lon00 = olon[:] |
---|
3386 | lat00 = olat[:] |
---|
3387 | lon0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
3388 | lat0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
3389 | |
---|
3390 | for iy in range(len(lat00)): |
---|
3391 | lon0[iy,:] = lon00 |
---|
3392 | for ix in range(len(lon00)): |
---|
3393 | lat0[:,ix] = lat00 |
---|
3394 | |
---|
3395 | map_proj=mapv.split(',')[0] |
---|
3396 | map_res=mapv.split(',')[1] |
---|
3397 | dx = lon0.shape[1] |
---|
3398 | dy = lon0.shape[0] |
---|
3399 | |
---|
3400 | if lonlatLims is not None: |
---|
3401 | print ' ' + fname + ': cutting the domain to plot !!!!' |
---|
3402 | print ' limits: W-E', lonlatLims[0], lonlatLims[2] |
---|
3403 | print ' limits: N-S', lonlatLims[1], lonlatLims[3] |
---|
3404 | nlon = lonlatLims[0] |
---|
3405 | xlon = lonlatLims[2] |
---|
3406 | nlat = lonlatLims[1] |
---|
3407 | xlat = lonlatLims[3] |
---|
3408 | |
---|
3409 | if map_proj == 'lcc': |
---|
3410 | lon2 = (lonlatLims[0] + lonlatLims[2])/2. |
---|
3411 | lat2 = (lonlatLims[1] + lonlatLims[3])/2. |
---|
3412 | else: |
---|
3413 | nlon = np.min(lon0) |
---|
3414 | xlon = np.max(lon0) |
---|
3415 | nlat = np.min(lat0) |
---|
3416 | xlat = np.max(lat0) |
---|
3417 | lon2 = lon0[dy/2,dx/2] |
---|
3418 | lat2 = lat0[dy/2,dx/2] |
---|
3419 | |
---|
3420 | plt.xlim(nlon, xlon) |
---|
3421 | plt.ylim(nlat, xlat) |
---|
3422 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
3423 | xlon, ',', xlat |
---|
3424 | |
---|
3425 | if map_proj == 'cyl': |
---|
3426 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
3427 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
3428 | elif map_proj == 'lcc': |
---|
3429 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
3430 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
3431 | else: |
---|
3432 | print errormsg |
---|
3433 | print ' ' + fname + ": projection '" + map_proj + "' does not exist!!" |
---|
3434 | print ' existing ones: cyl, lcc' |
---|
3435 | quit(-1) |
---|
3436 | |
---|
3437 | if len(olon[:].shape) == 1: |
---|
3438 | lons, lats = np.meshgrid(olon[:], olat[:]) |
---|
3439 | else: |
---|
3440 | if len(olon[:].shape) == 3: |
---|
3441 | lons = olon[0,:,:] |
---|
3442 | lats = olat[0,:,:] |
---|
3443 | else: |
---|
3444 | lons = olon[:] |
---|
3445 | lats = olat[:] |
---|
3446 | |
---|
3447 | x,y = m(lons,lats) |
---|
3448 | |
---|
3449 | plt.pcolormesh(x,y,varv, cmap=plt.get_cmap('terrain'), vmin=mint, vmax=maxt) |
---|
3450 | cbar = plt.colorbar() |
---|
3451 | |
---|
3452 | Nboxes = len(boxesX)/4 |
---|
3453 | for ibox in range(Nboxes): |
---|
3454 | plt.plot(boxesX[ibox*4], boxesY[ibox*4], linestyle='-', linewidth=3, \ |
---|
3455 | label=boxlabels[ibox], color=cols[ibox]) |
---|
3456 | plt.plot(boxesX[ibox*4+1], boxesY[ibox*4+1], linestyle='-', linewidth=3, \ |
---|
3457 | color=cols[ibox]) |
---|
3458 | plt.plot(boxesX[ibox*4+2], boxesY[ibox*4+2], linestyle='-', linewidth=3, \ |
---|
3459 | color=cols[ibox]) |
---|
3460 | plt.plot(boxesX[ibox*4+3], boxesY[ibox*4+3], linestyle='-', linewidth=3, \ |
---|
3461 | color=cols[ibox]) |
---|
3462 | |
---|
3463 | m.drawcoastlines() |
---|
3464 | |
---|
3465 | meridians = pretty_int(nlon,xlon,5) |
---|
3466 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
3467 | |
---|
3468 | parallels = pretty_int(nlat,xlat,5) |
---|
3469 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
3470 | |
---|
3471 | plt.xlabel('W-E') |
---|
3472 | plt.ylabel('S-N') |
---|
3473 | else: |
---|
3474 | print emsg |
---|
3475 | print ' ' + fname + ': A projection parameter is needed None given !!' |
---|
3476 | quit(-1) |
---|
3477 | |
---|
3478 | figname = 'domain_boxes' |
---|
3479 | graphtit = gtit.replace('_','\_').replace('&','\&') |
---|
3480 | cbar.set_label('height ($m$)') |
---|
3481 | |
---|
3482 | plt.title(graphtit) |
---|
3483 | plt.legend(loc=gloc) |
---|
3484 | |
---|
3485 | output_kind(kfig, figname, closeif) |
---|
3486 | |
---|
3487 | return |
---|
3488 | |
---|
3489 | def plot_2D_shadow(varsv,vnames,dimxv,dimyv,dimxu,dimyu,dimn, \ |
---|
3490 | colorbar,vs,uts,vtit,kfig,reva,mapv,ifclose): |
---|
3491 | """ Adding labels and other staff to the graph |
---|
3492 | varsv= 2D values to plot with shading |
---|
3493 | vnames= variable names for the figure |
---|
3494 | dim[x/y]v = values at the axes of x and y |
---|
3495 | dim[x/y]u = units at the axes of x and y |
---|
3496 | dimn= dimension names to plot |
---|
3497 | colorbar= name of the color bar to use |
---|
3498 | vs= minmum and maximum values to plot in shadow or: |
---|
3499 | 'Srange': for full range |
---|
3500 | 'Saroundmean@val': for mean-xtrm,mean+xtrm where xtrm = np.min(mean-min@val,max@val-mean) |
---|
3501 | 'Saroundminmax@val': for min*val,max*val |
---|
3502 | 'Saroundpercentile@val': for median-xtrm,median+xtrm where xtrm = np.min(median-percentile_(val), |
---|
3503 | percentile_(100-val)-median) |
---|
3504 | 'Smean@val': for -xtrm,xtrm where xtrm = np.min(mean-min*@val,max*@val-mean) |
---|
3505 | 'Smedian@val': for -xtrm,xtrm where xtrm = np.min(median-min@val,max@val-median) |
---|
3506 | 'Spercentile@val': for -xtrm,xtrm where xtrm = np.min(median-percentile_(val), |
---|
3507 | percentile_(100-val)-median) |
---|
3508 | uts= units of the variable to shadow |
---|
3509 | vtit= title of the variable |
---|
3510 | kfig= kind of figure (jpg, pdf, png) |
---|
3511 | reva= ('|' for combination) |
---|
3512 | * 'transpose': reverse the axes (x-->y, y-->x) |
---|
3513 | * 'flip'@[x/y]: flip the axis x or y |
---|
3514 | mapv= map characteristics: [proj],[res] |
---|
3515 | see full documentation: http://matplotlib.org/basemap/ |
---|
3516 | [proj]: projection |
---|
3517 | * 'cyl', cilindric |
---|
3518 | * 'lcc', lambert conformal |
---|
3519 | [res]: resolution: |
---|
3520 | * 'c', crude |
---|
3521 | * 'l', low |
---|
3522 | * 'i', intermediate |
---|
3523 | * 'h', high |
---|
3524 | * 'f', full |
---|
3525 | ifclose= boolean value whether figure should be close (finish) or not |
---|
3526 | """ |
---|
3527 | ## import matplotlib as mpl |
---|
3528 | ## mpl.use('Agg') |
---|
3529 | ## import matplotlib.pyplot as plt |
---|
3530 | fname = 'plot_2D_shadow' |
---|
3531 | |
---|
3532 | # print dimyv[73,21] |
---|
3533 | # dimyv[73,21] = -dimyv[73,21] |
---|
3534 | # print 'Lluis dimsv: ',np.min(dimxv), np.max(dimxv), ':', np.min(dimyv), np.max(dimyv) |
---|
3535 | |
---|
3536 | if varsv == 'h': |
---|
3537 | print fname + '_____________________________________________________________' |
---|
3538 | print plot_2D_shadow.__doc__ |
---|
3539 | quit() |
---|
3540 | |
---|
3541 | if len(varsv.shape) != 2: |
---|
3542 | print errormsg |
---|
3543 | print ' ' + fname + ': wrong variable shape:',varsv.shape,'is has to be 2D!!' |
---|
3544 | quit(-1) |
---|
3545 | |
---|
3546 | reva0 = '' |
---|
3547 | if reva.find('|') != 0: |
---|
3548 | revas = reva.split('|') |
---|
3549 | else: |
---|
3550 | revas = [reva] |
---|
3551 | reva0 = reva |
---|
3552 | |
---|
3553 | for rev in revas: |
---|
3554 | if reva[0:4] == 'flip': |
---|
3555 | reva0 = 'flip' |
---|
3556 | if len(reva.split('@')) != 2: |
---|
3557 | print errormsg |
---|
3558 | print ' ' + fname + ': flip is given', reva, 'but not axis!' |
---|
3559 | quit(-1) |
---|
3560 | |
---|
3561 | if rev == 'transpose': |
---|
3562 | print ' reversing the axes of the figure (x-->y, y-->x)!!' |
---|
3563 | varsv = np.transpose(varsv) |
---|
3564 | dxv = dimyv |
---|
3565 | dyv = dimxv |
---|
3566 | dimxv = dxv |
---|
3567 | dimyv = dyv |
---|
3568 | |
---|
3569 | if len(dimxv[:].shape) == 3: |
---|
3570 | xdims = '1,2' |
---|
3571 | elif len(dimxv[:].shape) == 2: |
---|
3572 | xdims = '0,1' |
---|
3573 | elif len(dimxv[:].shape) == 1: |
---|
3574 | xdims = '0' |
---|
3575 | |
---|
3576 | if len(dimyv[:].shape) == 3: |
---|
3577 | ydims = '1,2' |
---|
3578 | elif len(dimyv[:].shape) == 2: |
---|
3579 | ydims = '0,1' |
---|
3580 | elif len(dimyv[:].shape) == 1: |
---|
3581 | ydims = '0' |
---|
3582 | |
---|
3583 | # lon0 = dimxv |
---|
3584 | # lat0 = dimyv |
---|
3585 | lon0, lat0 = dxdy_lonlat(dimxv,dimyv, xdims, ydims) |
---|
3586 | |
---|
3587 | if not mapv is None: |
---|
3588 | map_proj=mapv.split(',')[0] |
---|
3589 | map_res=mapv.split(',')[1] |
---|
3590 | |
---|
3591 | dx = lon0.shape[1] |
---|
3592 | dy = lat0.shape[0] |
---|
3593 | |
---|
3594 | nlon = lon0[0,0] |
---|
3595 | xlon = lon0[dy-1,dx-1] |
---|
3596 | nlat = lat0[0,0] |
---|
3597 | xlat = lat0[dy-1,dx-1] |
---|
3598 | |
---|
3599 | # Thats too much! :) |
---|
3600 | # if lonlatLims is not None: |
---|
3601 | # print ' ' + fname + ': cutting the domain to plot !!!!' |
---|
3602 | # plt.xlim(lonlatLims[0], lonlatLims[2]) |
---|
3603 | # plt.ylim(lonlatLims[1], lonlatLims[3]) |
---|
3604 | # print ' limits: W-E', lonlatLims[0], lonlatLims[2] |
---|
3605 | # print ' limits: N-S', lonlatLims[1], lonlatLims[3] |
---|
3606 | |
---|
3607 | # if map_proj == 'cyl': |
---|
3608 | # nlon = lonlatLims[0] |
---|
3609 | # nlat = lonlatLims[1] |
---|
3610 | # xlon = lonlatLims[2] |
---|
3611 | # xlat = lonlatLims[3] |
---|
3612 | # elif map_proj == 'lcc': |
---|
3613 | # lon2 = (lonlatLims[0] + lonlatLims[2])/2. |
---|
3614 | # lat2 = (lonlatLims[1] + lonlatLims[3])/2. |
---|
3615 | # nlon = lonlatLims[0] |
---|
3616 | # xlon = lonlatLims[2] |
---|
3617 | # nlat = lonlatLims[1] |
---|
3618 | # xlat = lonlatLims[3] |
---|
3619 | |
---|
3620 | lon2 = lon0[dy/2,dx/2] |
---|
3621 | lat2 = lat0[dy/2,dx/2] |
---|
3622 | |
---|
3623 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
3624 | xlon, ',', xlat |
---|
3625 | |
---|
3626 | if map_proj == 'cyl': |
---|
3627 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
3628 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
3629 | elif map_proj == 'lcc': |
---|
3630 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
3631 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
3632 | else: |
---|
3633 | print errormsg |
---|
3634 | print ' ' + fname + ": map projection '" + map_proj + "' not defined!!!" |
---|
3635 | print ' available: cyl, lcc' |
---|
3636 | quit(-1) |
---|
3637 | |
---|
3638 | x,y = m(lon0,lat0) |
---|
3639 | |
---|
3640 | else: |
---|
3641 | x = lon0 |
---|
3642 | y = lat0 |
---|
3643 | |
---|
3644 | vsend = np.zeros((2), dtype=np.float) |
---|
3645 | # Changing limits of the colors |
---|
3646 | if type(vs[0]) != type(np.float(1.)): |
---|
3647 | if vs[0] == 'Srange': |
---|
3648 | vsend[0] = np.min(varsv) |
---|
3649 | elif vs[0][0:11] == 'Saroundmean': |
---|
3650 | meanv = np.mean(varsv) |
---|
3651 | permean = np.float(vs[0].split('@')[1]) |
---|
3652 | minv = np.min(varsv)*permean |
---|
3653 | maxv = np.max(varsv)*permean |
---|
3654 | minextrm = np.min([np.abs(meanv-minv), np.abs(maxv-meanv)]) |
---|
3655 | vsend[0] = meanv-minextrm |
---|
3656 | vsend[1] = meanv+minextrm |
---|
3657 | elif vs[0][0:13] == 'Saroundminmax': |
---|
3658 | permean = np.float(vs[0].split('@')[1]) |
---|
3659 | minv = np.min(varsv)*permean |
---|
3660 | maxv = np.max(varsv)*permean |
---|
3661 | vsend[0] = minv |
---|
3662 | vsend[1] = maxv |
---|
3663 | elif vs[0][0:17] == 'Saroundpercentile': |
---|
3664 | medianv = np.median(varsv) |
---|
3665 | valper = np.float(vs[0].split('@')[1]) |
---|
3666 | minv = np.percentile(varsv, valper) |
---|
3667 | maxv = np.percentile(varsv, 100.-valper) |
---|
3668 | minextrm = np.min([np.abs(medianv-minv), np.abs(maxv-medianv)]) |
---|
3669 | vsend[0] = medianv-minextrm |
---|
3670 | vsend[1] = medianv+minextrm |
---|
3671 | elif vs[0][0:5] == 'Smean': |
---|
3672 | meanv = np.mean(varsv) |
---|
3673 | permean = np.float(vs[0].split('@')[1]) |
---|
3674 | minv = np.min(varsv)*permean |
---|
3675 | maxv = np.max(varsv)*permean |
---|
3676 | minextrm = np.min([np.abs(meanv-minv), np.abs(maxv-meanv)]) |
---|
3677 | vsend[0] = -minextrm |
---|
3678 | vsend[1] = minextrm |
---|
3679 | elif vs[0][0:7] == 'Smedian': |
---|
3680 | medianv = np.median(varsv) |
---|
3681 | permedian = np.float(vs[0].split('@')[1]) |
---|
3682 | minv = np.min(varsv)*permedian |
---|
3683 | maxv = np.max(varsv)*permedian |
---|
3684 | minextrm = np.min([np.abs(medianv-minv), np.abs(maxv-medianv)]) |
---|
3685 | vsend[0] = -minextrm |
---|
3686 | vsend[1] = minextrm |
---|
3687 | elif vs[0][0:11] == 'Spercentile': |
---|
3688 | medianv = np.median(varsv) |
---|
3689 | valper = np.float(vs[0].split('@')[1]) |
---|
3690 | minv = np.percentile(varsv, valper) |
---|
3691 | maxv = np.percentile(varsv, 100.-valper) |
---|
3692 | minextrm = np.min([np.abs(medianv-minv), np.abs(maxv-medianv)]) |
---|
3693 | vsend[0] = -minextrm |
---|
3694 | vsend[1] = minextrm |
---|
3695 | else: |
---|
3696 | print errormsg |
---|
3697 | print ' ' + fname + ": range '" + vs[0] + "' not ready!!!" |
---|
3698 | quit(-1) |
---|
3699 | print ' ' + fname + ': modified shadow min,max:',vsend |
---|
3700 | else: |
---|
3701 | vsend[0] = vs[0] |
---|
3702 | |
---|
3703 | if type(vs[0]) != type(np.float(1.)): |
---|
3704 | if vs[1] == 'range': |
---|
3705 | vsend[1] = np.max(varsv) |
---|
3706 | else: |
---|
3707 | vsend[1] = vs[1] |
---|
3708 | |
---|
3709 | plt.rc('text', usetex=True) |
---|
3710 | |
---|
3711 | plt.pcolormesh(x, y, varsv, cmap=plt.get_cmap(colorbar), vmin=vsend[0], vmax=vsend[1]) |
---|
3712 | cbar = plt.colorbar() |
---|
3713 | |
---|
3714 | if not mapv is None: |
---|
3715 | if colorbar == 'gist_gray': |
---|
3716 | m.drawcoastlines(color="red") |
---|
3717 | else: |
---|
3718 | m.drawcoastlines() |
---|
3719 | |
---|
3720 | meridians = pretty_int(nlon,xlon,5) |
---|
3721 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
3722 | parallels = pretty_int(nlat,xlat,5) |
---|
3723 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
3724 | |
---|
3725 | plt.xlabel('W-E') |
---|
3726 | plt.ylabel('S-N') |
---|
3727 | else: |
---|
3728 | plt.xlabel(variables_values(dimn[1])[0].replace('_','\_') + ' (' + \ |
---|
3729 | units_lunits(dimxu) + ')') |
---|
3730 | plt.ylabel(variables_values(dimn[0])[0].replace('_','\_') + ' (' + \ |
---|
3731 | units_lunits(dimyu) + ')') |
---|
3732 | |
---|
3733 | txpos = pretty_int(x.min(),x.max(),5) |
---|
3734 | typos = pretty_int(y.min(),y.max(),5) |
---|
3735 | txlabels = list(txpos) |
---|
3736 | for i in range(len(txlabels)): txlabels[i] = str(txlabels[i]) |
---|
3737 | tylabels = list(typos) |
---|
3738 | for i in range(len(tylabels)): tylabels[i] = str(tylabels[i]) |
---|
3739 | |
---|
3740 | # set the limits of the plot to the limits of the data |
---|
3741 | |
---|
3742 | if searchInlist(revas,'transpose'): |
---|
3743 | x0 = y |
---|
3744 | y0 = x |
---|
3745 | x = x0 |
---|
3746 | y = y0 |
---|
3747 | # print 'Lluis reva0:',reva0,'x min,max:',x.min(),x.max(),' y min,max:',y.min(),y.max() |
---|
3748 | |
---|
3749 | if reva0 == 'flip': |
---|
3750 | if reva.split('@')[1] == 'x': |
---|
3751 | plt.axis([x.max(), x.min(), y.min(), y.max()]) |
---|
3752 | elif reva.split('@')[1] == 'y': |
---|
3753 | plt.axis([x.min(), x.max(), y.max(), y.min()]) |
---|
3754 | else: |
---|
3755 | plt.axis([x.max(), x.min(), y.max(), y.min()]) |
---|
3756 | else: |
---|
3757 | plt.axis([x.min(), x.max(), y.min(), y.max()]) |
---|
3758 | |
---|
3759 | if mapv is None: |
---|
3760 | plt.xticks(txpos, txlabels) |
---|
3761 | plt.yticks(typos, tylabels) |
---|
3762 | |
---|
3763 | # units labels |
---|
3764 | cbar.set_label(vnames.replace('_','\_') + ' (' + units_lunits(uts) + ')') |
---|
3765 | |
---|
3766 | figname = '2Dfields_shadow' |
---|
3767 | graphtit = vtit.replace('_','\_').replace('&','\&') |
---|
3768 | |
---|
3769 | plt.title(graphtit) |
---|
3770 | |
---|
3771 | output_kind(kfig, figname, ifclose) |
---|
3772 | |
---|
3773 | return |
---|
3774 | |
---|
3775 | #Nvals=50 |
---|
3776 | #vals1 = np.zeros((Nvals,Nvals), dtype= np.float) |
---|
3777 | #for j in range(Nvals): |
---|
3778 | # for i in range(Nvals): |
---|
3779 | # vals1[j,i]=np.sqrt((j-Nvals/2)**2. + (i-Nvals/2)**2.) |
---|
3780 | |
---|
3781 | #plot_2D_shadow(vals1, 'var1', np.arange(50)*1., np.arange(50)*1., 'ms-1', \ |
---|
3782 | # 'm', ['lat','lon'], 'rainbow', [0, Nvals], 'ms-1', 'test var1', 'pdf', 'None', \ |
---|
3783 | # None, True) |
---|
3784 | #quit() |
---|
3785 | |
---|
3786 | def transform(vals, dxv, dyv, dxt, dyt, dxl, dyl, dxtit, dytit, trans): |
---|
3787 | """ Function to transform the values and the axes |
---|
3788 | vals= values to transform |
---|
3789 | d[x/y]v= original values for the [x/y]-axis |
---|
3790 | d[x/y]t= original ticks for the [x/y]-axis |
---|
3791 | d[x/y]l= original tick-labels for the [x/y]-axis |
---|
3792 | d[x/y]tit= original titels for the [x/y]-axis |
---|
3793 | trans= '|' separated list of operations of transformation |
---|
3794 | 'transpose': Transpose matrix of values (x-->y, y-->x) |
---|
3795 | 'flip@[x/y]': Flip the given axis |
---|
3796 | """ |
---|
3797 | fname = 'transform' |
---|
3798 | |
---|
3799 | return newvals, newdxv, newdyv |
---|
3800 | |
---|
3801 | def plot_2D_shadow_time(varsv,vnames,dimxv,dimyv,dimxu,dimyu,dimn,colorbar,vs,uts, \ |
---|
3802 | vtit,kfig,reva,taxis,tpos,tlabs,ifclose): |
---|
3803 | """ Plotting a 2D field with one of the axes being time |
---|
3804 | varsv= 2D values to plot with shading |
---|
3805 | vnames= shading variable name for the figure |
---|
3806 | dim[x/y]v= values at the axes of x and y |
---|
3807 | dim[x/y]u= units at the axes of x and y |
---|
3808 | dimn= dimension names to plot |
---|
3809 | colorbar= name of the color bar to use |
---|
3810 | vs= minmum and maximum values to plot in shadow or: |
---|
3811 | 'Srange': for full range |
---|
3812 | 'Saroundmean@val': for mean-xtrm,mean+xtrm where xtrm = np.min(mean-min@val,max@val-mean) |
---|
3813 | 'Saroundminmax@val': for min*val,max*val |
---|
3814 | 'Saroundpercentile@val': for median-xtrm,median+xtrm where xtrm = np.min(median-percentile_(val), |
---|
3815 | percentile_(100-val)-median) |
---|
3816 | 'Smean@val': for -xtrm,xtrm where xtrm = np.min(mean-min*@val,max*@val-mean) |
---|
3817 | 'Smedian@val': for -xtrm,xtrm where xtrm = np.min(median-min@val,max@val-median) |
---|
3818 | 'Spercentile@val': for -xtrm,xtrm where xtrm = np.min(median-percentile_(val), |
---|
3819 | percentile_(100-val)-median) |
---|
3820 | uts= units of the variable to shadow |
---|
3821 | vtit= title of the variable |
---|
3822 | kfig= kind of figure (jpg, pdf, png) |
---|
3823 | reva= |
---|
3824 | * 'transpose': reverse the axes (x-->y, y-->x) |
---|
3825 | * 'flip'@[x/y]: flip the axis x or y |
---|
3826 | taxis= Which is the time-axis |
---|
3827 | tpos= positions of the time ticks |
---|
3828 | tlabs= labels of the time ticks |
---|
3829 | ifclose= boolean value whether figure should be close (finish) or not |
---|
3830 | """ |
---|
3831 | fname = 'plot_2D_shadow_time' |
---|
3832 | |
---|
3833 | if varsv == 'h': |
---|
3834 | print fname + '_____________________________________________________________' |
---|
3835 | print plot_2D_shadow_time.__doc__ |
---|
3836 | quit() |
---|
3837 | |
---|
3838 | # Definning ticks labels |
---|
3839 | if taxis == 'x': |
---|
3840 | txpos = tpos |
---|
3841 | txlabels = tlabs |
---|
3842 | plxlabel = dimxu |
---|
3843 | typos = pretty_int(np.min(dimyv),np.max(dimyv),10) |
---|
3844 | tylabels = list(typos) |
---|
3845 | for i in range(len(tylabels)): tylabels[i] = str(tylabels[i]) |
---|
3846 | plylabel = variables_values(dimn[0])[0].replace('_','\_') + ' (' + \ |
---|
3847 | units_lunits(dimyu) + ')' |
---|
3848 | else: |
---|
3849 | txpos = pretty_int(np.min(dimxv),np.max(dimxv),10) |
---|
3850 | txlabels = list(txpos) |
---|
3851 | plxlabel = variables_values(dimn[1])[0].replace('_','\_') + ' (' + \ |
---|
3852 | units_lunits(dimxu) + ')' |
---|
3853 | typos = tpos |
---|
3854 | tylabels = tlabs |
---|
3855 | plylabel = dimyu |
---|
3856 | |
---|
3857 | # Transposing/flipping axis |
---|
3858 | if reva.find('|') != 0: |
---|
3859 | revas = reva.split('|') |
---|
3860 | reva0 = '' |
---|
3861 | else: |
---|
3862 | revas = [reva] |
---|
3863 | reva0 = reva |
---|
3864 | |
---|
3865 | for rev in revas: |
---|
3866 | if rev[0:4] == 'flip': |
---|
3867 | reva0 = 'flip' |
---|
3868 | if len(reva.split('@')) != 2: |
---|
3869 | print errormsg |
---|
3870 | print ' ' + fname + ': flip is given', reva, 'but not axis!' |
---|
3871 | quit(-1) |
---|
3872 | else: |
---|
3873 | print " flipping '" + rev.split('@')[1] + "' axis !" |
---|
3874 | |
---|
3875 | if rev == 'transpose': |
---|
3876 | print ' reversing the axes of the figure (x-->y, y-->x)!!' |
---|
3877 | # Flipping values of variable |
---|
3878 | varsv = np.transpose(varsv) |
---|
3879 | dxv = dimyv |
---|
3880 | dyv = dimxv |
---|
3881 | dimxv = dxv |
---|
3882 | dimyv = dyv |
---|
3883 | |
---|
3884 | if len(dimxv.shape) == 3: |
---|
3885 | dxget='1,2' |
---|
3886 | elif len(dimxv.shape) == 2: |
---|
3887 | dxget='0,1' |
---|
3888 | elif len(dimxv.shape) == 1: |
---|
3889 | dxget='0' |
---|
3890 | else: |
---|
3891 | print errormsg |
---|
3892 | print ' ' + fname + ': shape of x-values:',dimxv.shape,'not ready!!' |
---|
3893 | quit(-1) |
---|
3894 | |
---|
3895 | if len(dimyv.shape) == 3: |
---|
3896 | dyget='1,2' |
---|
3897 | elif len(dimyv.shape) == 2: |
---|
3898 | dyget='0,1' |
---|
3899 | elif len(dimyv.shape) == 1: |
---|
3900 | dyget='0' |
---|
3901 | else: |
---|
3902 | print errormsg |
---|
3903 | print ' ' + fname + ': shape of y-values:',dimyv.shape,'not ready!!' |
---|
3904 | quit(-1) |
---|
3905 | |
---|
3906 | x,y = dxdy_lonlat(dimxv,dimyv,dxget,dyget) |
---|
3907 | |
---|
3908 | plt.rc('text', usetex=True) |
---|
3909 | |
---|
3910 | vsend = np.zeros((2), dtype=np.float) |
---|
3911 | # Changing limits of the colors |
---|
3912 | if type(vs[0]) != type(np.float(1.)): |
---|
3913 | if vs[0] == 'Srange': |
---|
3914 | vsend[0] = np.min(varsv) |
---|
3915 | elif vs[0][0:11] == 'Saroundmean': |
---|
3916 | meanv = np.mean(varsv) |
---|
3917 | permean = np.float(vs[0].split('@')[1]) |
---|
3918 | minv = np.min(varsv)*permean |
---|
3919 | maxv = np.max(varsv)*permean |
---|
3920 | minextrm = np.min([np.abs(meanv-minv), np.abs(maxv-meanv)]) |
---|
3921 | vsend[0] = meanv-minextrm |
---|
3922 | vsend[1] = meanv+minextrm |
---|
3923 | elif vs[0][0:13] == 'Saroundminmax': |
---|
3924 | permean = np.float(vs[0].split('@')[1]) |
---|
3925 | minv = np.min(varsv)*permean |
---|
3926 | maxv = np.max(varsv)*permean |
---|
3927 | vsend[0] = minv |
---|
3928 | vsend[1] = maxv |
---|
3929 | elif vs[0][0:17] == 'Saroundpercentile': |
---|
3930 | medianv = np.median(varsv) |
---|
3931 | valper = np.float(vs[0].split('@')[1]) |
---|
3932 | minv = np.percentile(varsv, valper) |
---|
3933 | maxv = np.percentile(varsv, 100.-valper) |
---|
3934 | minextrm = np.min([np.abs(medianv-minv), np.abs(maxv-medianv)]) |
---|
3935 | vsend[0] = medianv-minextrm |
---|
3936 | vsend[1] = medianv+minextrm |
---|
3937 | elif vs[0][0:5] == 'Smean': |
---|
3938 | meanv = np.mean(varsv) |
---|
3939 | permean = np.float(vs[0].split('@')[1]) |
---|
3940 | minv = np.min(varsv)*permean |
---|
3941 | maxv = np.max(varsv)*permean |
---|
3942 | minextrm = np.min([np.abs(meanv-minv), np.abs(maxv-meanv)]) |
---|
3943 | vsend[0] = -minextrm |
---|
3944 | vsend[1] = minextrm |
---|
3945 | elif vs[0][0:7] == 'Smedian': |
---|
3946 | medianv = np.median(varsv) |
---|
3947 | permedian = np.float(vs[0].split('@')[1]) |
---|
3948 | minv = np.min(varsv)*permedian |
---|
3949 | maxv = np.max(varsv)*permedian |
---|
3950 | minextrm = np.min([np.abs(medianv-minv), np.abs(maxv-medianv)]) |
---|
3951 | vsend[0] = -minextrm |
---|
3952 | vsend[1] = minextrm |
---|
3953 | elif vs[0][0:11] == 'Spercentile': |
---|
3954 | medianv = np.median(varsv) |
---|
3955 | valper = np.float(vs[0].split('@')[1]) |
---|
3956 | minv = np.percentile(varsv, valper) |
---|
3957 | maxv = np.percentile(varsv, 100.-valper) |
---|
3958 | minextrm = np.min([np.abs(medianv-minv), np.abs(maxv-medianv)]) |
---|
3959 | vsend[0] = -minextrm |
---|
3960 | vsend[1] = minextrm |
---|
3961 | else: |
---|
3962 | print errormsg |
---|
3963 | print ' ' + fname + ": range '" + vs[0] + "' not ready!!!" |
---|
3964 | quit(-1) |
---|
3965 | print ' ' + fname + ': modified shadow min,max:',vsend |
---|
3966 | else: |
---|
3967 | vsend[0] = vs[0] |
---|
3968 | |
---|
3969 | if type(vs[0]) != type(np.float(1.)): |
---|
3970 | if vs[1] == 'range': |
---|
3971 | vsend[1] = np.max(varsv) |
---|
3972 | else: |
---|
3973 | vsend[1] = vs[1] |
---|
3974 | |
---|
3975 | plt.pcolormesh(x, y, varsv, cmap=plt.get_cmap(colorbar), vmin=vsend[0], vmax=vsend[1]) |
---|
3976 | cbar = plt.colorbar() |
---|
3977 | |
---|
3978 | # print 'Lluis reva0:',reva0,'x min,max:',x.min(),x.max(),' y min,max:',y.min(),y.max() |
---|
3979 | |
---|
3980 | # set the limits of the plot to the limits of the data |
---|
3981 | if reva0 == 'flip': |
---|
3982 | if reva.split('@')[1] == 'x': |
---|
3983 | plt.axis([x.max(), x.min(), y.min(), y.max()]) |
---|
3984 | elif reva.split('@')[1] == 'y': |
---|
3985 | plt.axis([x.min(), x.max(), y.max(), y.min()]) |
---|
3986 | else: |
---|
3987 | plt.axis([x.max(), x.min(), y.max(), y.min()]) |
---|
3988 | else: |
---|
3989 | plt.axis([x.min(), x.max(), y.min(), y.max()]) |
---|
3990 | |
---|
3991 | if searchInlist(revas, 'transpose'): |
---|
3992 | plt.xticks(typos, tylabels) |
---|
3993 | plt.yticks(txpos, txlabels) |
---|
3994 | plt.xlabel(plylabel) |
---|
3995 | plt.ylabel(plxlabel) |
---|
3996 | else: |
---|
3997 | plt.xticks(txpos, txlabels) |
---|
3998 | plt.yticks(typos, tylabels) |
---|
3999 | plt.xlabel(plxlabel) |
---|
4000 | plt.ylabel(plylabel) |
---|
4001 | |
---|
4002 | # units labels |
---|
4003 | cbar.set_label(vnames.replace('_','\_') + ' (' + units_lunits(uts) + ')') |
---|
4004 | |
---|
4005 | figname = '2Dfields_shadow_time' |
---|
4006 | graphtit = vtit.replace('_','\_').replace('&','\&') |
---|
4007 | |
---|
4008 | plt.title(graphtit) |
---|
4009 | |
---|
4010 | output_kind(kfig, figname, ifclose) |
---|
4011 | |
---|
4012 | return |
---|
4013 | |
---|
4014 | def plot_2D_shadow_contour(varsv,varcv,vnames,dimxv,dimyv,dimxu,dimyu,dimn, \ |
---|
4015 | colorbar,ckind,clabfmt,vs,vc,uts,vtit,kfig,reva,mapv): |
---|
4016 | """ Adding labels and other staff to the graph |
---|
4017 | varsv= 2D values to plot with shading |
---|
4018 | varcv= 2D values to plot with contours |
---|
4019 | vnames= variable names for the figure |
---|
4020 | dim[x/y]v = values at the axes of x and y |
---|
4021 | dim[x/y]u = units at the axes of x and y |
---|
4022 | dimn= dimension names to plot |
---|
4023 | colorbar= name of the color bar to use |
---|
4024 | ckind= contour kind |
---|
4025 | 'cmap': as it gets from colorbar |
---|
4026 | 'fixc,[colname]': fixed color [colname], all stright lines |
---|
4027 | 'fixsigc,[colname]': fixed color [colname], >0 stright, <0 dashed line |
---|
4028 | clabfmt= format of the labels in the contour plot (None, no labels) |
---|
4029 | vs= minmum and maximum values to plot in shadow |
---|
4030 | vc= vector with the levels for the contour |
---|
4031 | uts= units of the variable [u-shadow, u-contour] |
---|
4032 | vtit= title of the variable |
---|
4033 | kfig= kind of figure (jpg, pdf, png) |
---|
4034 | reva= |
---|
4035 | * 'transpose': reverse the axes (x-->y, y-->x) |
---|
4036 | * 'flip'@[x/y]: flip the axis x or y |
---|
4037 | mapv= map characteristics: [proj],[res] |
---|
4038 | see full documentation: http://matplotlib.org/basemap/ |
---|
4039 | [proj]: projection |
---|
4040 | * 'cyl', cilindric |
---|
4041 | * 'lcc', lamvbert conformal |
---|
4042 | [res]: resolution: |
---|
4043 | * 'c', crude |
---|
4044 | * 'l', low |
---|
4045 | * 'i', intermediate |
---|
4046 | * 'h', high |
---|
4047 | * 'f', full |
---|
4048 | """ |
---|
4049 | ## import matplotlib as mpl |
---|
4050 | ## mpl.use('Agg') |
---|
4051 | ## import matplotlib.pyplot as plt |
---|
4052 | fname = 'plot_2D_shadow_contour' |
---|
4053 | |
---|
4054 | if varsv == 'h': |
---|
4055 | print fname + '_____________________________________________________________' |
---|
4056 | print plot_2D_shadow_contour.__doc__ |
---|
4057 | quit() |
---|
4058 | |
---|
4059 | if reva[0:4] == 'flip': |
---|
4060 | reva0 = 'flip' |
---|
4061 | if len(reva.split('@')) != 2: |
---|
4062 | print errormsg |
---|
4063 | print ' ' + fname + ': flip is given', reva, 'but not axis!' |
---|
4064 | quit(-1) |
---|
4065 | else: |
---|
4066 | reva0 = reva |
---|
4067 | |
---|
4068 | if reva0 == 'transpose': |
---|
4069 | print ' reversing the axes of the figure (x-->y, y-->x)!!' |
---|
4070 | varsv = np.transpose(varsv) |
---|
4071 | varcv = np.transpose(varcv) |
---|
4072 | dxv = dimyv |
---|
4073 | dyv = dimxv |
---|
4074 | dimxv = dxv |
---|
4075 | dimyv = dyv |
---|
4076 | |
---|
4077 | if not mapv is None: |
---|
4078 | if len(dimxv[:].shape) == 3: |
---|
4079 | lon0 = dimxv[0,] |
---|
4080 | lat0 = dimyv[0,] |
---|
4081 | elif len(dimxv[:].shape) == 2: |
---|
4082 | lon0 = dimxv[:] |
---|
4083 | lat0 = dimyv[:] |
---|
4084 | elif len(dimxv[:].shape) == 1: |
---|
4085 | lon00 = dimxv[:] |
---|
4086 | lat00 = dimyv[:] |
---|
4087 | lon0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
4088 | lat0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
4089 | |
---|
4090 | for iy in range(len(lat00)): |
---|
4091 | lon0[iy,:] = lon00 |
---|
4092 | for ix in range(len(lon00)): |
---|
4093 | lat0[:,ix] = lat00 |
---|
4094 | |
---|
4095 | map_proj=mapv.split(',')[0] |
---|
4096 | map_res=mapv.split(',')[1] |
---|
4097 | |
---|
4098 | dx = lon0.shape[1] |
---|
4099 | dy = lon0.shape[0] |
---|
4100 | |
---|
4101 | nlon = lon0[0,0] |
---|
4102 | xlon = lon0[dy-1,dx-1] |
---|
4103 | nlat = lat0[0,0] |
---|
4104 | xlat = lat0[dy-1,dx-1] |
---|
4105 | |
---|
4106 | # Thats too much! :) |
---|
4107 | # if lonlatLims is not None: |
---|
4108 | # print ' ' + fname + ': cutting the domain to plot !!!!' |
---|
4109 | # plt.xlim(lonlatLims[0], lonlatLims[2]) |
---|
4110 | # plt.ylim(lonlatLims[1], lonlatLims[3]) |
---|
4111 | # print ' limits: W-E', lonlatLims[0], lonlatLims[2] |
---|
4112 | # print ' limits: N-S', lonlatLims[1], lonlatLims[3] |
---|
4113 | |
---|
4114 | # if map_proj == 'cyl': |
---|
4115 | # nlon = lonlatLims[0] |
---|
4116 | # nlat = lonlatLims[1] |
---|
4117 | # xlon = lonlatLims[2] |
---|
4118 | # xlat = lonlatLims[3] |
---|
4119 | # elif map_proj == 'lcc': |
---|
4120 | # lon2 = (lonlatLims[0] + lonlatLims[2])/2. |
---|
4121 | # lat2 = (lonlatLims[1] + lonlatLims[3])/2. |
---|
4122 | # nlon = lonlatLims[0] |
---|
4123 | # xlon = lonlatLims[2] |
---|
4124 | # nlat = lonlatLims[1] |
---|
4125 | # xlat = lonlatLims[3] |
---|
4126 | |
---|
4127 | lon2 = lon0[dy/2,dx/2] |
---|
4128 | lat2 = lat0[dy/2,dx/2] |
---|
4129 | |
---|
4130 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
4131 | xlon, ',', xlat |
---|
4132 | |
---|
4133 | if map_proj == 'cyl': |
---|
4134 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
4135 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
4136 | elif map_proj == 'lcc': |
---|
4137 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
4138 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
4139 | |
---|
4140 | if len(dimxv.shape) == 1: |
---|
4141 | lons, lats = np.meshgrid(dimxv, dimyv) |
---|
4142 | else: |
---|
4143 | if len(dimxv.shape) == 3: |
---|
4144 | lons = dimxv[0,:,:] |
---|
4145 | lats = dimyv[0,:,:] |
---|
4146 | else: |
---|
4147 | lons = dimxv[:] |
---|
4148 | lats = dimyv[:] |
---|
4149 | |
---|
4150 | x,y = m(lons,lats) |
---|
4151 | |
---|
4152 | else: |
---|
4153 | if len(dimxv.shape) == 2: |
---|
4154 | x = dimxv |
---|
4155 | else: |
---|
4156 | if len(dimyv.shape) == 1: |
---|
4157 | x = np.zeros((len(dimyv),len(dimxv)), dtype=np.float) |
---|
4158 | for j in range(len(dimyv)): |
---|
4159 | x[j,:] = dimxv |
---|
4160 | else: |
---|
4161 | x = np.zeros((dimyv.shape), dtype=np.float) |
---|
4162 | if x.shape[0] == dimxv.shape[0]: |
---|
4163 | for j in range(x.shape[1]): |
---|
4164 | x[:,j] = dimxv |
---|
4165 | else: |
---|
4166 | for j in range(x.shape[0]): |
---|
4167 | x[j,:] = dimxv |
---|
4168 | |
---|
4169 | if len(dimyv.shape) == 2: |
---|
4170 | y = dimyv |
---|
4171 | else: |
---|
4172 | if len(dimxv.shape) == 1: |
---|
4173 | y = np.zeros((len(dimyv),len(dimxv)), dtype=np.float) |
---|
4174 | for i in range(len(dimxv)): |
---|
4175 | y[:,i] = dimyv |
---|
4176 | else: |
---|
4177 | y = np.zeros((dimxv.shape), dtype=np.float) |
---|
4178 | |
---|
4179 | if y.shape[0] == dimyv.shape[0]: |
---|
4180 | for i in range(y.shape[1]): |
---|
4181 | y[i,:] = dimyv |
---|
4182 | else: |
---|
4183 | for i in range(y.shape[0]): |
---|
4184 | y[i,:] = dimyv |
---|
4185 | |
---|
4186 | plt.rc('text', usetex=True) |
---|
4187 | |
---|
4188 | plt.pcolormesh(x, y, varsv, cmap=plt.get_cmap(colorbar), vmin=vs[0], vmax=vs[1]) |
---|
4189 | cbar = plt.colorbar() |
---|
4190 | |
---|
4191 | # contour |
---|
4192 | ## |
---|
4193 | contkind = ckind.split(',')[0] |
---|
4194 | if contkind == 'cmap': |
---|
4195 | cplot = plt.contour(x, y, varcv, levels=vc) |
---|
4196 | elif contkind == 'fixc': |
---|
4197 | plt.rcParams['contour.negative_linestyle'] = 'solid' |
---|
4198 | coln = ckind.split(',')[1] |
---|
4199 | cplot = plt.contour(x, y, varcv, levels=vc, colors=coln) |
---|
4200 | elif contkind == 'fixsigc': |
---|
4201 | coln = ckind.split(',')[1] |
---|
4202 | cplot = plt.contour(x, y, varcv, levels=vc, colors=coln) |
---|
4203 | else: |
---|
4204 | print errormsg |
---|
4205 | print ' ' + fname + ': contour kind "' + contkind + '" not defined !!!!!' |
---|
4206 | quit(-1) |
---|
4207 | |
---|
4208 | if clabfmt is not None: |
---|
4209 | plt.clabel(cplot, fmt=clabfmt) |
---|
4210 | mincntS = format(vc[0], clabfmt[1:len(clabfmt)]) |
---|
4211 | maxcntS = format(vc[len(vc)-1], clabfmt[1:len(clabfmt)]) |
---|
4212 | else: |
---|
4213 | mincntS = '{:g}'.format(vc[0]) |
---|
4214 | maxcntS = '{:g}'.format(vc[len(vc)-1]) |
---|
4215 | |
---|
4216 | if not mapv is None: |
---|
4217 | m.drawcoastlines() |
---|
4218 | |
---|
4219 | meridians = pretty_int(nlon,xlon,5) |
---|
4220 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
4221 | parallels = pretty_int(nlat,xlat,5) |
---|
4222 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
4223 | |
---|
4224 | plt.xlabel('W-E') |
---|
4225 | plt.ylabel('S-N') |
---|
4226 | else: |
---|
4227 | plt.xlabel(variables_values(dimn[1])[0] + ' (' + units_lunits(dimxu) + ')') |
---|
4228 | plt.ylabel(variables_values(dimn[0])[0] + ' (' + units_lunits(dimyu) + ')') |
---|
4229 | |
---|
4230 | txpos = pretty_int(x.min(),x.max(),5) |
---|
4231 | typos = pretty_int(y.min(),y.max(),5) |
---|
4232 | txlabels = list(txpos) |
---|
4233 | for i in range(len(txlabels)): txlabels[i] = '{:.1f}'.format(txlabels[i]) |
---|
4234 | tylabels = list(typos) |
---|
4235 | for i in range(len(tylabels)): tylabels[i] = '{:.1f}'.format(tylabels[i]) |
---|
4236 | plt.xticks(txpos, txlabels) |
---|
4237 | plt.yticks(typos, tylabels) |
---|
4238 | |
---|
4239 | # set the limits of the plot to the limits of the data |
---|
4240 | if reva0 == 'flip': |
---|
4241 | if reva.split('@')[1] == 'x': |
---|
4242 | plt.axis([x.max(), x.min(), y.min(), y.max()]) |
---|
4243 | else: |
---|
4244 | plt.axis([x.min(), x.max(), y.max(), y.min()]) |
---|
4245 | else: |
---|
4246 | plt.axis([x.min(), x.max(), y.min(), y.max()]) |
---|
4247 | |
---|
4248 | |
---|
4249 | # units labels |
---|
4250 | cbar.set_label(vnames[0].replace('_','\_') + ' (' + units_lunits(uts[0]) + ')') |
---|
4251 | plt.annotate(vnames[1].replace('_','\_') +' (' + units_lunits(uts[1]) + ') [' + \ |
---|
4252 | mincntS + ', ' + maxcntS + ']', xy=(0.55,0.04), xycoords='figure fraction', \ |
---|
4253 | color=coln) |
---|
4254 | |
---|
4255 | figname = '2Dfields_shadow-contour' |
---|
4256 | graphtit = vtit.replace('_','\_').replace('&','\&') |
---|
4257 | |
---|
4258 | plt.title(graphtit) |
---|
4259 | |
---|
4260 | output_kind(kfig, figname, True) |
---|
4261 | |
---|
4262 | return |
---|
4263 | |
---|
4264 | #Nvals=50 |
---|
4265 | #vals1 = np.zeros((Nvals,Nvals), dtype= np.float) |
---|
4266 | #vals2 = np.zeros((Nvals,Nvals), dtype= np.float) |
---|
4267 | #for j in range(Nvals): |
---|
4268 | # for i in range(Nvals): |
---|
4269 | # vals1[j,i]=np.sqrt((j-Nvals/2)**2. + (i-Nvals/2)**2.) |
---|
4270 | # vals2[j,i]=np.sqrt((j-Nvals/2)**2. + (i-Nvals/2)**2.) - Nvals/2 |
---|
4271 | |
---|
4272 | #prettylev=pretty_int(-Nvals/2,Nvals/2,10) |
---|
4273 | |
---|
4274 | #plot_2D_shadow_contour(vals1, vals2, ['var1', 'var2'], np.arange(50)*1., \ |
---|
4275 | # np.arange(50)*1., ['x-axis','y-axis'], 'rainbow', 'fixc,b', "%.2f", [0, Nvals], \ |
---|
4276 | # prettylev, ['$ms^{-1}$','$kJm^{-1}s^{-1}$'], 'test var1 & var2', 'pdf', False) |
---|
4277 | |
---|
4278 | def plot_2D_shadow_contour_time(varsv,varcv,vnames,valv,timv,timpos,timlab,valu, \ |
---|
4279 | timeu,axist,dimn,colorbar,ckind,clabfmt,vs,vc,uts,vtit,kfig,reva,mapv): |
---|
4280 | """ Adding labels and other staff to the graph |
---|
4281 | varsv= 2D values to plot with shading |
---|
4282 | varcv= 2D values to plot with contours |
---|
4283 | vnames= variable names for the figure |
---|
4284 | valv = values at the axes which is not time |
---|
4285 | timv = values for the axis time |
---|
4286 | timpos = positions at the axis time |
---|
4287 | timlab = labes at the axis time |
---|
4288 | valu = units at the axes which is not time |
---|
4289 | timeu = units at the axes which is not time |
---|
4290 | axist = which is the axis time |
---|
4291 | dimn= dimension names to plot |
---|
4292 | colorbar= name of the color bar to use |
---|
4293 | ckind= contour kind |
---|
4294 | 'cmap': as it gets from colorbar |
---|
4295 | 'fixc,[colname]': fixed color [colname], all stright lines |
---|
4296 | 'fixsigc,[colname]': fixed color [colname], >0 stright, <0 dashed line |
---|
4297 | clabfmt= format of the labels in the contour plot (None, no labels) |
---|
4298 | vs= minmum and maximum values to plot in shadow |
---|
4299 | vc= vector with the levels for the contour |
---|
4300 | uts= units of the variable [u-shadow, u-contour] |
---|
4301 | vtit= title of the variable |
---|
4302 | kfig= kind of figure (jpg, pdf, png) |
---|
4303 | reva= |
---|
4304 | * 'transpose': reverse the axes (x-->y, y-->x) |
---|
4305 | * 'flip'@[x/y]: flip the axis x or y |
---|
4306 | mapv= map characteristics: [proj],[res] |
---|
4307 | see full documentation: http://matplotlib.org/basemap/ |
---|
4308 | [proj]: projection |
---|
4309 | * 'cyl', cilindric |
---|
4310 | * 'lcc', lamvbert conformal |
---|
4311 | [res]: resolution: |
---|
4312 | * 'c', crude |
---|
4313 | * 'l', low |
---|
4314 | * 'i', intermediate |
---|
4315 | * 'h', high |
---|
4316 | * 'f', full |
---|
4317 | """ |
---|
4318 | ## import matplotlib as mpl |
---|
4319 | ## mpl.use('Agg') |
---|
4320 | ## import matplotlib.pyplot as plt |
---|
4321 | fname = 'plot_2D_shadow_contour' |
---|
4322 | |
---|
4323 | if varsv == 'h': |
---|
4324 | print fname + '_____________________________________________________________' |
---|
4325 | print plot_2D_shadow_contour.__doc__ |
---|
4326 | quit() |
---|
4327 | |
---|
4328 | if axist == 'x': |
---|
4329 | dimxv = timv.copy() |
---|
4330 | dimyv = valv.copy() |
---|
4331 | else: |
---|
4332 | dimxv = valv.copy() |
---|
4333 | dimyv = timv.copy() |
---|
4334 | |
---|
4335 | if reva[0:4] == 'flip': |
---|
4336 | reva0 = 'flip' |
---|
4337 | if len(reva.split('@')) != 2: |
---|
4338 | print errormsg |
---|
4339 | print ' ' + fname + ': flip is given', reva, 'but not axis!' |
---|
4340 | quit(-1) |
---|
4341 | else: |
---|
4342 | reva0 = reva |
---|
4343 | |
---|
4344 | if reva0 == 'transpose': |
---|
4345 | if axist == 'x': |
---|
4346 | axist = 'y' |
---|
4347 | else: |
---|
4348 | axist = 'x' |
---|
4349 | |
---|
4350 | if not mapv is None: |
---|
4351 | if len(dimxv[:].shape) == 3: |
---|
4352 | lon0 = dimxv[0,] |
---|
4353 | lat0 = dimyv[0,] |
---|
4354 | elif len(dimxv[:].shape) == 2: |
---|
4355 | lon0 = dimxv[:] |
---|
4356 | lat0 = dimyv[:] |
---|
4357 | elif len(dimxv[:].shape) == 1: |
---|
4358 | lon00 = dimxv[:] |
---|
4359 | lat00 = dimyv[:] |
---|
4360 | lon0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
4361 | lat0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
4362 | |
---|
4363 | for iy in range(len(lat00)): |
---|
4364 | lon0[iy,:] = lon00 |
---|
4365 | for ix in range(len(lon00)): |
---|
4366 | lat0[:,ix] = lat00 |
---|
4367 | if reva0 == 'transpose': |
---|
4368 | print ' reversing the axes of the figure (x-->y, y-->x)!!' |
---|
4369 | varsv = np.transpose(varsv) |
---|
4370 | varcv = np.transpose(varcv) |
---|
4371 | lon0 = np.transpose(lon0) |
---|
4372 | lat0 = np.transpose(lat0) |
---|
4373 | |
---|
4374 | map_proj=mapv.split(',')[0] |
---|
4375 | map_res=mapv.split(',')[1] |
---|
4376 | |
---|
4377 | dx = lon0.shape[1] |
---|
4378 | dy = lon0.shape[0] |
---|
4379 | |
---|
4380 | nlon = lon0[0,0] |
---|
4381 | xlon = lon0[dy-1,dx-1] |
---|
4382 | nlat = lat0[0,0] |
---|
4383 | xlat = lat0[dy-1,dx-1] |
---|
4384 | |
---|
4385 | # Thats too much! :) |
---|
4386 | # if lonlatLims is not None: |
---|
4387 | # print ' ' + fname + ': cutting the domain to plot !!!!' |
---|
4388 | # plt.xlim(lonlatLims[0], lonlatLims[2]) |
---|
4389 | # plt.ylim(lonlatLims[1], lonlatLims[3]) |
---|
4390 | # print ' limits: W-E', lonlatLims[0], lonlatLims[2] |
---|
4391 | # print ' limits: N-S', lonlatLims[1], lonlatLims[3] |
---|
4392 | |
---|
4393 | # if map_proj == 'cyl': |
---|
4394 | # nlon = lonlatLims[0] |
---|
4395 | # nlat = lonlatLims[1] |
---|
4396 | # xlon = lonlatLims[2] |
---|
4397 | # xlat = lonlatLims[3] |
---|
4398 | # elif map_proj == 'lcc': |
---|
4399 | # lon2 = (lonlatLims[0] + lonlatLims[2])/2. |
---|
4400 | # lat2 = (lonlatLims[1] + lonlatLims[3])/2. |
---|
4401 | # nlon = lonlatLims[0] |
---|
4402 | # xlon = lonlatLims[2] |
---|
4403 | # nlat = lonlatLims[1] |
---|
4404 | # xlat = lonlatLims[3] |
---|
4405 | |
---|
4406 | lon2 = lon0[dy/2,dx/2] |
---|
4407 | lat2 = lat0[dy/2,dx/2] |
---|
4408 | |
---|
4409 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
4410 | xlon, ',', xlat |
---|
4411 | |
---|
4412 | if map_proj == 'cyl': |
---|
4413 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
4414 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
4415 | elif map_proj == 'lcc': |
---|
4416 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
4417 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
4418 | |
---|
4419 | if len(dimxv.shape) == 1: |
---|
4420 | lons, lats = np.meshgrid(dimxv, dimyv) |
---|
4421 | else: |
---|
4422 | if len(dimxv.shape) == 3: |
---|
4423 | lons = dimxv[0,:,:] |
---|
4424 | lats = dimyv[0,:,:] |
---|
4425 | else: |
---|
4426 | lons = dimxv[:] |
---|
4427 | lats = dimyv[:] |
---|
4428 | |
---|
4429 | x,y = m(lons,lats) |
---|
4430 | |
---|
4431 | else: |
---|
4432 | if reva0 == 'transpose': |
---|
4433 | print ' reversing the axes of the figure (x-->y, y-->x)!!' |
---|
4434 | varsv = np.transpose(varsv) |
---|
4435 | varcv = np.transpose(varcv) |
---|
4436 | dimn0 = [] |
---|
4437 | dimn0.append(dimn[1] + '') |
---|
4438 | dimn0.append(dimn[0] + '') |
---|
4439 | dimn = dimn0 |
---|
4440 | if len(dimyv.shape) == 2: |
---|
4441 | x = np.transpose(dimyv) |
---|
4442 | else: |
---|
4443 | if len(dimxv.shape) == 2: |
---|
4444 | ddx = len(dimyv) |
---|
4445 | ddy = dimxv.shape[1] |
---|
4446 | else: |
---|
4447 | ddx = len(dimyv) |
---|
4448 | ddy = len(dimxv) |
---|
4449 | |
---|
4450 | x = np.zeros((ddy,ddx), dtype=np.float) |
---|
4451 | for j in range(ddy): |
---|
4452 | x[j,:] = dimyv |
---|
4453 | |
---|
4454 | if len(dimxv.shape) == 2: |
---|
4455 | y = np.transpose(dimxv) |
---|
4456 | else: |
---|
4457 | if len(dimyv.shape) == 2: |
---|
4458 | ddx = dimyv.shape[0] |
---|
4459 | ddy = len(dimxv) |
---|
4460 | else: |
---|
4461 | ddx = len(dimyv) |
---|
4462 | ddy = len(dimxv) |
---|
4463 | |
---|
4464 | y = np.zeros((ddy,ddx), dtype=np.float) |
---|
4465 | for i in range(ddx): |
---|
4466 | y[:,i] = dimxv |
---|
4467 | else: |
---|
4468 | if len(dimxv.shape) == 2: |
---|
4469 | x = dimxv |
---|
4470 | else: |
---|
4471 | if len(dimyv.shape) == 1: |
---|
4472 | x = np.zeros((len(dimyv),len(dimxv)), dtype=np.float) |
---|
4473 | for j in range(len(dimyv)): |
---|
4474 | x[j,:] = dimxv |
---|
4475 | else: |
---|
4476 | x = np.zeros((dimyv.shape), dtype=np.float) |
---|
4477 | if x.shape[0] == dimxv.shape[0]: |
---|
4478 | for j in range(x.shape[1]): |
---|
4479 | x[:,j] = dimxv |
---|
4480 | else: |
---|
4481 | for j in range(x.shape[0]): |
---|
4482 | x[j,:] = dimxv |
---|
4483 | |
---|
4484 | if len(dimyv.shape) == 2: |
---|
4485 | y = dimyv |
---|
4486 | else: |
---|
4487 | if len(dimxv.shape) == 1: |
---|
4488 | y = np.zeros((len(dimyv),len(dimxv)), dtype=np.float) |
---|
4489 | for i in range(len(dimxv)): |
---|
4490 | y[:,i] = dimyv |
---|
4491 | else: |
---|
4492 | y = np.zeros((dimxv.shape), dtype=np.float) |
---|
4493 | if y.shape[0] == dimyv.shape[0]: |
---|
4494 | for i in range(y.shape[1]): |
---|
4495 | y[:,i] = dimyv |
---|
4496 | else: |
---|
4497 | for i in range(y.shape[0]): |
---|
4498 | y[i,:] = dimyv |
---|
4499 | |
---|
4500 | dx=varsv.shape[1] |
---|
4501 | dy=varsv.shape[0] |
---|
4502 | |
---|
4503 | plt.rc('text', usetex=True) |
---|
4504 | |
---|
4505 | if axist == 'x': |
---|
4506 | valpos = pretty_int(y.min(),y.max(),10) |
---|
4507 | vallabels = list(valpos) |
---|
4508 | for i in range(len(vallabels)): vallabels[i] = str(vallabels[i]) |
---|
4509 | else: |
---|
4510 | valpos = pretty_int(x.min(),x.max(),10) |
---|
4511 | vallabels = list(valpos) |
---|
4512 | for i in range(len(vallabels)): vallabels[i] = str(vallabels[i]) |
---|
4513 | |
---|
4514 | if reva0 == 'flip': |
---|
4515 | if reva.split('@')[1] == 'x': |
---|
4516 | varsv[:,0:dx-1] = varsv[:,dx-1:0:-1] |
---|
4517 | varcv[:,0:dx-1] = varcv[:,dx-1:0:-1] |
---|
4518 | plt.xticks(valpos, vallabels[::-1]) |
---|
4519 | else: |
---|
4520 | varsv[0:dy-1,:] = varsv[dy-1:0:-1,:] |
---|
4521 | varcv[0:dy-1,:] = varcv[dy-1:0:-1,:] |
---|
4522 | plt.yticks(valpos, vallabels[::-1]) |
---|
4523 | else: |
---|
4524 | plt.xlim(0,dx-1) |
---|
4525 | plt.ylim(0,dy-1) |
---|
4526 | |
---|
4527 | plt.pcolormesh(x, y, varsv, cmap=plt.get_cmap(colorbar), vmin=vs[0], vmax=vs[1]) |
---|
4528 | cbar = plt.colorbar() |
---|
4529 | |
---|
4530 | # contour |
---|
4531 | ## |
---|
4532 | contkind = ckind.split(',')[0] |
---|
4533 | if contkind == 'cmap': |
---|
4534 | cplot = plt.contour(x, y, varcv, levels=vc) |
---|
4535 | elif contkind == 'fixc': |
---|
4536 | plt.rcParams['contour.negative_linestyle'] = 'solid' |
---|
4537 | coln = ckind.split(',')[1] |
---|
4538 | cplot = plt.contour(x, y, varcv, levels=vc, colors=coln) |
---|
4539 | elif contkind == 'fixsigc': |
---|
4540 | coln = ckind.split(',')[1] |
---|
4541 | cplot = plt.contour(x, y, varcv, levels=vc, colors=coln) |
---|
4542 | else: |
---|
4543 | print errormsg |
---|
4544 | print ' ' + fname + ': contour kind "' + contkind + '" not defined !!!!!' |
---|
4545 | quit(-1) |
---|
4546 | |
---|
4547 | if clabfmt is not None: |
---|
4548 | plt.clabel(cplot, fmt=clabfmt) |
---|
4549 | mincntS = format(vc[0], clabfmt[1:len(clabfmt)]) |
---|
4550 | maxcntS = format(vc[len(vc)-1], clabfmt[1:len(clabfmt)]) |
---|
4551 | else: |
---|
4552 | mincntS = '{:g}'.format(vc[0]) |
---|
4553 | maxcntS = '{:g}'.format(vc[len(vc)-1]) |
---|
4554 | |
---|
4555 | if not mapv is None: |
---|
4556 | m.drawcoastlines() |
---|
4557 | |
---|
4558 | meridians = pretty_int(nlon,xlon,5) |
---|
4559 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
4560 | parallels = pretty_int(nlat,xlat,5) |
---|
4561 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
4562 | |
---|
4563 | plt.xlabel('W-E') |
---|
4564 | plt.ylabel('S-N') |
---|
4565 | else: |
---|
4566 | if axist == 'x': |
---|
4567 | plt.xlabel(timeu) |
---|
4568 | plt.xticks(timpos, timlab) |
---|
4569 | plt.ylabel(variables_values(dimn[0])[0] + ' (' + units_lunits(valu) + ')') |
---|
4570 | plt.yticks(valpos, vallabels) |
---|
4571 | else: |
---|
4572 | plt.xlabel(variables_values(dimn[1])[0] + ' (' + units_lunits(valu) + ')') |
---|
4573 | plt.xticks(valpos, vallabels) |
---|
4574 | plt.ylabel(timeu) |
---|
4575 | plt.yticks(timpos, timlab) |
---|
4576 | |
---|
4577 | # set the limits of the plot to the limits of the data |
---|
4578 | plt.axis([x.min(), x.max(), y.min(), y.max()]) |
---|
4579 | |
---|
4580 | # units labels |
---|
4581 | cbar.set_label(vnames[0].replace('_','\_') + ' (' + units_lunits(uts[0]) + ')') |
---|
4582 | plt.annotate(vnames[1].replace('_','\_') +' (' + units_lunits(uts[1]) + ') [' + \ |
---|
4583 | mincntS + ', ' + maxcntS + ']', xy=(0.55,0.04), xycoords='figure fraction', \ |
---|
4584 | color=coln) |
---|
4585 | |
---|
4586 | figname = '2Dfields_shadow-contour' |
---|
4587 | graphtit = vtit.replace('_','\_').replace('&','\&') |
---|
4588 | |
---|
4589 | plt.title(graphtit) |
---|
4590 | |
---|
4591 | output_kind(kfig, figname, True) |
---|
4592 | |
---|
4593 | return |
---|
4594 | |
---|
4595 | def dxdy_lonlat(dxv,dyv,ddx,ddy): |
---|
4596 | """ Function to provide lon/lat 2D lilke-matrices from any sort of dx,dy values |
---|
4597 | dxdy_lonlat(dxv,dyv,Lv,lv) |
---|
4598 | dx: values for the x |
---|
4599 | dy: values for the y |
---|
4600 | ddx: ',' list of which dimensions to use from values along x |
---|
4601 | ddy: ',' list of which dimensions to use from values along y |
---|
4602 | """ |
---|
4603 | |
---|
4604 | fname = 'dxdy_lonlat' |
---|
4605 | |
---|
4606 | if ddx.find(',') > -1: |
---|
4607 | dxk = 2 |
---|
4608 | ddxv = ddx.split(',') |
---|
4609 | ddxy = int(ddxv[0]) |
---|
4610 | ddxx = int(ddxv[1]) |
---|
4611 | else: |
---|
4612 | dxk = 1 |
---|
4613 | ddxy = int(ddx) |
---|
4614 | ddxx = int(ddx) |
---|
4615 | |
---|
4616 | if ddy.find(',') > -1: |
---|
4617 | dyk = 2 |
---|
4618 | ddyv = ddy.split(',') |
---|
4619 | ddyy = int(ddyv[0]) |
---|
4620 | ddyx = int(ddyv[1]) |
---|
4621 | else: |
---|
4622 | dyk = 1 |
---|
4623 | ddyy = int(ddy) |
---|
4624 | ddyx = int(ddy) |
---|
4625 | |
---|
4626 | ddxxv = dxv.shape[ddxx] |
---|
4627 | ddxyv = dxv.shape[ddxy] |
---|
4628 | ddyxv = dyv.shape[ddyx] |
---|
4629 | ddyyv = dyv.shape[ddyy] |
---|
4630 | |
---|
4631 | slicex = [] |
---|
4632 | if len(dxv.shape) > 1: |
---|
4633 | for idim in range(len(dxv.shape)): |
---|
4634 | if idim == ddxx or idim == ddxy: |
---|
4635 | slicex.append(slice(0,dxv.shape[idim])) |
---|
4636 | else: |
---|
4637 | slicex.append(0) |
---|
4638 | else: |
---|
4639 | slicex.append(slice(0,len(dxv))) |
---|
4640 | |
---|
4641 | slicey = [] |
---|
4642 | if len(dyv.shape) > 1: |
---|
4643 | for idim in range(len(dyv.shape)): |
---|
4644 | if idim == ddyx or idim == ddyy: |
---|
4645 | slicey.append(slice(0,dyv.shape[idim])) |
---|
4646 | else: |
---|
4647 | slicey.append(0) |
---|
4648 | else: |
---|
4649 | slicey.append(slice(0,len(dyv))) |
---|
4650 | |
---|
4651 | if dxk == 2 and dyk == 2: |
---|
4652 | if ddxxv != ddyxv: |
---|
4653 | print errormsg |
---|
4654 | print ' ' + fname + ': wrong dx dimensions! ddxx=',ddxxv,'ddyx=',ddyxv |
---|
4655 | print ' choose another for x:',dxv.shape,'or y:',dyv.shape |
---|
4656 | quit(-1) |
---|
4657 | if ddxyv != ddyyv: |
---|
4658 | print errormsg |
---|
4659 | print ' ' + fname + ': wrong dy dimensions! ddxy=',ddxyv,'ddyy=',ddyv |
---|
4660 | print ' choose another for x:',dxv.shape,'or y:',dyv.shape |
---|
4661 | quit(-1) |
---|
4662 | dx = ddxxv |
---|
4663 | dy = ddxyv |
---|
4664 | |
---|
4665 | print ' ' + fname + ': final dimension 2D lon/lat-like matrices:',dy,',',dx |
---|
4666 | lonv = np.zeros((dy,dx), dtype=np.float) |
---|
4667 | latv = np.zeros((dy,dx), dtype=np.float) |
---|
4668 | |
---|
4669 | |
---|
4670 | lonv = dxv[tuple(slicex)] |
---|
4671 | latv = dyv[tuple(slicey)] |
---|
4672 | |
---|
4673 | elif dxk == 2 and dyk == 1: |
---|
4674 | if not ddxxv == ddyxv and not ddxyv == ddyyv: |
---|
4675 | print errormsg |
---|
4676 | print ' ' + fname + ': wrong dimensions! ddxx=',ddxxv,'ddyx=',ddyxv, \ |
---|
4677 | 'ddyx=',ddyxv,'ddyy=',ddyyv |
---|
4678 | print ' choose another for x:',dxv.shape,'or y:',dyv.shape |
---|
4679 | quit(-1) |
---|
4680 | dx = ddxvv |
---|
4681 | dy = ddxyv |
---|
4682 | |
---|
4683 | print ' ' + fname + ': final dimension 2D lon/lat-like matrices:',dy,',',dx |
---|
4684 | lonv = np.zeros((dy,dx), dtype=np.float) |
---|
4685 | latv = np.zeros((dy,dx), dtype=np.float) |
---|
4686 | lonv = dxv[tuple(slicex)] |
---|
4687 | |
---|
4688 | if ddxxv == ddyxv: |
---|
4689 | for iy in range(dy): |
---|
4690 | latv[iy,:] = dyv[tuple(slicey)] |
---|
4691 | else: |
---|
4692 | for ix in range(dx): |
---|
4693 | latv[:,ix] = dyv[tuple(slicey)] |
---|
4694 | |
---|
4695 | elif dxk == 1 and dyk == 2: |
---|
4696 | if not ddxxv == ddyxv and not ddxyv == ddyyv: |
---|
4697 | print errormsg |
---|
4698 | print ' ' + fname + ': wrong dimensions! ddxx=',ddxxv,'ddyx=',ddyxv, \ |
---|
4699 | 'ddyx=',ddyxv,'ddyy=',ddyyv |
---|
4700 | print ' choose another for x:',dxv.shape,'or y:',dyv.shape |
---|
4701 | quit(-1) |
---|
4702 | dx = ddyxv |
---|
4703 | dy = ddyyv |
---|
4704 | |
---|
4705 | print ' ' + fname + ': final dimension 2D lon/lat-like matrices:',dy,',',dx |
---|
4706 | lonv = np.zeros((dy,dx), dtype=np.float) |
---|
4707 | latv = np.zeros((dy,dx), dtype=np.float) |
---|
4708 | |
---|
4709 | latv = dyv[tuple(slicey)] |
---|
4710 | |
---|
4711 | if ddyxv == ddxxv: |
---|
4712 | for iy in range(dy): |
---|
4713 | lonv[iy,:] = dxv[tuple(slicex)] |
---|
4714 | else: |
---|
4715 | for ix in range(dx): |
---|
4716 | lonv[:,ix] = dxv[tuple(slicex)] |
---|
4717 | |
---|
4718 | |
---|
4719 | elif dxk == 1 and dyk == 1: |
---|
4720 | dx = ddxxv |
---|
4721 | dy = ddyyv |
---|
4722 | |
---|
4723 | # print 'dx:',dx,'dy:',dy |
---|
4724 | |
---|
4725 | lonv = np.zeros((dy,dx), dtype=np.float) |
---|
4726 | latv = np.zeros((dy,dx), dtype=np.float) |
---|
4727 | |
---|
4728 | for iy in range(dy): |
---|
4729 | lonv[iy,:] = dxv[tuple(slicex)] |
---|
4730 | for ix in range(dx): |
---|
4731 | latv[:,ix] = dyv[tuple(slicey)] |
---|
4732 | |
---|
4733 | return lonv,latv |
---|
4734 | |
---|
4735 | def dxdy_lonlatDIMS(dxv,dyv,dnx,dny,dd): |
---|
4736 | """ Function to provide lon/lat 2D lilke-matrices from any sort of dx,dy values for a given |
---|
4737 | list of values |
---|
4738 | dxdy_lonlat(dxv,dyv,Lv,lv) |
---|
4739 | dxv: values for the x |
---|
4740 | dyv: values for the y |
---|
4741 | dnx: mnames of the dimensions for values on x |
---|
4742 | dny: mnames of the dimensions for values on y |
---|
4743 | dd: list of [dimname]|[val] for the dimensions use |
---|
4744 | [dimname]: name of the dimension |
---|
4745 | [val]: value (-1 for all the range) |
---|
4746 | """ |
---|
4747 | fname = 'dxdy_lonlatDIMS' |
---|
4748 | |
---|
4749 | print 'Lluis dd:',dd |
---|
4750 | |
---|
4751 | slicex = [] |
---|
4752 | ipos=0 |
---|
4753 | for dn in dnx: |
---|
4754 | for idd in range(len(dd)): |
---|
4755 | dname = dd[idd].split('|')[0] |
---|
4756 | dvalue = dd[idd].split('|')[1] |
---|
4757 | if dn == dname: |
---|
4758 | if dvalue.find('@') != -1: |
---|
4759 | slicex.append(slice(int(dvalue.split('@')[0]), \ |
---|
4760 | int(dvalue.split('@')[1]))) |
---|
4761 | else: |
---|
4762 | if int(dvalue) == -1: |
---|
4763 | slicex.append(slice(0,dxv.shape[ipos])) |
---|
4764 | elif int(dvalue) == -9: |
---|
4765 | slicex.append(dxv.shape[ipos]-1) |
---|
4766 | else: |
---|
4767 | slicex.append(int(dvalue)) |
---|
4768 | break |
---|
4769 | ipos = ipos + 1 |
---|
4770 | |
---|
4771 | slicey = [] |
---|
4772 | ipos=0 |
---|
4773 | for dn in dny: |
---|
4774 | for idd in range(len(dd)): |
---|
4775 | dname = dd[idd].split('|')[0] |
---|
4776 | dvalue = dd[idd].split('|')[1] |
---|
4777 | if dn == dname: |
---|
4778 | if dvalue.find('@') != -1: |
---|
4779 | slicey.append(slice(int(dvalue.split('@')[0]), \ |
---|
4780 | int(dvalue.split('@')[1]))) |
---|
4781 | else: |
---|
4782 | if int(dvalue) == -1: |
---|
4783 | slicey.append(slice(0,dyv.shape[ipos])) |
---|
4784 | elif int(dvalue) == -9: |
---|
4785 | slicey.append(dyv.shape[ipos]-1) |
---|
4786 | else: |
---|
4787 | slicey.append(int(dvalue)) |
---|
4788 | break |
---|
4789 | ipos = ipos + 1 |
---|
4790 | |
---|
4791 | lonv = dxv[tuple(slicex)] |
---|
4792 | latv = dyv[tuple(slicey)] |
---|
4793 | |
---|
4794 | if len(lonv.shape) != len(latv.shape): |
---|
4795 | print ' ' + fname + ': dimension size on x:', len(lonv.shape), 'and on y:', \ |
---|
4796 | len(latv.shape),'do not coincide!!' |
---|
4797 | quit(-1) |
---|
4798 | |
---|
4799 | return lonv,latv |
---|
4800 | |
---|
4801 | def plot_2D_shadow_line(varsv,varlv,vnames,vnamel,dimxv,dimyv,dimxu,dimyu,dimn, \ |
---|
4802 | colorbar,colln,vs,uts,utl,vtit,kfig,reva,mapv,ifclose): |
---|
4803 | """ Plotting a 2D field with shadows and another one with a line |
---|
4804 | varsv= 2D values to plot with shading |
---|
4805 | varlv= 1D values to plot with line |
---|
4806 | vnames= variable names for the shadow variable in the figure |
---|
4807 | vnamel= variable names for the line varibale in the figure |
---|
4808 | dim[x/y]v = values at the axes of x and y |
---|
4809 | dim[x/y]u = units at the axes of x and y |
---|
4810 | dimn= dimension names to plot |
---|
4811 | colorbar= name of the color bar to use |
---|
4812 | colln= color for the line |
---|
4813 | vs= minmum and maximum values to plot in shadow |
---|
4814 | uts= units of the variable to shadow |
---|
4815 | utl= units of the variable to line |
---|
4816 | vtit= title of the variable |
---|
4817 | kfig= kind of figure (jpg, pdf, png) |
---|
4818 | reva= |
---|
4819 | * 'transpose': reverse the axes (x-->y, y-->x) |
---|
4820 | * 'flip'@[x/y]: flip the axis x or y |
---|
4821 | mapv= map characteristics: [proj],[res] |
---|
4822 | see full documentation: http://matplotlib.org/basemap/ |
---|
4823 | [proj]: projection |
---|
4824 | * 'cyl', cilindric |
---|
4825 | * 'lcc', lambert conformal |
---|
4826 | [res]: resolution: |
---|
4827 | * 'c', crude |
---|
4828 | * 'l', low |
---|
4829 | * 'i', intermediate |
---|
4830 | * 'h', high |
---|
4831 | * 'f', full |
---|
4832 | ifclose= boolean value whether figure should be close (finish) or not |
---|
4833 | """ |
---|
4834 | ## import matplotlib as mpl |
---|
4835 | ## mpl.use('Agg') |
---|
4836 | ## import matplotlib.pyplot as plt |
---|
4837 | fname = 'plot_2D_shadow_line' |
---|
4838 | |
---|
4839 | if varsv == 'h': |
---|
4840 | print fname + '_____________________________________________________________' |
---|
4841 | print plot_2D_shadow_line.__doc__ |
---|
4842 | quit() |
---|
4843 | |
---|
4844 | if reva[0:4] == 'flip': |
---|
4845 | reva0 = 'flip' |
---|
4846 | if len(reva.split('@')) != 2: |
---|
4847 | print errormsg |
---|
4848 | print ' ' + fname + ': flip is given', reva, 'but not axis!' |
---|
4849 | quit(-1) |
---|
4850 | else: |
---|
4851 | reva0 = reva |
---|
4852 | |
---|
4853 | if reva0 == 'transpose': |
---|
4854 | print ' reversing the axes of the figure (x-->y, y-->x)!!' |
---|
4855 | varsv = np.transpose(varsv) |
---|
4856 | dxv = dimyv |
---|
4857 | dyv = dimxv |
---|
4858 | dimxv = dxv |
---|
4859 | dimyv = dyv |
---|
4860 | |
---|
4861 | if len(dimxv[:].shape) == 3: |
---|
4862 | lon0 = dimxv[0,] |
---|
4863 | elif len(dimxv[:].shape) == 2: |
---|
4864 | lon0 = dimxv[:] |
---|
4865 | |
---|
4866 | if len(dimyv[:].shape) == 3: |
---|
4867 | lat0 = dimyv[0,] |
---|
4868 | elif len(dimyv[:].shape) == 2: |
---|
4869 | lat0 = dimyv[:] |
---|
4870 | |
---|
4871 | if len(dimxv[:].shape) == 1 and len(dimyv[:].shape) == 1: |
---|
4872 | lon00 = dimxv[:] |
---|
4873 | lon0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float ) |
---|
4874 | |
---|
4875 | for iy in range(len(lat00)): |
---|
4876 | lon0[iy,:] = lon00 |
---|
4877 | for ix in range(len(lon00)): |
---|
4878 | lat0[:,ix] = lat00 |
---|
4879 | |
---|
4880 | if not mapv is None: |
---|
4881 | map_proj=mapv.split(',')[0] |
---|
4882 | map_res=mapv.split(',')[1] |
---|
4883 | |
---|
4884 | dx = lon0.shape[1] |
---|
4885 | dy = lat0.shape[0] |
---|
4886 | |
---|
4887 | nlon = lon0[0,0] |
---|
4888 | xlon = lon0[dy-1,dx-1] |
---|
4889 | nlat = lat0[0,0] |
---|
4890 | xlat = lat0[dy-1,dx-1] |
---|
4891 | |
---|
4892 | # Thats too much! :) |
---|
4893 | # if lonlatLims is not None: |
---|
4894 | # print ' ' + fname + ': cutting the domain to plot !!!!' |
---|
4895 | # plt.xlim(lonlatLims[0], lonlatLims[2]) |
---|
4896 | # plt.ylim(lonlatLims[1], lonlatLims[3]) |
---|
4897 | # print ' limits: W-E', lonlatLims[0], lonlatLims[2] |
---|
4898 | # print ' limits: N-S', lonlatLims[1], lonlatLims[3] |
---|
4899 | |
---|
4900 | # if map_proj == 'cyl': |
---|
4901 | # nlon = lonlatLims[0] |
---|
4902 | # nlat = lonlatLims[1] |
---|
4903 | # xlon = lonlatLims[2] |
---|
4904 | # xlat = lonlatLims[3] |
---|
4905 | # elif map_proj == 'lcc': |
---|
4906 | # lon2 = (lonlatLims[0] + lonlatLims[2])/2. |
---|
4907 | # lat2 = (lonlatLims[1] + lonlatLims[3])/2. |
---|
4908 | # nlon = lonlatLims[0] |
---|
4909 | # xlon = lonlatLims[2] |
---|
4910 | # nlat = lonlatLims[1] |
---|
4911 | # xlat = lonlatLims[3] |
---|
4912 | |
---|
4913 | lon2 = lon0[dy/2,dx/2] |
---|
4914 | lat2 = lat0[dy/2,dx/2] |
---|
4915 | |
---|
4916 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
4917 | xlon, ',', xlat |
---|
4918 | |
---|
4919 | if map_proj == 'cyl': |
---|
4920 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
4921 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
4922 | elif map_proj == 'lcc': |
---|
4923 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
4924 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
4925 | else: |
---|
4926 | print errormsg |
---|
4927 | print ' ' + fname + ": map projection '" + map_proj + "' not defined!!!" |
---|
4928 | print ' available: cyl, lcc' |
---|
4929 | quit(-1) |
---|
4930 | |
---|
4931 | if len(dimxv.shape) == 1: |
---|
4932 | lons, lats = np.meshgrid(dimxv, dimyv) |
---|
4933 | else: |
---|
4934 | if len(dimxv.shape) == 3: |
---|
4935 | lons = dimxv[0,:,:] |
---|
4936 | else: |
---|
4937 | lons = dimxv[:] |
---|
4938 | |
---|
4939 | if len(dimyv.shape) == 3: |
---|
4940 | lats = dimyv[0,:,:] |
---|
4941 | else: |
---|
4942 | lats = dimyv[:] |
---|
4943 | |
---|
4944 | x,y = m(lons,lats) |
---|
4945 | |
---|
4946 | else: |
---|
4947 | if len(dimxv.shape) == 3: |
---|
4948 | x = dimxv[0,:,:] |
---|
4949 | elif len(dimxv.shape) == 2: |
---|
4950 | x = dimxv |
---|
4951 | else: |
---|
4952 | # Attempt of simplier way... |
---|
4953 | # x = np.zeros((lon0.shape), dtype=np.float) |
---|
4954 | # for j in range(lon0.shape[0]): |
---|
4955 | # x[j,:] = dimxv |
---|
4956 | |
---|
4957 | ## This way is too complicated and maybe not necessary ? (assuming dimxv.shape == dimyv.shape) |
---|
4958 | if len(dimyv.shape) == 1: |
---|
4959 | x = np.zeros((len(dimyv),len(dimxv)), dtype=np.float) |
---|
4960 | for j in range(len(dimxv)): |
---|
4961 | x[j,:] = dimxv |
---|
4962 | else: |
---|
4963 | x = np.zeros((dimyv.shape), dtype=np.float) |
---|
4964 | if x.shape[0] == dimxv.shape[0]: |
---|
4965 | for j in range(x.shape[1]): |
---|
4966 | x[:,j] = dimxv |
---|
4967 | else: |
---|
4968 | for j in range(x.shape[0]): |
---|
4969 | x[j,:] = dimxv |
---|
4970 | |
---|
4971 | if len(dimyv.shape) == 3: |
---|
4972 | y = dimyv[0,:,:] |
---|
4973 | elif len(dimyv.shape) == 2: |
---|
4974 | y = dimyv |
---|
4975 | else: |
---|
4976 | # y = np.zeros((lat0.shape), dtype=np.float) |
---|
4977 | # for i in range(lat0.shape[1]): |
---|
4978 | # x[:,i] = dimyv |
---|
4979 | |
---|
4980 | # Idem |
---|
4981 | if len(dimxv.shape) == 1: |
---|
4982 | y = np.zeros((len(dimyv),len(dimxv)), dtype=np.float) |
---|
4983 | for i in range(len(dimxv)): |
---|
4984 | y[:,i] = dimyv |
---|
4985 | else: |
---|
4986 | y = np.zeros((dimxv.shape), dtype=np.float) |
---|
4987 | if y.shape[0] == dimyv.shape[0]: |
---|
4988 | for i in range(y.shape[1]): |
---|
4989 | y[:,i] = dimyv |
---|
4990 | else: |
---|
4991 | for j in range(y.shape[0]): |
---|
4992 | y[j,:] = dimyv |
---|
4993 | |
---|
4994 | plt.rc('text', usetex=True) |
---|
4995 | |
---|
4996 | plt.pcolormesh(x, y, varsv, cmap=plt.get_cmap(colorbar), vmin=vs[0], vmax=vs[1]) |
---|
4997 | cbar = plt.colorbar() |
---|
4998 | |
---|
4999 | if not mapv is None: |
---|
5000 | m.drawcoastlines() |
---|
5001 | |
---|
5002 | meridians = pretty_int(nlon,xlon,5) |
---|
5003 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
5004 | parallels = pretty_int(nlat,xlat,5) |
---|
5005 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
5006 | |
---|
5007 | plt.xlabel('W-E') |
---|
5008 | plt.ylabel('S-N') |
---|
5009 | else: |
---|
5010 | plt.xlabel(variables_values(dimn[1])[0] + ' (' + units_lunits(dimxu) + ')') |
---|
5011 | plt.ylabel(variables_values(dimn[0])[0] + ' (' + units_lunits(dimyu) + ')') |
---|
5012 | |
---|
5013 | # Line |
---|
5014 | ## |
---|
5015 | |
---|
5016 | if reva0 == 'flip' and reva.split('@')[1] == 'y': |
---|
5017 | b=-np.max(y[0,:])/np.max(varlv) |
---|
5018 | a=np.max(y[0,:]) |
---|
5019 | else: |
---|
5020 | b=np.max(y[0,:])/np.max(varlv) |
---|
5021 | a=0. |
---|
5022 | |
---|
5023 | newlinv = varlv*b+a |
---|
5024 | if reva0 == 'transpose': |
---|
5025 | plt.plot(newlinv, x[0,:], '-', color=colln, linewidth=2) |
---|
5026 | else: |
---|
5027 | plt.plot(x[0,:], newlinv, '-', color=colln, linewidth=2) |
---|
5028 | |
---|
5029 | txpos = pretty_int(x.min(),x.max(),10) |
---|
5030 | typos = pretty_int(y.min(),y.max(),10) |
---|
5031 | txlabels = list(txpos) |
---|
5032 | for i in range(len(txlabels)): txlabels[i] = str(txlabels[i]) |
---|
5033 | tylabels = list(typos) |
---|
5034 | for i in range(len(tylabels)): tylabels[i] = str(tylabels[i]) |
---|
5035 | |
---|
5036 | tllabels = pretty_int(np.min(varlv),np.max(varlv),len(txlabels)) |
---|
5037 | for it in range(len(tllabels)): |
---|
5038 | yval = (tllabels[it]*b+a) |
---|
5039 | plt.plot([x.max()*0.97, x.max()], [yval, yval], '-', color='k') |
---|
5040 | plt.annotate(tllabels[it], xy=(1.01,tllabels[it]/np.max(varlv)), \ |
---|
5041 | xycoords='axes fraction') |
---|
5042 | |
---|
5043 | # set the limits of the plot to the limits of the data |
---|
5044 | if reva0 == 'flip': |
---|
5045 | if reva.split('@')[1] == 'x': |
---|
5046 | plt.axis([x.max(), x.min(), y.min(), y.max()]) |
---|
5047 | else: |
---|
5048 | plt.axis([x.min(), x.max(), y.max(), y.min()]) |
---|
5049 | else: |
---|
5050 | plt.axis([x.min(), x.max(), y.min(), y.max()]) |
---|
5051 | |
---|
5052 | plt.tick_params(axis='y',right='off') |
---|
5053 | if mapv is None: |
---|
5054 | plt.xticks(txpos, txlabels) |
---|
5055 | plt.yticks(typos, tylabels) |
---|
5056 | |
---|
5057 | tllabels = pretty_int(np.min(varlv),np.max(varlv),len(txlabels)) |
---|
5058 | for it in range(len(tllabels)): |
---|
5059 | plt.annotate(tllabels[it], xy=(1.01,tllabels[it]/np.max(varlv)), xycoords='axes fraction') |
---|
5060 | |
---|
5061 | # units labels |
---|
5062 | cbar.set_label(vnames.replace('_','\_') + ' (' + units_lunits(uts) + ')') |
---|
5063 | |
---|
5064 | plt.annotate(vnamel +' (' + units_lunits(utl) + ')', xy=(0.75,0.04), |
---|
5065 | xycoords='figure fraction', color=colln) |
---|
5066 | figname = '2Dfields_shadow_line' |
---|
5067 | graphtit = vtit.replace('_','\_').replace('&','\&') |
---|
5068 | |
---|
5069 | plt.title(graphtit) |
---|
5070 | |
---|
5071 | output_kind(kfig, figname, ifclose) |
---|
5072 | |
---|
5073 | return |
---|
5074 | |
---|
5075 | def plot_Neighbourghood_evol(varsv, dxv, dyv, vnames, ttits, tpos, tlabels, colorbar, \ |
---|
5076 | Nng, vs, uts, gtit, kfig, ifclose): |
---|
5077 | """ Plotting neighbourghood evolution |
---|
5078 | varsv= 2D values to plot with shading |
---|
5079 | vnames= shading variable name for the figure |
---|
5080 | d[x/y]v= values at the axes of x and y |
---|
5081 | ttits= titles of both time axis |
---|
5082 | tpos= positions of the time ticks |
---|
5083 | tlabels= labels of the time ticks |
---|
5084 | colorbar= name of the color bar to use |
---|
5085 | Nng= Number of grid points of the full side of the box (odd value) |
---|
5086 | vs= minmum and maximum values to plot in shadow or: |
---|
5087 | 'Srange': for full range |
---|
5088 | 'Saroundmean@val': for mean-xtrm,mean+xtrm where xtrm = np.min(mean-min@val,max@val-mean) |
---|
5089 | 'Saroundminmax@val': for min*val,max*val |
---|
5090 | 'Saroundpercentile@val': for median-xtrm,median+xtrm where xtrm = np.min(median-percentile_(val), |
---|
5091 | percentile_(100-val)-median) |
---|
5092 | 'Smean@val': for -xtrm,xtrm where xtrm = np.min(mean-min*@val,max*@val-mean) |
---|
5093 | 'Smedian@val': for -xtrm,xtrm where xtrm = np.min(median-min@val,max@val-median) |
---|
5094 | 'Spercentile@val': for -xtrm,xtrm where xtrm = np.min(median-percentile_(val), |
---|
5095 | percentile_(100-val)-median) |
---|
5096 | uts= units of the variable to shadow |
---|
5097 | gtit= title of the graph |
---|
5098 | kfig= kind of figure (jpg, pdf, png) |
---|
5099 | ifclose= boolean value whether figure should be close (finish) or not |
---|
5100 | """ |
---|
5101 | import numpy.ma as ma |
---|
5102 | |
---|
5103 | fname = 'plot_Neighbourghood_evol' |
---|
5104 | |
---|
5105 | if varsv == 'h': |
---|
5106 | print fname + '_____________________________________________________________' |
---|
5107 | print plot_Neighbourghood_evol.__doc__ |
---|
5108 | quit() |
---|
5109 | |
---|
5110 | if len(varsv.shape) != 2: |
---|
5111 | print errormsg |
---|
5112 | print ' ' + fname + ': wrong number of dimensions of the values: ', \ |
---|
5113 | varsv.shape |
---|
5114 | quit(-1) |
---|
5115 | |
---|
5116 | varsvmask = ma.masked_equal(varsv,fillValue) |
---|
5117 | |
---|
5118 | vsend = np.zeros((2), dtype=np.float) |
---|
5119 | # Changing limits of the colors |
---|
5120 | if type(vs[0]) != type(np.float(1.)): |
---|
5121 | if vs[0] == 'Srange': |
---|
5122 | vsend[0] = np.min(varsvmask) |
---|
5123 | elif vs[0][0:11] == 'Saroundmean': |
---|
5124 | meanv = np.mean(varsvmask) |
---|
5125 | permean = np.float(vs[0].split('@')[1]) |
---|
5126 | minv = np.min(varsvmask)*permean |
---|
5127 | maxv = np.max(varsvmask)*permean |
---|
5128 | minextrm = np.min([np.abs(meanv-minv), np.abs(maxv-meanv)]) |
---|
5129 | vsend[0] = meanv-minextrm |
---|
5130 | vsend[1] = meanv+minextrm |
---|
5131 | elif vs[0][0:13] == 'Saroundminmax': |
---|
5132 | permean = np.float(vs[0].split('@')[1]) |
---|
5133 | minv = np.min(varsvmask)*permean |
---|
5134 | maxv = np.max(varsvmask)*permean |
---|
5135 | vsend[0] = minv |
---|
5136 | vsend[1] = maxv |
---|
5137 | elif vs[0][0:17] == 'Saroundpercentile': |
---|
5138 | medianv = np.median(varsvmask) |
---|
5139 | valper = np.float(vs[0].split('@')[1]) |
---|
5140 | minv = np.percentile(varsvmask, valper) |
---|
5141 | maxv = np.percentile(varsvmask, 100.-valper) |
---|
5142 | minextrm = np.min([np.abs(medianv-minv), np.abs(maxv-medianv)]) |
---|
5143 | vsend[0] = medianv-minextrm |
---|
5144 | vsend[1] = medianv+minextrm |
---|
5145 | elif vs[0][0:5] == 'Smean': |
---|
5146 | meanv = np.mean(varsvmask) |
---|
5147 | permean = np.float(vs[0].split('@')[1]) |
---|
5148 | minv = np.min(varsvmask)*permean |
---|
5149 | maxv = np.max(varsvmask)*permean |
---|
5150 | minextrm = np.min([np.abs(meanv-minv), np.abs(maxv-meanv)]) |
---|
5151 | vsend[0] = -minextrm |
---|
5152 | vsend[1] = minextrm |
---|
5153 | elif vs[0][0:7] == 'Smedian': |
---|
5154 | medianv = np.median(varsvmask) |
---|
5155 | permedian = np.float(vs[0].split('@')[1]) |
---|
5156 | minv = np.min(varsvmask)*permedian |
---|
5157 | maxv = np.max(varsvmask)*permedian |
---|
5158 | minextrm = np.min([np.abs(medianv-minv), np.abs(maxv-medianv)]) |
---|
5159 | vsend[0] = -minextrm |
---|
5160 | vsend[1] = minextrm |
---|
5161 | elif vs[0][0:11] == 'Spercentile': |
---|
5162 | medianv = np.median(varsvmask) |
---|
5163 | valper = np.float(vs[0].split('@')[1]) |
---|
5164 | minv = np.percentile(varsvmask, valper) |
---|
5165 | maxv = np.percentile(varsvmask, 100.-valper) |
---|
5166 | minextrm = np.min([np.abs(medianv-minv), np.abs(maxv-medianv)]) |
---|
5167 | vsend[0] = -minextrm |
---|
5168 | vsend[1] = minextrm |
---|
5169 | else: |
---|
5170 | print errormsg |
---|
5171 | print ' ' + fname + ": range '" + vs[0] + "' not ready!!!" |
---|
5172 | quit(-1) |
---|
5173 | print ' ' + fname + ': modified shadow min,max:',vsend |
---|
5174 | else: |
---|
5175 | vsend[0] = vs[0] |
---|
5176 | |
---|
5177 | if type(vs[0]) != type(np.float(1.)): |
---|
5178 | if vs[1] == 'range': |
---|
5179 | vsend[1] = np.max(varsv) |
---|
5180 | else: |
---|
5181 | vsend[1] = vs[1] |
---|
5182 | |
---|
5183 | plt.rc('text', usetex=True) |
---|
5184 | |
---|
5185 | # plt.pcolormesh(dxv, dyv, varsv, cmap=plt.get_cmap(colorbar), vmin=vsend[0], vmax=vsend[1]) |
---|
5186 | plt.pcolormesh(varsvmask, cmap=plt.get_cmap(colorbar), vmin=vsend[0], vmax=vsend[1]) |
---|
5187 | cbar = plt.colorbar() |
---|
5188 | |
---|
5189 | newtposx = (tpos[0][:] - np.min(dxv)) * len(dxv) * Nng / (np.max(dxv) - np.min(dxv)) |
---|
5190 | newtposy = (tpos[1][:] - np.min(dyv)) * len(dyv) * Nng / (np.max(dyv) - np.min(dyv)) |
---|
5191 | |
---|
5192 | plt.xticks(newtposx, tlabels[0]) |
---|
5193 | plt.yticks(newtposy, tlabels[1]) |
---|
5194 | plt.xlabel(ttits[0]) |
---|
5195 | plt.ylabel(ttits[1]) |
---|
5196 | |
---|
5197 | plt.axes().set_aspect('equal') |
---|
5198 | # From: http://stackoverflow.com/questions/14406214/moving-x-axis-to-the-top-of-a-plot-in-matplotlib |
---|
5199 | plt.axes().xaxis.tick_top |
---|
5200 | plt.axes().xaxis.set_ticks_position('top') |
---|
5201 | |
---|
5202 | # units labels |
---|
5203 | cbar.set_label(vnames.replace('_','\_') + ' (' + units_lunits(uts) + ')') |
---|
5204 | |
---|
5205 | figname = 'Neighbourghood_evol' |
---|
5206 | graphtit = gtit.replace('_','\_').replace('&','\&') |
---|
5207 | |
---|
5208 | plt.title(graphtit, position=(0.5,1.05)) |
---|
5209 | |
---|
5210 | output_kind(kfig, figname, ifclose) |
---|
5211 | |
---|
5212 | return |
---|
5213 | |
---|
5214 | def plot_lines(vardv, varvv, vaxis, dtit, linesn, vtit, vunit, gtit, gloc, kfig): |
---|
5215 | """ Function to plot a collection of lines |
---|
5216 | vardv= list of set of dimension values |
---|
5217 | varvv= list of set of values |
---|
5218 | vaxis= which axis will be used for the values ('x', or 'y') |
---|
5219 | dtit= title for the common dimension |
---|
5220 | linesn= names for the legend |
---|
5221 | vtit= title for the vaxis |
---|
5222 | vunit= units of the vaxis |
---|
5223 | gtit= main title |
---|
5224 | gloc= location of the legend (0, autmoatic) |
---|
5225 | 1: 'upper right', 2: 'upper left', 3: 'lower left', 4: 'lower right', |
---|
5226 | 5: 'right', 6: 'center left', 7: 'center right', 8: 'lower center', |
---|
5227 | 9: 'upper center', 10: 'center' |
---|
5228 | kfig= kind of figure |
---|
5229 | plot_lines([np.arange(10)], [np.sin(np.arange(10)*np.pi/2.5)], 'y', 'time (s)', \ |
---|
5230 | ['2.5'], 'sin', '-', 'sinus frequency dependency', 'pdf') |
---|
5231 | """ |
---|
5232 | fname = 'plot_lines' |
---|
5233 | |
---|
5234 | if vardv == 'h': |
---|
5235 | print fname + '_____________________________________________________________' |
---|
5236 | print plot_lines.__doc__ |
---|
5237 | quit() |
---|
5238 | |
---|
5239 | # Canging line kinds every 7 lines (end of standard colors) |
---|
5240 | linekinds=['.-','x-','o-'] |
---|
5241 | |
---|
5242 | Ntraj = len(vardv) |
---|
5243 | |
---|
5244 | N7lines = 0 |
---|
5245 | |
---|
5246 | xmin = 100000. |
---|
5247 | xmax = -100000. |
---|
5248 | ymin = 100000. |
---|
5249 | ymax = -100000. |
---|
5250 | for il in range(Ntraj): |
---|
5251 | minv = np.min(varvv[il]) |
---|
5252 | maxv = np.max(varvv[il]) |
---|
5253 | mind = np.min(vardv[il]) |
---|
5254 | maxd = np.max(vardv[il]) |
---|
5255 | |
---|
5256 | if minv < xmin: xmin = minv |
---|
5257 | if maxv > xmax: xmax = maxv |
---|
5258 | if mind < ymin: ymin = mind |
---|
5259 | if maxd > ymax: ymax = maxd |
---|
5260 | |
---|
5261 | print 'x:',xmin,',',xmax,'y:',ymin,ymax |
---|
5262 | |
---|
5263 | plt.rc('text', usetex=True) |
---|
5264 | |
---|
5265 | if vaxis == 'x': |
---|
5266 | for il in range(Ntraj): |
---|
5267 | plt.plot(varvv[il], vardv[il], linekinds[N7lines], label= linesn[il]) |
---|
5268 | if il == 6: N7lines = N7lines + 1 |
---|
5269 | |
---|
5270 | plt.xlabel(vtit + ' (' + vunit + ')') |
---|
5271 | plt.ylabel(dtit) |
---|
5272 | plt.xlim(xmin,xmax) |
---|
5273 | plt.ylim(ymin,ymax) |
---|
5274 | |
---|
5275 | else: |
---|
5276 | for il in range(Ntraj): |
---|
5277 | plt.plot(vardv[il], varvv[il], linekinds[N7lines], label= linesn[il]) |
---|
5278 | if il == 6: N7lines = N7lines + 1 |
---|
5279 | |
---|
5280 | plt.xlabel(dtit) |
---|
5281 | plt.ylabel(vtit + ' (' + vunit + ')') |
---|
5282 | |
---|
5283 | plt.xlim(ymin,ymax) |
---|
5284 | plt.ylim(xmin,xmax) |
---|
5285 | |
---|
5286 | figname = 'lines' |
---|
5287 | graphtit = gtit.replace('_','\_').replace('&','\&') |
---|
5288 | |
---|
5289 | plt.title(graphtit) |
---|
5290 | plt.legend(loc=gloc) |
---|
5291 | |
---|
5292 | output_kind(kfig, figname, True) |
---|
5293 | |
---|
5294 | return |
---|
5295 | |
---|
5296 | def plot_lines_time(vardv, varvv, vaxis, dtit, linesn0, vtit, vunit, tpos, tlabs, \ |
---|
5297 | gtit, gloc, kfig, coll, ptl): |
---|
5298 | """ Function to plot a collection of lines with a time axis |
---|
5299 | vardv= list of set of dimension values |
---|
5300 | varvv= list of set of values |
---|
5301 | vaxis= which axis will be used for the time values ('x', or 'y') |
---|
5302 | dtit= title for the common dimension |
---|
5303 | linesn= names for the legend (None, no legend) |
---|
5304 | vtit= title for the vaxis |
---|
5305 | vunit= units of the vaxis |
---|
5306 | tpos= positions of the time ticks |
---|
5307 | tlabs= labels of the time ticks |
---|
5308 | gtit= main title |
---|
5309 | gloc= location of the legend (0, autmoatic) |
---|
5310 | 1: 'upper right', 2: 'upper left', 3: 'lower left', 4: 'lower right', |
---|
5311 | 5: 'right', 6: 'center left', 7: 'center right', 8: 'lower center', |
---|
5312 | 9: 'upper center', 10: 'center' |
---|
5313 | kfig= kind of figure |
---|
5314 | coll= ',' list of colors for the lines or None for automatic |
---|
5315 | coll= ',' list of colors for the lines, None for automatic, single |
---|
5316 | value all the same |
---|
5317 | ptl= ',' list of type of points for the lines, None for automatic, single |
---|
5318 | value all the same |
---|
5319 | |
---|
5320 | plot_lines([np.arange(10)], [np.sin(np.arange(10)*np.pi/2.5)], 'y', 'time (s)', \ |
---|
5321 | ['2.5'], 'sin', '-', 'sinus frequency dependency', 'pdf') |
---|
5322 | """ |
---|
5323 | fname = 'plot_lines' |
---|
5324 | |
---|
5325 | if vardv == 'h': |
---|
5326 | print fname + '_____________________________________________________________' |
---|
5327 | print plot_lines.__doc__ |
---|
5328 | quit() |
---|
5329 | |
---|
5330 | # Canging line kinds every 7 lines (end of standard colors) |
---|
5331 | linekinds = [] |
---|
5332 | if ptl is None: |
---|
5333 | linekindsauto=['.-','x-','o-'] |
---|
5334 | for ptype in range(4): |
---|
5335 | for ip in range(7): |
---|
5336 | linekinds.append(linekindsauto[ptype]) |
---|
5337 | else: |
---|
5338 | linekinds = ptl |
---|
5339 | |
---|
5340 | Ntraj = len(vardv) |
---|
5341 | |
---|
5342 | N7lines = 0 |
---|
5343 | |
---|
5344 | plt.rc('text', usetex=True) |
---|
5345 | xtrmvv = [fillValueF,-fillValueF] |
---|
5346 | xtrmdv = [fillValueF,-fillValueF] |
---|
5347 | |
---|
5348 | # Do we have legend? |
---|
5349 | ## |
---|
5350 | if linesn0 is None: |
---|
5351 | linesn = [] |
---|
5352 | for itrj in range(Ntraj): |
---|
5353 | linesn.append(str(itrj)) |
---|
5354 | else: |
---|
5355 | linesn = linesn0 |
---|
5356 | |
---|
5357 | if vaxis == 'x': |
---|
5358 | for il in range(Ntraj): |
---|
5359 | if coll is None: |
---|
5360 | plt.plot(varvv[il], vardv[il], linekinds[il], label= linesn[il]) |
---|
5361 | else: |
---|
5362 | plt.plot(varvv[il], vardv[il], linekinds[il], label= linesn[il],\ |
---|
5363 | color=coll[il]) |
---|
5364 | |
---|
5365 | minvv = np.min(varvv[il]) |
---|
5366 | maxvv = np.max(varvv[il]) |
---|
5367 | mindv = np.min(vardv[il]) |
---|
5368 | maxdv = np.max(vardv[il]) |
---|
5369 | |
---|
5370 | if minvv < xtrmvv[0]: xtrmvv[0] = minvv |
---|
5371 | if maxvv > xtrmvv[1]: xtrmvv[1] = maxvv |
---|
5372 | if mindv < xtrmdv[0]: xtrmdv[0] = mindv |
---|
5373 | if maxdv > xtrmdv[1]: xtrmdv[1] = maxdv |
---|
5374 | |
---|
5375 | plt.xlabel(vtit + ' (' + vunit + ')') |
---|
5376 | plt.ylabel(dtit) |
---|
5377 | # plt.xlim(np.min(varTvv),np.max(varTvv)) |
---|
5378 | # plt.ylim(np.min(varTdv),np.max(varTdv)) |
---|
5379 | plt.xlim(xtrmvv[0],xtrmvv[1]) |
---|
5380 | plt.ylim(xtrmdv[0],xtrmdv[1]) |
---|
5381 | |
---|
5382 | plt.yticks(tpos, tlabs) |
---|
5383 | else: |
---|
5384 | for il in range(Ntraj): |
---|
5385 | if coll is None: |
---|
5386 | plt.plot(vardv[il], varvv[il], linekinds[il], label= linesn[il]) |
---|
5387 | else: |
---|
5388 | plt.plot(vardv[il], varvv[il], linekinds[il], label= linesn[il],\ |
---|
5389 | color=coll[il]) |
---|
5390 | |
---|
5391 | minvv = np.min(varvv[il]) |
---|
5392 | maxvv = np.max(varvv[il]) |
---|
5393 | mindv = np.min(vardv[il]) |
---|
5394 | maxdv = np.max(vardv[il]) |
---|
5395 | |
---|
5396 | if minvv < xtrmvv[0]: xtrmvv[0] = minvv |
---|
5397 | if maxvv > xtrmvv[1]: xtrmvv[1] = maxvv |
---|
5398 | if mindv < xtrmdv[0]: xtrmdv[0] = mindv |
---|
5399 | if maxdv > xtrmdv[1]: xtrmdv[1] = maxdv |
---|
5400 | |
---|
5401 | plt.xlabel(dtit) |
---|
5402 | plt.ylabel(vtit + ' (' + vunit + ')') |
---|
5403 | |
---|
5404 | plt.xlim(xtrmdv[0],xtrmdv[1]) |
---|
5405 | plt.ylim(xtrmvv[0],xtrmvv[1]) |
---|
5406 | |
---|
5407 | # plt.xlim(np.min(varTdv),np.max(varTdv)) |
---|
5408 | # plt.ylim(np.min(varTvv),np.max(varTvv)) |
---|
5409 | plt.xticks(tpos, tlabs) |
---|
5410 | |
---|
5411 | figname = 'lines_time' |
---|
5412 | graphtit = gtit.replace('_','\_').replace('&','\&') |
---|
5413 | |
---|
5414 | plt.title(graphtit) |
---|
5415 | if linesn0 is not None: |
---|
5416 | plt.legend(loc=gloc) |
---|
5417 | |
---|
5418 | print plt.xlim(),':', plt.ylim() |
---|
5419 | |
---|
5420 | output_kind(kfig, figname, True) |
---|
5421 | |
---|
5422 | return |
---|
5423 | |
---|
5424 | def plot_barbs(xvals,yvals,uvals,vvals,vecfreq,veccolor,veclength,windn,wuts,mapv,graphtit,kfig,figname): |
---|
5425 | """ Function to plot wind barbs |
---|
5426 | xvals= values for the 'x-axis' |
---|
5427 | yvals= values for the 'y-axis' |
---|
5428 | vecfreq= [xfreq],[yfreq] frequency of values allong each axis (None, all grid points; |
---|
5429 | 'auto', computed automatically to have 20 vectors along each axis) |
---|
5430 | veccolor= color of the vectors (None, for 'red') |
---|
5431 | veclength= length of the wind barbs (None, for 9) |
---|
5432 | windn= name of the wind variable in the graph |
---|
5433 | wuts= units of the wind variable in the graph |
---|
5434 | mapv= map characteristics: [proj],[res] |
---|
5435 | see full documentation: http://matplotlib.org/basemap/ |
---|
5436 | [proj]: projection |
---|
5437 | * 'cyl', cilindric |
---|
5438 | * 'lcc', lambert conformal |
---|
5439 | [res]: resolution: |
---|
5440 | * 'c', crude |
---|
5441 | * 'l', low |
---|
5442 | * 'i', intermediate |
---|
5443 | * 'h', high |
---|
5444 | * 'f', full |
---|
5445 | graphtit= title of the graph ('|', for spaces) |
---|
5446 | kfig= kind of figure |
---|
5447 | figname= name of the figure |
---|
5448 | """ |
---|
5449 | fname = 'plot_barbs' |
---|
5450 | |
---|
5451 | dx=xvals.shape[1] |
---|
5452 | dy=xvals.shape[0] |
---|
5453 | |
---|
5454 | # Frequency of vectors |
---|
5455 | if vecfreq is None: |
---|
5456 | xfreq = 1 |
---|
5457 | yfreq = 1 |
---|
5458 | elif vecfreq == 'auto': |
---|
5459 | xfreq = dx/20 |
---|
5460 | yfreq = dy/20 |
---|
5461 | else: |
---|
5462 | xfreq=int(vecfreq.split('@')[0]) |
---|
5463 | yfreq=int(vecfreq.split('@')[1]) |
---|
5464 | |
---|
5465 | if veccolor == 'auto': |
---|
5466 | vcolor = "red" |
---|
5467 | else: |
---|
5468 | vcolor = veccolor |
---|
5469 | |
---|
5470 | if veclength == 'auto': |
---|
5471 | vlength = 9 |
---|
5472 | else: |
---|
5473 | vlength = veclength |
---|
5474 | |
---|
5475 | plt.rc('text', usetex=True) |
---|
5476 | |
---|
5477 | if not mapv is None: |
---|
5478 | lon00 = np.where(xvals[:] < 0., 360. + xvals[:], xvals[:]) |
---|
5479 | lat00 = yvals[:] |
---|
5480 | |
---|
5481 | map_proj=mapv.split(',')[0] |
---|
5482 | map_res=mapv.split(',')[1] |
---|
5483 | |
---|
5484 | nlon = np.min(xvals[::yfreq,::xfreq]) |
---|
5485 | xlon = np.max(xvals[::yfreq,::xfreq]) |
---|
5486 | nlat = np.min(yvals[::yfreq,::xfreq]) |
---|
5487 | xlat = np.max(yvals[::yfreq,::xfreq]) |
---|
5488 | |
---|
5489 | lon2 = xvals[dy/2,dx/2] |
---|
5490 | lat2 = yvals[dy/2,dx/2] |
---|
5491 | |
---|
5492 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
5493 | xlon, ',', xlat |
---|
5494 | |
---|
5495 | if map_proj == 'cyl': |
---|
5496 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
5497 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
5498 | elif map_proj == 'lcc': |
---|
5499 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
5500 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
5501 | else: |
---|
5502 | print errormsg |
---|
5503 | print ' ' + fname + ": projection '" + map_proj + "' not ready!!" |
---|
5504 | print ' projections available: cyl, lcc' |
---|
5505 | quit(-1) |
---|
5506 | |
---|
5507 | m.drawcoastlines() |
---|
5508 | |
---|
5509 | meridians = pretty_int(nlon,xlon,5) |
---|
5510 | m.drawmeridians(meridians,labels=[True,False,False,True],color="black") |
---|
5511 | |
---|
5512 | parallels = pretty_int(nlat,xlat,5) |
---|
5513 | m.drawparallels(parallels,labels=[False,True,True,False],color="black") |
---|
5514 | |
---|
5515 | plt.xlabel('W-E') |
---|
5516 | plt.ylabel('S-N') |
---|
5517 | |
---|
5518 | plt.barbs(xvals[::yfreq,::xfreq], yvals[::yfreq,::xfreq], uvals[::yfreq,::xfreq],\ |
---|
5519 | vvals[::yfreq,::xfreq], color=vcolor, pivot='tip') |
---|
5520 | |
---|
5521 | plt.annotate(windn.replace('_','\_') +' (' + units_lunits(wuts) + ')', \ |
---|
5522 | xy=(0.85,-0.10), xycoords='axes fraction', color=vcolor) |
---|
5523 | |
---|
5524 | plt.title(graphtit.replace('|',' ').replace('&','\&')) |
---|
5525 | |
---|
5526 | ## NOT WORKING ## |
---|
5527 | |
---|
5528 | # No legend so it is imposed |
---|
5529 | ## windlabel=windn.replace('_','\_') +' (' + units_lunits(wuts[1]) + ')' |
---|
5530 | ## vecpatch = mpatches.Patch(color=vcolor, label=windlabel) |
---|
5531 | |
---|
5532 | ## plt.legend(handles=[vecpatch]) |
---|
5533 | |
---|
5534 | ## vecline = mlines.Line2D([], [], color=vcolor, marker='.', markersize=10, label=windlabel) |
---|
5535 | ## plt.legend(handles=[vecline], loc=1) |
---|
5536 | |
---|
5537 | output_kind(kfig, figname, True) |
---|
5538 | |
---|
5539 | return |
---|
5540 | |
---|
5541 | def plot_ptZvals(vname,vunits,points,ptype,ptsize,graphlims,minmax,figtitle,cbar, \ |
---|
5542 | mapv,kfig): |
---|
5543 | """ Function to plot a given list of points and values |
---|
5544 | vname= name of the variable in the graph |
---|
5545 | vunits= units of the variable |
---|
5546 | points= [lon,lat,val] matrix of values |
---|
5547 | ptype= type of the point |
---|
5548 | ptsize= size of the point |
---|
5549 | graphlims= minLON,minLAT,maxLON,maxLAT limits of the graph, None for the full size |
---|
5550 | minmax= minimum and maximum type |
---|
5551 | 'auto': values taken from the extrems of the data |
---|
5552 | [min],[max]: given minimum and maximum values |
---|
5553 | figtitle= title of the figure |
---|
5554 | cbar= color bar |
---|
5555 | mapv= map characteristics: [proj],[res] |
---|
5556 | see full documentation: http://matplotlib.org/basemap/ |
---|
5557 | [proj]: projection |
---|
5558 | * 'cyl', cilindric |
---|
5559 | * 'lcc', lambert-conformal |
---|
5560 | [res]: resolution: |
---|
5561 | * 'c', crude |
---|
5562 | * 'l', low |
---|
5563 | * 'i', intermediate |
---|
5564 | * 'h', high |
---|
5565 | * 'f', full |
---|
5566 | kfig= kind of figure |
---|
5567 | """ |
---|
5568 | fname = 'plot_ptZvals' |
---|
5569 | |
---|
5570 | figname = 'pointsZval' |
---|
5571 | |
---|
5572 | minlon = points[:,0].min() |
---|
5573 | maxlon = points[:,0].max() |
---|
5574 | |
---|
5575 | minlat = points[:,1].min() |
---|
5576 | maxlat = points[:,1].max() |
---|
5577 | |
---|
5578 | minval = points[:,2].min() |
---|
5579 | maxval = points[:,2].max() |
---|
5580 | |
---|
5581 | # print 'min/max val;',minval,maxval |
---|
5582 | |
---|
5583 | lonrange = (points[:,0] - minlon)/(maxlon - minlon) |
---|
5584 | latrange = (points[:,1] - minlat)/(maxlat - minlat) |
---|
5585 | colorrange = (points[:,2] - minval)/(maxval - minval) |
---|
5586 | |
---|
5587 | plt.rc('text', usetex=True) |
---|
5588 | |
---|
5589 | if mapv is not None: |
---|
5590 | vlon = points[:,0] |
---|
5591 | vlat = points[:,1] |
---|
5592 | dx = len(vlon) |
---|
5593 | dy = len(vlat) |
---|
5594 | |
---|
5595 | # vlon = np.where(vlon[:] < 0., 360. + vlon[:], vlon[:]) |
---|
5596 | # xvala = np.array(xval) |
---|
5597 | # xvala = np.where(xvala < 0., 360. + xvala, xvala) |
---|
5598 | # xval = list(xvala) |
---|
5599 | |
---|
5600 | map_proj=mapv.split(',')[0] |
---|
5601 | map_res=mapv.split(',')[1] |
---|
5602 | |
---|
5603 | if graphlims is not None: |
---|
5604 | nlon = graphlims[0] |
---|
5605 | xlon = graphlims[2] |
---|
5606 | nlat = graphlims[1] |
---|
5607 | xlat = graphlims[3] |
---|
5608 | else: |
---|
5609 | nlon = np.min(vlon) |
---|
5610 | xlon = np.max(vlon) |
---|
5611 | nlat = np.min(vlat) |
---|
5612 | xlat = np.max(vlat) |
---|
5613 | |
---|
5614 | lon2 = vlon[dy/2] |
---|
5615 | lat2 = vlat[dy/2] |
---|
5616 | |
---|
5617 | print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:', \ |
---|
5618 | xlon, ',', xlat |
---|
5619 | |
---|
5620 | if map_proj == 'cyl': |
---|
5621 | m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat, \ |
---|
5622 | urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
5623 | elif map_proj == 'lcc': |
---|
5624 | m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \ |
---|
5625 | llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res) |
---|
5626 | else: |
---|
5627 | print errormsg |
---|
5628 | print ' ' + fname + ": map projecion '" + map_proj + "' not ready!!" |
---|
5629 | print ' available: cyl, lcc' |
---|
5630 | quit(-1) |
---|
5631 | |
---|
5632 | # lons, lats = np.meshgrid(vlon, vlat) |
---|
5633 | # lons = np.where(lons < 0., lons + 360., lons) |
---|
5634 | |
---|
5635 | x,y = m(vlon,vlat) |
---|
5636 | |
---|
5637 | m.drawcoastlines() |
---|
5638 | |
---|
5639 | meridians = pretty_int(nlon,xlon,5) |
---|
5640 | m.drawmeridians(meridians,labels=[True,False,False,True]) |
---|
5641 | |
---|
5642 | parallels = pretty_int(nlat,xlat,5) |
---|
5643 | m.drawparallels(parallels,labels=[False,True,True,False]) |
---|
5644 | # else: |
---|
5645 | # x = vlon |
---|
5646 | # y = vlat |
---|
5647 | # plt.xlim(0,dx-1) |
---|
5648 | # plt.ylim(0,dy-1) |
---|
5649 | |
---|
5650 | if minmax == 'auto': |
---|
5651 | plt.scatter(points[:,0], points[:,1], c=points[:,2], s=ptsize, cmap=cbar, \ |
---|
5652 | marker=ptype) |
---|
5653 | else: |
---|
5654 | minv = np.float(minmax.split(',')[0]) |
---|
5655 | maxv = np.float(minmax.split(',')[1]) |
---|
5656 | |
---|
5657 | plt.scatter(points[:,0], points[:,1], c=points[:,2], s=ptsize, cmap=cbar, \ |
---|
5658 | marker=ptype, vmin=minv, vmax=maxv) |
---|
5659 | |
---|
5660 | cbar = plt.colorbar() |
---|
5661 | cbar.set_label(vname.replace('_','\_') +' ('+ units_lunits(vunits) + ')') |
---|
5662 | |
---|
5663 | plt.title(figtitle) |
---|
5664 | if graphlims is not None: |
---|
5665 | plt.xlim(graphlims[0], graphlims[2]) |
---|
5666 | plt.ylim(graphlims[1], graphlims[3]) |
---|
5667 | |
---|
5668 | output_kind(kfig, figname, True) |
---|
5669 | |
---|
5670 | return |
---|
5671 | |
---|
5672 | #pts = np.zeros((10,3), dtype=np.float) |
---|
5673 | #pts[:,0] = np.arange(10,20)*1. |
---|
5674 | #pts[:,1] = np.arange(30,40)*1. |
---|
5675 | #pts[:,2] = np.arange(-5,5)*1. |
---|
5676 | |
---|
5677 | #plot_ptZvals('vals','kgm-2',pts,'.',300, 'values of values', 'seismic', 'cyl,l', 'pdf') |
---|
5678 | |
---|
5679 | def plot_ZQradii(Zmeans, graphtit, kfig, figname): |
---|
5680 | """ Function to plot following radial averages only at exact grid poins |
---|
5681 | Zmeans= radial means |
---|
5682 | radii= values of the taken radii |
---|
5683 | graphtit= title of the graph ('|', for spaces) |
---|
5684 | kfig= kind of figure |
---|
5685 | figname= name of the figure |
---|
5686 | """ |
---|
5687 | |
---|
5688 | fname = 'plot_ZQradii' |
---|
5689 | |
---|
5690 | output_kind(kfig, figname, True) |
---|
5691 | |
---|
5692 | return |
---|