1 | # -*- coding: iso-8859-15 -*- |
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2 | # Generic program to transfrom ASCII observational data in columns to a netcdf |
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3 | # L. Fita, LMD February 2015 |
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4 | ## e.g. # create_OBSnetcdf.py -c '#' -d ACAR/description.dat -e space -f ACAR/2012/10/ACAR_121018.asc -g true -t 19491201000000,seconds -k trajectory |
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5 | |
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6 | import numpy as np |
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7 | from netCDF4 import Dataset as NetCDFFile |
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8 | import os |
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9 | import re |
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10 | from optparse import OptionParser |
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11 | |
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12 | # version |
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13 | version=1.1 |
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14 | |
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15 | # Filling values for floats, integer and string |
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16 | fillValueF = 1.e20 |
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17 | fillValueI = -99999 |
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18 | fillValueS = '---' |
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19 | |
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20 | # Length of the string variables |
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21 | StringLength = 200 |
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22 | |
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23 | # Size of the map for the complementary variables/maps |
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24 | Ndim2D = 100 |
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25 | |
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26 | main = 'create_OBSnetcdf.py' |
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27 | errormsg = 'ERROR -- error -- ERROR -- error' |
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28 | warnmsg = 'WARNING -- warning -- WARNING -- warning' |
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29 | |
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30 | fillValue = 1.e20 |
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31 | |
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32 | def searchInlist(listname, nameFind): |
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33 | """ Function to search a value within a list |
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34 | listname = list |
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35 | nameFind = value to find |
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36 | >>> searInlist(['1', '2', '3', '5'], '5') |
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37 | True |
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38 | """ |
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39 | for x in listname: |
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40 | if x == nameFind: |
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41 | return True |
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42 | return False |
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43 | |
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44 | def set_attribute(ncvar, attrname, attrvalue): |
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45 | """ Sets a value of an attribute of a netCDF variable. Removes previous attribute value if exists |
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46 | ncvar = object netcdf variable |
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47 | attrname = name of the attribute |
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48 | attrvalue = value of the attribute |
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49 | """ |
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50 | import numpy as np |
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51 | from netCDF4 import Dataset as NetCDFFile |
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52 | |
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53 | attvar = ncvar.ncattrs() |
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54 | if searchInlist(attvar, attrname): |
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55 | attr = ncvar.delncattr(attrname) |
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56 | |
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57 | attr = ncvar.setncattr(attrname, attrvalue) |
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58 | |
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59 | return ncvar |
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60 | |
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61 | def basicvardef(varobj, vstname, vlname, vunits): |
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62 | """ Function to give the basic attributes to a variable |
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63 | varobj= netCDF variable object |
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64 | vstname= standard name of the variable |
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65 | vlname= long name of the variable |
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66 | vunits= units of the variable |
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67 | """ |
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68 | attr = varobj.setncattr('standard_name', vstname) |
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69 | attr = varobj.setncattr('long_name', vlname) |
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70 | attr = varobj.setncattr('units', vunits) |
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71 | |
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72 | return |
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73 | |
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74 | def remove_NONascii(string): |
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75 | """ Function to remove that characters which are not in the standard 127 ASCII |
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76 | string= string to transform |
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77 | >>> remove_NONascii('LluÃs') |
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78 | Lluis |
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79 | """ |
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80 | fname = 'remove_NONascii' |
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81 | |
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82 | newstring = string |
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83 | |
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84 | RTFchar= ['á', 'é', 'Ã', 'ó', 'ú', 'à ', 'Ú', 'ì', 'ò', 'ù', 'â', 'ê', 'î', 'ÃŽ', \ |
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85 | 'û', 'À', 'ë', 'ï', 'ö', 'ÃŒ', 'ç', 'ñ','Ê', 'Å', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', \ |
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86 | 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã', 'Ã',\ |
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87 | 'Ã', 'Å', '\n', '\t'] |
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88 | ASCchar= ['a', 'e', 'i', 'o', 'u', 'a', 'e', 'i', 'o', 'u', 'a', 'e', 'i', 'o', \ |
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89 | 'u', 'a', 'e', 'i', 'o', 'u', 'c', 'n','ae', 'oe', 'A', 'E', 'I', 'O', 'U', 'A', \ |
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90 | 'E', 'I', 'O', 'U', 'A', 'E', 'I', 'O', 'U', 'A', 'E', 'I', 'O', 'U', 'C', 'N',\ |
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91 | 'AE', 'OE', '', ' '] |
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92 | |
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93 | Nchars = len(RTFchar) |
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94 | for ichar in range(Nchars): |
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95 | foundchar = string.find(RTFchar[ichar]) |
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96 | if foundchar != -1: |
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97 | newstring = newstring.replace(RTFchar[ichar], ASCchar[ichar]) |
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98 | |
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99 | return newstring |
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100 | |
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101 | def read_description(fdobs, dbg): |
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102 | """ reads the description file of the observational data-set |
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103 | fdobs= descriptive observational data-set |
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104 | dbg= boolean argument for debugging |
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105 | * Each station should have a 'description.dat' file with: |
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106 | institution=Institution who creates the data |
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107 | department=Department within the institution |
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108 | scientists=names of the data producers |
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109 | contact=contact of the data producers |
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110 | description=description of the observations |
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111 | acknowledgement=sentence of acknowlegement |
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112 | comment=comment for the measurements |
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113 | |
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114 | MissingValue='|' list of ASCII values for missing values within the data |
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115 | (as they appear!, 'empty' for no value at all) |
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116 | comment=comments |
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117 | |
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118 | varN='|' list of variable names |
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119 | varLN='|' list of long variable names |
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120 | varU='|' list units of the variables |
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121 | varBUFR='|' list BUFR code of the variables |
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122 | varTYPE='|' list of variable types ('D', 'F', 'I', 'I64', 'S') |
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123 | varOPER='|' list of operations to do to the variables to meet their units ([oper],[val]) |
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124 | [oper]: |
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125 | -, nothing |
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126 | sumc, add [val] |
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127 | subc, rest [val] |
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128 | mulc, multiply by [val] |
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129 | divc, divide by [val] |
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130 | rmchar,[val],[pos], remove [val] characters from [pos]='B', beginning, 'E', end |
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131 | NAMElon=name of the variable with the longitude (x position) |
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132 | NAMElat=name of the variable with the latitude (y position) |
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133 | NAMEheight=ind_alt |
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134 | NAMEtime=name of the varibale with the time |
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135 | FMTtime=format of the time (as in 'C', 'CFtime' for already CF-like time) |
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136 | |
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137 | """ |
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138 | fname = 'read_description' |
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139 | |
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140 | descobj = open(fdobs, 'r') |
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141 | desc = {} |
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142 | |
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143 | namevalues = [] |
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144 | |
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145 | for line in descobj: |
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146 | if line[0:1] != '#' and len(line) > 1 : |
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147 | descn = remove_NONascii(line.split('=')[0]) |
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148 | descv = remove_NONascii(line.split('=')[1]) |
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149 | namevalues.append(descn) |
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150 | if descn[0:3] != 'var': |
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151 | if descn != 'MissingValue': |
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152 | desc[descn] = descv |
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153 | else: |
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154 | desc[descn] = [] |
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155 | for dn in descv.split('|'): desc[descn].append(dn) |
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156 | print ' ' + fname + ': missing values found:',desc[descn] |
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157 | elif descn[0:3] == 'var': |
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158 | desc[descn] = descv.split('|') |
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159 | elif descn[0:4] == 'NAME': |
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160 | desc[descn] = descv |
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161 | elif descn[0:3] == 'FMT': |
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162 | desc[descn] = descv |
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163 | if not desc.has_key('varOPER'): desc['varOPER'] = None |
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164 | |
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165 | if dbg: |
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166 | Nvars = len(desc['varN']) |
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167 | print ' ' + fname + ": description content of '" + fdobs + "'______________" |
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168 | for varn in namevalues: |
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169 | if varn[0:3] != 'var': |
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170 | print ' ' + varn + ':',desc[varn] |
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171 | elif varn == 'varN': |
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172 | print ' * Variables:' |
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173 | for ivar in range(Nvars): |
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174 | varname = desc['varN'][ivar] |
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175 | varLname = desc['varLN'][ivar] |
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176 | varunits = desc['varU'][ivar] |
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177 | if desc.has_key('varBUFR'): |
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178 | varbufr = desc['varBUFR'][ivar] |
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179 | else: |
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180 | varbufr = None |
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181 | if desc['varOPER'] is not None: |
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182 | opv = desc['varOPER'][ivar] |
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183 | else: |
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184 | opv = None |
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185 | print ' ', ivar, varname+':',varLname,'[',varunits, \ |
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186 | ']','bufr code:',varbufr,'oper:',opv |
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187 | |
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188 | descobj.close() |
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189 | |
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190 | return desc |
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191 | |
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192 | def value_fmt(val, miss, op, fmt): |
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193 | """ Function to transform an ASCII value to a given format |
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194 | val= value to transform |
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195 | miss= list of possible missing values |
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196 | op= operation to perform to the value |
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197 | fmt= format to take: |
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198 | 'D': float double precission |
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199 | 'F': float |
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200 | 'I': integer |
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201 | 'I64': 64-bits integer |
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202 | 'S': string |
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203 | >>> value_fmt('9876.12', '-999', 'F') |
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204 | 9876.12 |
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205 | """ |
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206 | |
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207 | fname = 'value_fmt' |
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208 | |
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209 | aopers = ['sumc','subc','mulc','divc', 'rmchar'] |
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210 | |
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211 | fmts = ['D', 'F', 'I', 'I64', 'S'] |
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212 | Nfmts = len(fmts) |
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213 | |
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214 | if not searchInlist(miss,val): |
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215 | if searchInlist(miss,'empty') and len(val) == 0: |
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216 | newval = None |
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217 | else: |
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218 | if op != '-': |
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219 | opern = op.split(',')[0] |
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220 | operv = op.split(',')[1] |
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221 | |
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222 | if not searchInlist(aopers,opern): |
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223 | print errormsg |
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224 | print ' ' + fname + ": operation '" + opern + "' not ready!!" |
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225 | print ' availables:',aopers |
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226 | quit(-1) |
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227 | else: |
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228 | opern = 'sumc' |
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229 | operv = '0.' |
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230 | |
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231 | if not searchInlist(fmts, fmt): |
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232 | print errormsg |
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233 | print ' ' + fname + ": format '" + fmt + "' not ready !!" |
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234 | quit(-1) |
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235 | else: |
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236 | if fmt == 'D': |
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237 | opv = np.float32(operv) |
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238 | if opern == 'sumc': newval = np.float32(val) + opv |
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239 | elif opern == 'subc': newval = np.float32(val) - opv |
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240 | elif opern == 'mulc': newval = np.float32(val) * opv |
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241 | elif opern == 'divc': newval = np.float32(val) / opv |
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242 | elif opern == 'rmchar': |
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243 | opv = int(operv) |
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244 | Lval = len(val) |
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245 | if op.split(',')[2] == 'B': |
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246 | newval = np.float32(val[opv:Lval+1]) |
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247 | elif op.split(',')[2] == 'E': |
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248 | newval = np.float32(val[Lval-opv:Lval]) |
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249 | else: |
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250 | print errormsg |
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251 | print ' ' + fname + ": operation '" + opern + "' not " +\ |
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252 | " work with '" + op.split(',')[2] + "' !!" |
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253 | quit(-1) |
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254 | elif fmt == 'F': |
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255 | opv = np.float(operv) |
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256 | if opern == 'sumc': newval = np.float(val) + opv |
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257 | elif opern == 'subc': newval = np.float(val) - opv |
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258 | elif opern == 'mulc': newval = np.float(val) * opv |
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259 | elif opern == 'divc': newval = np.float(val) / opv |
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260 | elif opern == 'rmchar': |
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261 | opv = int(operv) |
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262 | Lval = len(val) |
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263 | if op.split(',')[2] == 'B': |
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264 | newval = np.float(val[opv:Lval+1]) |
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265 | elif op.split(',')[2] == 'E': |
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266 | newval = np.float(val[0:Lval-opv]) |
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267 | else: |
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268 | print errormsg |
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269 | print ' ' + fname + ": operation '" + opern + "' not " +\ |
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270 | " work with '" + op.split(',')[2] + "' !!" |
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271 | quit(-1) |
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272 | |
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273 | elif fmt == 'I': |
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274 | opv = int(operv) |
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275 | if opern == 'sumc': newval = int(val) + opv |
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276 | elif opern == 'subc': newval = int(val) - opv |
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277 | elif opern == 'mulc': newval = int(val) * opv |
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278 | elif opern == 'divc': newval = int(val) / opv |
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279 | elif opern == 'rmchar': |
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280 | opv = int(operv) |
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281 | Lval = len(val) |
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282 | if op.split(',')[2] == 'B': |
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283 | newval = int(val[opv:Lval+1]) |
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284 | elif op.split(',')[2] == 'E': |
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285 | newval = int(val[0:Lval-opv]) |
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286 | else: |
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287 | print errormsg |
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288 | print ' ' + fname + ": operation '" + opern + "' not " +\ |
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289 | " work with '" + op.split(',')[2] + "' !!" |
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290 | quit(-1) |
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291 | elif fmt == 'I64': |
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292 | opv = np.int64(operv) |
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293 | if opern == 'sumc': newval = np.int64(val) + opv |
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294 | elif opern == 'subc': newval = np.int64(val) - opv |
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295 | elif opern == 'mulc': newval = np.int64(val) * opv |
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296 | elif opern == 'divc': newval = np.int64(val) / opv |
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297 | elif opern == 'rmchar': |
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298 | opv = int(operv) |
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299 | Lval = len(val) |
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300 | if op.split(',')[2] == 'B': |
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301 | newval = np.int64(val[opv:Lval+1]) |
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302 | elif op.split(',')[2] == 'E': |
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303 | newval = np.int64(val[0:Lval-opv]) |
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304 | else: |
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305 | print errormsg |
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306 | print ' ' + fname + ": operation '" + opern + "' not " +\ |
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307 | " work with '" + op.split(',')[2] + "' !!" |
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308 | quit(-1) |
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309 | elif fmt == 'S': |
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310 | if opern == 'rmchar': |
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311 | opv = int(operv) |
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312 | Lval = len(val) |
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313 | if op.split(',')[2] == 'B': |
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314 | newval = val[opv:Lval+1] |
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315 | elif op.split(',')[2] == 'E': |
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316 | newval = val[0:Lval-opv] |
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317 | else: |
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318 | print errormsg |
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319 | print ' ' + fname + ": operation '" + opern + "' not " +\ |
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320 | " work with '" + op.split(',')[2] + "' !!" |
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321 | quit(-1) |
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322 | else: |
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323 | newval = val |
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324 | |
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325 | else: |
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326 | newval = None |
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327 | |
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328 | return newval |
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329 | |
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330 | def read_datavalues(dataf, comchar, colchar, fmt, oper, miss, varns, dbg): |
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331 | """ Function to read from an ASCII file values in column |
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332 | dataf= data file |
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333 | comchar= list of the characters indicating comment in the file |
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334 | colchar= character which indicate end of value in the column |
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335 | dbg= debug mode or not |
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336 | fmt= list of kind of values to be found |
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337 | oper= list of operations to perform |
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338 | miss= missing value |
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339 | varns= list of name of the variables to find |
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340 | """ |
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341 | |
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342 | fname = 'read_datavalues' |
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343 | |
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344 | ofile = open(dataf, 'r') |
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345 | Nvals = len(fmt) |
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346 | |
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347 | if oper is None: |
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348 | opers = [] |
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349 | for ioper in range(Nvals): |
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350 | opers.append('-') |
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351 | else: |
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352 | opers = oper |
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353 | |
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354 | finalvalues = {} |
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355 | |
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356 | iline = 0 |
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357 | for line in ofile: |
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358 | line = line.replace('\n','').replace(chr(13),'') |
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359 | if not searchInlist(comchar,line[0:1]) and len(line) > 1: |
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360 | values0 = line.split(colchar) |
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361 | # Removing no-value columns |
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362 | values = [] |
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363 | for iv in values0: |
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364 | if len(iv) > 0: values.append(iv) |
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365 | |
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366 | Nvalues = len(values) |
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367 | # Checkings for wierd characters at the end of lines (use it to check) |
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368 | # if values[Nvalues-1][0:4] == '-999': |
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369 | # print line,'last v:',values[Nvalues-1],'len:',len(values[Nvalues-1]) |
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370 | # for ic in range(len(values[Nvalues-1])): |
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371 | # print ic,ord(values[Nvalues-1][ic:ic+1]) |
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372 | # quit() |
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373 | |
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374 | if len(values[Nvalues-1]) == 0: |
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375 | Nvalues = Nvalues - 1 |
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376 | |
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377 | if Nvalues != Nvals: |
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378 | print warnmsg |
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379 | print ' ' + fname + ': number of formats:',Nvals,' and number of ', \ |
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380 | 'values:',Nvalues,' with split character *' + colchar + \ |
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381 | '* does not coincide!!' |
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382 | print ' * what is found is ________' |
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383 | if Nvalues > Nvals: |
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384 | Nshow = Nvals |
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385 | for ivar in range(Nshow): |
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386 | print ' ',varns[ivar],'fmt:',fmt[ivar],'value:',values[ivar] |
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387 | print ' missing formats for:',values[Nshow:Nvalues+1] |
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388 | print ' values not considered, continue' |
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389 | else: |
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390 | Nshow = Nvalues |
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391 | for ivar in range(Nshow): |
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392 | print ' ',varns[ivar],'fmt:',fmt[ivar],'value:',values[ivar] |
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393 | print ' excess of formats:',fmt[Nshow:Nvals+1] |
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394 | quit(-1) |
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395 | |
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396 | # Reading and transforming values |
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397 | if dbg: print ' ' + fname + ': values found _________' |
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398 | |
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399 | for ivar in range(Nvals): |
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400 | if dbg: |
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401 | print iline, varns[ivar],'value:',values[ivar],miss,opers[ivar], \ |
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402 | fmt[ivar] |
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403 | |
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404 | if iline == 0: |
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405 | listvals = [] |
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406 | listvals.append(value_fmt(values[ivar], miss, opers[ivar], \ |
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407 | fmt[ivar])) |
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408 | finalvalues[varns[ivar]] = listvals |
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409 | else: |
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410 | listvals = finalvalues[varns[ivar]] |
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411 | listvals.append(value_fmt(values[ivar], miss, opers[ivar], \ |
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412 | fmt[ivar])) |
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413 | finalvalues[varns[ivar]] = listvals |
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414 | else: |
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415 | # First line without values |
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416 | if iline == 0: iline = -1 |
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417 | |
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418 | iline = iline + 1 |
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419 | |
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420 | ofile.close() |
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421 | |
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422 | return finalvalues |
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423 | |
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424 | def writing_str_nc(varo, values, Lchar): |
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425 | """ Function to write string values in a netCDF variable as a chain of 1char values |
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426 | varo= netCDF variable object |
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427 | values = list of values to introduce |
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428 | Lchar = length of the string in the netCDF file |
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429 | """ |
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430 | |
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431 | Nvals = len(values) |
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432 | |
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433 | for iv in range(Nvals): |
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434 | stringv=values[iv] |
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435 | charvals = np.chararray(Lchar) |
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436 | Lstr = len(stringv) |
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437 | charvals[Lstr:Lchar] = '' |
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438 | |
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439 | for ich in range(Lstr): |
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440 | charvals[ich] = stringv[ich:ich+1] |
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441 | |
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442 | varo[iv,:] = charvals |
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443 | |
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444 | return |
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445 | |
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446 | def Stringtimes_CF(tvals, fmt, Srefdate, tunits, dbg): |
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447 | """ Function to transform a given data in String formats to a CF date |
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448 | tvals= string temporal values |
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449 | fmt= format of the the time values |
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450 | Srefdate= reference date in [YYYY][MM][DD][HH][MI][SS] format |
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451 | tunits= units to use ('weeks', 'days', 'hours', 'minutes', 'seconds') |
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452 | dbg= debug |
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453 | >>> Stringtimes_CF(['19760217082712','20150213101837'], '%Y%m%d%H%M%S', |
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454 | '19491201000000', 'hours', False) |
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455 | [229784.45333333 571570.31027778] |
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456 | """ |
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457 | import datetime as dt |
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458 | |
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459 | fname = 'Stringtimes' |
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460 | |
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461 | dimt = len(tvals) |
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462 | |
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463 | yrref = int(Srefdate[0:4]) |
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464 | monref = int(Srefdate[4:6]) |
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465 | dayref = int(Srefdate[6:8]) |
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466 | horref = int(Srefdate[8:10]) |
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467 | minref = int(Srefdate[10:12]) |
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468 | secref = int(Srefdate[12:14]) |
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469 | refdate = dt.datetime( yrref, monref, dayref, horref, minref, secref) |
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470 | |
---|
471 | cftimes = np.zeros((dimt), dtype=np.float) |
---|
472 | |
---|
473 | Nfmt=len(fmt.split('%')) |
---|
474 | |
---|
475 | if dbg: print ' ' + fname + ': fmt=',fmt,'refdate:',Srefdate,'uits:',tunits, \ |
---|
476 | 'date dt_days dt_time deltaseconds CFtime _______' |
---|
477 | for it in range(dimt): |
---|
478 | |
---|
479 | # Removing excess of mili-seconds (up to 6 decimals) |
---|
480 | if fmt.split('%')[Nfmt-1] == 'f': |
---|
481 | tpoints = tvals[it].split('.') |
---|
482 | if len(tpoints[len(tpoints)-1]) > 6: |
---|
483 | milisec = '{0:.6f}'.format(np.float('0.'+tpoints[len(tpoints)-1]))[0:7] |
---|
484 | newtval = '' |
---|
485 | for ipt in range(len(tpoints)-1): |
---|
486 | newtval = newtval + tpoints[ipt] + '.' |
---|
487 | newtval = newtval + str(milisec)[2:len(milisec)+1] |
---|
488 | else: |
---|
489 | newtval = tvals[it] |
---|
490 | tval = dt.datetime.strptime(newtval, fmt) |
---|
491 | else: |
---|
492 | tval = dt.datetime.strptime(tvals[it], fmt) |
---|
493 | |
---|
494 | deltatime = tval - refdate |
---|
495 | deltaseconds = deltatime.days*24.*3600. + deltatime.seconds + \ |
---|
496 | deltatime.microseconds/100000. |
---|
497 | if tunits == 'weeks': |
---|
498 | deltat = 7.*24.*3600. |
---|
499 | elif tunits == 'days': |
---|
500 | deltat = 24.*3600. |
---|
501 | elif tunits == 'hours': |
---|
502 | deltat = 3600. |
---|
503 | elif tunits == 'minutes': |
---|
504 | deltat = 60. |
---|
505 | elif tunits == 'seconds': |
---|
506 | deltat = 1. |
---|
507 | else: |
---|
508 | print errormsg |
---|
509 | print ' ' + fname + ": time units '" + tunits + "' not ready !!" |
---|
510 | quit(-1) |
---|
511 | |
---|
512 | cftimes[it] = deltaseconds / deltat |
---|
513 | if dbg: |
---|
514 | print ' ' + tvals[it], deltatime, deltaseconds, cftimes[it] |
---|
515 | |
---|
516 | return cftimes |
---|
517 | |
---|
518 | def adding_complementary(onc, dscn, okind, dvalues, tvals, refCFt, CFtu, Nd, dbg): |
---|
519 | """ Function to add complementary variables as function of the observational type |
---|
520 | onc= netcdf objecto file to add the variables |
---|
521 | dscn= description dictionary |
---|
522 | okind= observational kind |
---|
523 | dvalues= values |
---|
524 | tvals= CF time values |
---|
525 | refCFt= reference time of CF time (in [YYYY][MM][DD][HH][MI][SS]) |
---|
526 | CFtu= CF time units |
---|
527 | Nd= size of the domain |
---|
528 | dbg= debugging flag |
---|
529 | """ |
---|
530 | import numpy.ma as ma |
---|
531 | |
---|
532 | fname = 'adding_complementary' |
---|
533 | |
---|
534 | # Kind of observations which require de integer lon/lat (for the 2D map) |
---|
535 | map2D=['multi-points', 'trajectory'] |
---|
536 | |
---|
537 | SrefCFt = refCFt[0:4] +'-'+ refCFt[4:6] +'-'+ refCFt[6:8] + ' ' + refCFt[8:10] + \ |
---|
538 | ':'+ refCFt[10:12] +':'+ refCFt[12:14] |
---|
539 | |
---|
540 | if dscn['NAMElon'] == '-' or dscn['NAMElat'] == '-': |
---|
541 | print errormsg |
---|
542 | print ' ' + fname + ": to complement a '" + okind + "' observation kind " + \ |
---|
543 | " a given longitude ('NAMElon':",dscn['NAMElon'],") and latitude ('" + \ |
---|
544 | "'NAMElat:'", dscn['NAMElat'],') from the data has to be provided and ' + \ |
---|
545 | 'any are given !!' |
---|
546 | quit(-1) |
---|
547 | |
---|
548 | if not dvalues.has_key(dscn['NAMElon']) or not dvalues.has_key(dscn['NAMElat']): |
---|
549 | print errormsg |
---|
550 | print ' ' + fname + ": observations do not have 'NAMElon':", \ |
---|
551 | dscn['NAMElon'],"and/or 'NAMElat:'", dscn['NAMElat'],' !!' |
---|
552 | print ' available data:',dvalues.keys() |
---|
553 | quit(-1) |
---|
554 | |
---|
555 | if okind == 'trajectory': |
---|
556 | if dscn['NAMEheight'] == '-': |
---|
557 | print warnmsg |
---|
558 | print ' ' + fname + ": to complement a '" + okind + "' observation " + \ |
---|
559 | "kind a given height ('NAMEheight':",dscn['NAMEheight'],"') might " + \ |
---|
560 | 'be provided and any is given !!' |
---|
561 | quit(-1) |
---|
562 | |
---|
563 | if not dvalues.has_key(dscn['NAMEheight']): |
---|
564 | print errormsg |
---|
565 | print ' ' + fname + ": observations do not have 'NAMEtime':", \ |
---|
566 | dscn['NAMEtime'],' !!' |
---|
567 | print ' available data:',dvalues.keys() |
---|
568 | quit(-1) |
---|
569 | |
---|
570 | if searchInlist(map2D, okind): |
---|
571 | # A new 2D map with the number of observation will be added for that 'NAMElon' |
---|
572 | # and 'NAMElat' are necessary. A NdxNd domain space size will be used. |
---|
573 | objfile.createDimension('lon2D',Nd) |
---|
574 | objfile.createDimension('lat2D',Nd) |
---|
575 | lonvals = ma.masked_equal(dvalues[dscn['NAMElon']], None) |
---|
576 | latvals = ma.masked_equal(dvalues[dscn['NAMElat']], None) |
---|
577 | |
---|
578 | minlon = min(lonvals) |
---|
579 | maxlon = max(lonvals) |
---|
580 | minlat = min(latvals) |
---|
581 | maxlat = max(latvals) |
---|
582 | |
---|
583 | blon = (maxlon - minlon)/(Nd-1) |
---|
584 | blat = (maxlat - minlat)/(Nd-1) |
---|
585 | |
---|
586 | newvar = onc.createVariable( 'lon2D', 'f8', ('lon2D')) |
---|
587 | basicvardef(newvar, 'longitude', 'longitude map observations','degrees_East') |
---|
588 | newvar[:] = minlon + np.arange(Nd)*blon |
---|
589 | newattr = set_attribute(newvar, 'axis', 'X') |
---|
590 | |
---|
591 | newvar = onc.createVariable( 'lat2D', 'f8', ('lat2D')) |
---|
592 | basicvardef(newvar, 'latitude', 'latitude map observations', 'degrees_North') |
---|
593 | newvar[:] = minlat + np.arange(Nd)*blat |
---|
594 | newattr = set_attribute(newvar, 'axis', 'Y') |
---|
595 | |
---|
596 | if dbg: |
---|
597 | print ' ' + fname + ': minlon=',minlon,'maxlon=',maxlon |
---|
598 | print ' ' + fname + ': minlat=',minlat,'maxlat=',maxlat |
---|
599 | print ' ' + fname + ': precission on x-axis=', blon*(Nd-1), 'y-axis=', \ |
---|
600 | blat*(Nd-1) |
---|
601 | |
---|
602 | if okind == 'multi-points': |
---|
603 | map2D = np.ones((Nd, Nd), dtype=np.float)*fillValueI |
---|
604 | |
---|
605 | dimt = len(tvals) |
---|
606 | Nlost = 0 |
---|
607 | for it in range(dimt): |
---|
608 | lon = dvalues[dscn['NAMElon']][it] |
---|
609 | lat = dvalues[dscn['NAMElat']][it] |
---|
610 | if lon is not None and lat is not None: |
---|
611 | ilon = int((Nd-1)*(lon - minlon)/(maxlon - minlon)) |
---|
612 | ilat = int((Nd-1)*(lat - minlat)/(maxlat - minlat)) |
---|
613 | |
---|
614 | if map2D[ilat,ilon] == fillValueI: |
---|
615 | map2D[ilat,ilon] = 1 |
---|
616 | else: |
---|
617 | map2D[ilat,ilon] = map2D[ilat,ilon] + 1 |
---|
618 | if dbg: print it, lon, lat, ilon, ilat, map2D[ilat,ilon] |
---|
619 | |
---|
620 | newvar = onc.createVariable( 'mapobs', 'f4', ('lat2D', 'lon2D'), \ |
---|
621 | fill_value = fillValueI) |
---|
622 | basicvardef(newvar, 'map_observations', 'number of observations', '-') |
---|
623 | newvar[:] = map2D |
---|
624 | newattr = set_attribute(newvar, 'coordinates', 'lon2D lat2D') |
---|
625 | |
---|
626 | elif okind == 'trajectory': |
---|
627 | # A new 2D map with the trajectory 'NAMElon' and 'NAMElat' and maybe 'NAMEheight' |
---|
628 | # are necessary. A NdxNdxNd domain space size will be used. Using time as |
---|
629 | # reference variable |
---|
630 | if dscn['NAMEheight'] == '-': |
---|
631 | # No height |
---|
632 | map2D = np.ones((Nd, Nd), dtype=np.float)*fillValueI |
---|
633 | |
---|
634 | dimt = len(tvals) |
---|
635 | Nlost = 0 |
---|
636 | if dbg: print ' time-step lon lat ix iy passes _______' |
---|
637 | for it in range(dimt): |
---|
638 | lon = dvalues[dscn['NAMElon']][it] |
---|
639 | lat = dvalues[dscn['NAMElat']][it] |
---|
640 | if lon is not None and lat is not None: |
---|
641 | ilon = int((Nd-1)*(lon - minlon)/(maxlon - minlon)) |
---|
642 | ilat = int((Nd-1)*(lat - minlat)/(maxlat - minlat)) |
---|
643 | |
---|
644 | if map2D[ilat,ilon] == fillValueI: |
---|
645 | map2D[ilat,ilon] = 1 |
---|
646 | else: |
---|
647 | map2D[ilat,ilon] = map2D[ilat,ilon] + 1 |
---|
648 | if dbg: print it, lon, lat, ilon, ilat, map2D[ilat,ilon] |
---|
649 | |
---|
650 | newvar = onc.createVariable( 'trjobs', 'i', ('lat2D', 'lon2D'), \ |
---|
651 | fill_value = fillValueI) |
---|
652 | basicvardef(newvar, 'trajectory_observations', 'number of passes', '-' ) |
---|
653 | newvar[:] = map2D |
---|
654 | newattr = set_attribute(newvar, 'coordinates', 'lon2D lat2D') |
---|
655 | |
---|
656 | else: |
---|
657 | ivn = 0 |
---|
658 | for vn in dscn['varN']: |
---|
659 | if vn == dscn['NAMEheight']: |
---|
660 | zu = dscn['varU'][ivn] |
---|
661 | break |
---|
662 | ivn = ivn + 1 |
---|
663 | |
---|
664 | objfile.createDimension('z2D',Nd) |
---|
665 | zvals = ma.masked_equal(dvalues[dscn['NAMEheight']], None) |
---|
666 | minz = min(zvals) |
---|
667 | maxz = max(zvals) |
---|
668 | |
---|
669 | bz = (maxz - minz)/(Nd-1) |
---|
670 | |
---|
671 | newvar = onc.createVariable( 'z2D', 'f8', ('z2D')) |
---|
672 | basicvardef(newvar, 'z2D', 'z-coordinate map observations', zu) |
---|
673 | newvar[:] = minz + np.arange(Nd)*bz |
---|
674 | newattr = set_attribute(newvar, 'axis', 'Z') |
---|
675 | |
---|
676 | if dbg: |
---|
677 | print ' ' + fname + ': zmin=',minz,zu,'zmax=',maxz,zu |
---|
678 | print ' ' + fname + ': precission on z-axis=', bz*(Nd-1), zu |
---|
679 | |
---|
680 | map3D = np.ones((Nd, Nd, Nd), dtype=int)*fillValueI |
---|
681 | dimt = len(tvals) |
---|
682 | Nlost = 0 |
---|
683 | if dbg: print ' time-step lon lat z ix iy iz passes _______' |
---|
684 | for it in range(dimt): |
---|
685 | lon = dvalues[dscn['NAMElon']][it] |
---|
686 | lat = dvalues[dscn['NAMElat']][it] |
---|
687 | z = dvalues[dscn['NAMEheight']][it] |
---|
688 | if lon is not None and lat is not None and z is not None: |
---|
689 | ilon = int((Nd-1)*(lon - minlon)/(maxlon - minlon)) |
---|
690 | ilat = int((Nd-1)*(lat - minlat)/(maxlat - minlat)) |
---|
691 | iz = int((Nd-1)*(z - minz)/(maxz - minz)) |
---|
692 | |
---|
693 | if map3D[iz,ilat,ilon] == fillValueI: |
---|
694 | map3D[iz,ilat,ilon] = 1 |
---|
695 | else: |
---|
696 | map3D[iz,ilat,ilon] = map3D[iz,ilat,ilon] + 1 |
---|
697 | if dbg: print it, lon, lat, z, ilon, ilat, iz, map3D[iz,ilat,ilon] |
---|
698 | |
---|
699 | newvar = onc.createVariable( 'trjobs', 'i', ('z2D', 'lat2D', 'lon2D'), \ |
---|
700 | fill_value = fillValueI) |
---|
701 | basicvardef(newvar, 'trajectory_observations', 'number of passes', '-') |
---|
702 | newvar[:] = map3D |
---|
703 | newattr = set_attribute(newvar, 'coordinates', 'lon2D lat2D z2D') |
---|
704 | |
---|
705 | onc.sync() |
---|
706 | return |
---|
707 | |
---|
708 | def adding_station_desc(onc,stdesc): |
---|
709 | """ Function to add a station description in a netCDF file |
---|
710 | onc= netCDF object |
---|
711 | stdesc= station description name, lon, lat, height |
---|
712 | """ |
---|
713 | fname = 'adding_station_desc' |
---|
714 | |
---|
715 | newdim = onc.createDimension('nst',1) |
---|
716 | |
---|
717 | newvar = objfile.createVariable( 'station', 'c', ('nst','StrLength')) |
---|
718 | writing_str_nc(newvar, [stdesc[0].replace('!', ' ')], StringLength) |
---|
719 | |
---|
720 | newvar = objfile.createVariable( 'lonstGDM', 'c', ('nst','StrLength')) |
---|
721 | Gv = int(stdesc[1]) |
---|
722 | Dv = int((stdesc[1] - Gv)*60.) |
---|
723 | Mv = int((stdesc[1] - Gv - Dv/60.)*3600.) |
---|
724 | writing_str_nc(newvar, [str(Gv)+"d" + str(Dv)+"m" + str(Mv)+'s'], StringLength) |
---|
725 | |
---|
726 | if onc.variables.has_key('lon'): |
---|
727 | print warnmsg |
---|
728 | print ' ' + fname + ": variable 'lon' already exist !!" |
---|
729 | print " renaming it as 'lonst'" |
---|
730 | lonname = 'lonst' |
---|
731 | else: |
---|
732 | lonname = 'lon' |
---|
733 | |
---|
734 | newvar = objfile.createVariable( lonname, 'f4', ('nst')) |
---|
735 | basicvardef(newvar, lonname, 'longitude', 'degrees_West' ) |
---|
736 | newvar[:] = stdesc[1] |
---|
737 | |
---|
738 | newvar = objfile.createVariable( 'latstGDM', 'c', ('nst','StrLength')) |
---|
739 | Gv = int(stdesc[2]) |
---|
740 | Dv = int((stdesc[2] - Gv)*60.) |
---|
741 | Mv = int((stdesc[2] - Gv - Dv/60.)*3600.) |
---|
742 | writing_str_nc(newvar, [str(Gv)+"d" + str(Dv)+"m" + str(Mv)+'s'], StringLength) |
---|
743 | |
---|
744 | if onc.variables.has_key('lat'): |
---|
745 | print warnmsg |
---|
746 | print ' ' + fname + ": variable 'lat' already exist !!" |
---|
747 | print " renaming it as 'latst'" |
---|
748 | latname = 'latst' |
---|
749 | else: |
---|
750 | latname = 'lat' |
---|
751 | |
---|
752 | newvar = objfile.createVariable( latname, 'f4', ('nst')) |
---|
753 | basicvardef(newvar, lonname, 'latitude', 'degrees_North' ) |
---|
754 | newvar[:] = stdesc[2] |
---|
755 | |
---|
756 | if onc.variables.has_key('height'): |
---|
757 | print warnmsg |
---|
758 | print ' ' + fname + ": variable 'height' already exist !!" |
---|
759 | print " renaming it as 'heightst'" |
---|
760 | heightname = 'heightst' |
---|
761 | else: |
---|
762 | heightname = 'height' |
---|
763 | |
---|
764 | newvar = objfile.createVariable( heightname, 'f4', ('nst')) |
---|
765 | basicvardef(newvar, heightname, 'height above sea level', 'm' ) |
---|
766 | newvar[:] = stdesc[3] |
---|
767 | |
---|
768 | return |
---|
769 | |
---|
770 | def oper_values(dvals, opers): |
---|
771 | """ Function to operate the values according to given parameters |
---|
772 | dvals= datavalues |
---|
773 | opers= operations |
---|
774 | """ |
---|
775 | fname = 'oper_values' |
---|
776 | |
---|
777 | newdvals = {} |
---|
778 | varnames = dvals.keys() |
---|
779 | |
---|
780 | aopers = ['sumc','subc','mulc','divc'] |
---|
781 | |
---|
782 | Nopers = len(opers) |
---|
783 | for iop in range(Nopers): |
---|
784 | vn = varnames[iop] |
---|
785 | print vn,'oper:',opers[iop] |
---|
786 | if opers[iop] != '-': |
---|
787 | opern = opers[iop].split(',')[0] |
---|
788 | operv = np.float(opers[iop].split(',')[1]) |
---|
789 | |
---|
790 | vvals = np.array(dvals[vn]) |
---|
791 | |
---|
792 | if opern == 'sumc': |
---|
793 | newvals = np.where(vvals is None, None, vvals+operv) |
---|
794 | elif opern == 'subc': |
---|
795 | newvals = np.where(vvals is None, None, vvals-operv) |
---|
796 | elif opern == 'mulc': |
---|
797 | newvals = np.where(vvals is None, None, vvals*operv) |
---|
798 | elif opern == 'divc': |
---|
799 | newvals = np.where(vvals is None, None, vvals/operv) |
---|
800 | else: |
---|
801 | print errormsg |
---|
802 | print ' ' + fname + ": operation '" + opern + "' not ready!!" |
---|
803 | print ' availables:',aopers |
---|
804 | quit(-1) |
---|
805 | |
---|
806 | newdvals[vn] = list(newvals) |
---|
807 | else: |
---|
808 | newdvals[vn] = dvals[vn] |
---|
809 | |
---|
810 | return newdvals |
---|
811 | |
---|
812 | ####### ###### ##### #### ### ## # |
---|
813 | |
---|
814 | strCFt="Refdate,tunits (CF reference date [YYYY][MM][DD][HH][MI][SS] format and " + \ |
---|
815 | " and time units: 'weeks', 'days', 'hours', 'miuntes', 'seconds')" |
---|
816 | |
---|
817 | kindobs=['stations-map','multi-points', 'single-station', 'trajectory'] |
---|
818 | strkObs="kind of observations; 'multi-points': multiple individual punctual obs " + \ |
---|
819 | "(e.g., lightning strikes), 'single-station': single station on a fixed position,"+\ |
---|
820 | "'trajectory': following a trajectory" |
---|
821 | |
---|
822 | parser = OptionParser() |
---|
823 | parser.add_option("-c", "--comments", dest="charcom", |
---|
824 | help="':', list of characters used for comments", metavar="VALUES") |
---|
825 | parser.add_option("-d", "--descriptionfile", dest="fdesc", |
---|
826 | help="description file to use" + read_description.__doc__, metavar="FILE") |
---|
827 | parser.add_option("-e", "--end_column", dest="endcol", |
---|
828 | help="character to indicate end of the column ('space', for ' ')", metavar="VALUE") |
---|
829 | parser.add_option("-f", "--file", dest="obsfile", |
---|
830 | help="observational file to use", metavar="FILE") |
---|
831 | parser.add_option("-g", "--debug", dest="debug", |
---|
832 | help="whther debug is required ('false', 'true')", metavar="VALUE") |
---|
833 | parser.add_option("-k", "--kindObs", dest="obskind", type='choice', choices=kindobs, |
---|
834 | help=strkObs, metavar="VALUE") |
---|
835 | parser.add_option("-s", "--stationLocation", dest="stloc", |
---|
836 | help="name ('!' for spaces), longitude, latitude and height of the station (only for 'single-station')", |
---|
837 | metavar="FILE") |
---|
838 | parser.add_option("-t", "--CFtime", dest="CFtime", help=strCFt, metavar="VALUE") |
---|
839 | |
---|
840 | (opts, args) = parser.parse_args() |
---|
841 | |
---|
842 | ####### ####### |
---|
843 | ## MAIN |
---|
844 | ####### |
---|
845 | |
---|
846 | ofile='OBSnetcdf.nc' |
---|
847 | |
---|
848 | if opts.charcom is None: |
---|
849 | print warnmsg |
---|
850 | print ' ' + main + ': No list of comment characters provided!!' |
---|
851 | print ' assuming no need!' |
---|
852 | charcomments = [] |
---|
853 | else: |
---|
854 | charcomments = opts.charcom.split(':') |
---|
855 | |
---|
856 | if opts.fdesc is None: |
---|
857 | print errormsg |
---|
858 | print ' ' + main + ': No description file for the observtional data provided!!' |
---|
859 | quit(-1) |
---|
860 | |
---|
861 | if opts.endcol is None: |
---|
862 | print warnmsg |
---|
863 | print ' ' + main + ': No list of comment characters provided!!' |
---|
864 | print " assuming 'space'" |
---|
865 | endcol = ' ' |
---|
866 | else: |
---|
867 | if opts.endcol == 'space': |
---|
868 | endcol = ' ' |
---|
869 | else: |
---|
870 | endcol = opts.endcol |
---|
871 | |
---|
872 | if opts.obsfile is None: |
---|
873 | print errormsg |
---|
874 | print ' ' + main + ': No observations file provided!!' |
---|
875 | quit(-1) |
---|
876 | |
---|
877 | if opts.debug is None: |
---|
878 | print warnmsg |
---|
879 | print ' ' + main + ': No debug provided!!' |
---|
880 | print " assuming 'False'" |
---|
881 | debug = False |
---|
882 | else: |
---|
883 | if opts.debug == 'true': |
---|
884 | debug = True |
---|
885 | else: |
---|
886 | debug = False |
---|
887 | |
---|
888 | if not os.path.isfile(opts.fdesc): |
---|
889 | print errormsg |
---|
890 | print ' ' + main + ": description file '" + opts.fdesc + "' does not exist !!" |
---|
891 | quit(-1) |
---|
892 | |
---|
893 | if not os.path.isfile(opts.obsfile): |
---|
894 | print errormsg |
---|
895 | print ' ' + main + ": observational file '" + opts.obsfile + "' does not exist !!" |
---|
896 | quit(-1) |
---|
897 | |
---|
898 | if opts.CFtime is None: |
---|
899 | print warnmsg |
---|
900 | print ' ' + main + ': No CFtime criteria are provided !!' |
---|
901 | print " either time is already in CF-format ('timeFMT=CFtime') in '" + \ |
---|
902 | opts.fdesc + "'" |
---|
903 | print " or assuming refdate: '19491201000000' and time units: 'hours'" |
---|
904 | referencedate = '19491201000000' |
---|
905 | timeunits = 'hours' |
---|
906 | else: |
---|
907 | referencedate = opts.CFtime.split(',')[0] |
---|
908 | timeunits = opts.CFtime.split(',')[1] |
---|
909 | |
---|
910 | if opts.obskind is None: |
---|
911 | print warnmsg |
---|
912 | print ' ' + main + ': No kind of observations provided !!' |
---|
913 | print " assuming 'single-station': single station on a fixed position at 0,0,0" |
---|
914 | obskind = 'single-station' |
---|
915 | stationdesc = [0.0, 0.0, 0.0, 0.0] |
---|
916 | else: |
---|
917 | obskind = opts.obskind |
---|
918 | if obskind == 'single-station': |
---|
919 | if opts.stloc is None: |
---|
920 | print errornmsg |
---|
921 | print ' ' + main + ': No station location provided !!' |
---|
922 | quit(-1) |
---|
923 | else: |
---|
924 | stvals = opts.stloc.split(',') |
---|
925 | stationdesc = [stvals[0], np.float(stvals[1]), np.float(stvals[2]), \ |
---|
926 | np.float(stvals[3])] |
---|
927 | else: |
---|
928 | obskind = opts.obskind |
---|
929 | |
---|
930 | # Reading description file |
---|
931 | ## |
---|
932 | description = read_description(opts.fdesc, debug) |
---|
933 | |
---|
934 | Nvariables=len(description['varN']) |
---|
935 | formats = description['varTYPE'] |
---|
936 | |
---|
937 | if len(formats) != Nvariables: |
---|
938 | print errormsg |
---|
939 | print ' ' + main + ': number of formats:',len(formats),' and number of ' + \ |
---|
940 | 'variables', Nvariables,' does not coincide!!' |
---|
941 | print ' * what is found is _______' |
---|
942 | if Nvariables > len(formats): |
---|
943 | Nshow = len(formats) |
---|
944 | for ivar in range(Nshow): |
---|
945 | print ' ',description['varN'][ivar],':', description['varLN'][ivar],\ |
---|
946 | '[', description['varU'][ivar], '] fmt:', formats[ivar] |
---|
947 | print ' missing values for:', description['varN'][Nshow:Nvariables+1] |
---|
948 | else: |
---|
949 | Nshow = Nvariables |
---|
950 | for ivar in range(Nshow): |
---|
951 | print ' ',description['varN'][ivar],':', description['varLN'][ivar],\ |
---|
952 | '[', description['varU'][ivar], '] fmt:', formats[ivar] |
---|
953 | print ' excess of formats for:', formats[Nshow:len(formats)+1] |
---|
954 | |
---|
955 | # quit(-1) |
---|
956 | |
---|
957 | # Reading values |
---|
958 | ## |
---|
959 | datavalues = read_datavalues(opts.obsfile, charcomments, endcol, formats, |
---|
960 | description['varOPER'], description['MissingValue'], description['varN'], debug) |
---|
961 | |
---|
962 | # Total number of values |
---|
963 | Ntvalues = len(datavalues[description['varN'][0]]) |
---|
964 | if obskind == 'stations-map': |
---|
965 | print main + ': total values found:',Ntvalues |
---|
966 | else: |
---|
967 | print main + ': total temporal values found:',Ntvalues |
---|
968 | |
---|
969 | objfile = NetCDFFile(ofile, 'w') |
---|
970 | |
---|
971 | # Creation of dimensions |
---|
972 | ## |
---|
973 | if obskind == 'stations-map': |
---|
974 | rowsdim = 'Npoints' |
---|
975 | dimlength = Ntvalues |
---|
976 | else: |
---|
977 | rowsdim = 'time' |
---|
978 | dimlength = None |
---|
979 | |
---|
980 | objfile.createDimension(rowsdim,dimlength) |
---|
981 | objfile.createDimension('StrLength',StringLength) |
---|
982 | |
---|
983 | # Creation of variables |
---|
984 | ## |
---|
985 | for ivar in range(Nvariables): |
---|
986 | varn = description['varN'][ivar] |
---|
987 | print " including: '" + varn + "' ... .. ." |
---|
988 | |
---|
989 | if formats[ivar] == 'D': |
---|
990 | newvar = objfile.createVariable(varn, 'f32', (rowsdim), fill_value=fillValueF) |
---|
991 | basicvardef(newvar, varn, description['varLN'][ivar], \ |
---|
992 | description['varU'][ivar]) |
---|
993 | newvar[:] = np.where(datavalues[varn] is None, fillValueF, datavalues[varn]) |
---|
994 | elif formats[ivar] == 'F': |
---|
995 | newvar = objfile.createVariable(varn, 'f', (rowsdim), fill_value=fillValueF) |
---|
996 | basicvardef(newvar, varn, description['varLN'][ivar], \ |
---|
997 | description['varU'][ivar]) |
---|
998 | newvar[:] = np.where(datavalues[varn] is None, fillValueF, datavalues[varn]) |
---|
999 | elif formats[ivar] == 'I': |
---|
1000 | newvar = objfile.createVariable(varn, 'i', (rowsdim), fill_value=fillValueI) |
---|
1001 | basicvardef(newvar, varn, description['varLN'][ivar], \ |
---|
1002 | description['varU'][ivar]) |
---|
1003 | # Why is not wotking with integers? |
---|
1004 | vals = np.array(datavalues[varn]) |
---|
1005 | for iv in range(Ntvalues): |
---|
1006 | if vals[iv] is None: vals[iv] = fillValueI |
---|
1007 | newvar[:] = vals |
---|
1008 | elif formats[ivar] == 'S': |
---|
1009 | newvar = objfile.createVariable(varn, 'c', (rowsdim,'StrLength')) |
---|
1010 | basicvardef(newvar, varn, description['varLN'][ivar], \ |
---|
1011 | description['varU'][ivar]) |
---|
1012 | writing_str_nc(newvar, datavalues[varn], StringLength) |
---|
1013 | |
---|
1014 | # Extra variable descriptions/attributes |
---|
1015 | if description.has_key('varBUFR'): |
---|
1016 | set_attribute(newvar,'bufr_code',description['varBUFR'][ivar]) |
---|
1017 | |
---|
1018 | objfile.sync() |
---|
1019 | |
---|
1020 | # Time variable in CF format |
---|
1021 | ## |
---|
1022 | if description['FMTtime'] == 'CFtime': |
---|
1023 | timevals = datavalues[description['NAMEtime']] |
---|
1024 | iv = 0 |
---|
1025 | for ivn in description['varN']: |
---|
1026 | if ivn == description['NAMEtime']: |
---|
1027 | tunits = description['varU'][iv] |
---|
1028 | break |
---|
1029 | iv = iv + 1 |
---|
1030 | else: |
---|
1031 | # Time as a composition of different columns |
---|
1032 | tcomposite = description['NAMEtime'].find('@') |
---|
1033 | if tcomposite != -1: |
---|
1034 | timevars = description['NAMEtime'].split('@') |
---|
1035 | |
---|
1036 | print warnmsg |
---|
1037 | print ' ' + main + ': time values as combination of different columns!' |
---|
1038 | print ' combining:',timevars,' with a final format: ',description['FMTtime'] |
---|
1039 | |
---|
1040 | timeSvals = [] |
---|
1041 | if debug: print ' ' + main + ': creating times _______' |
---|
1042 | for it in range(Ntvalues): |
---|
1043 | tSvals = '' |
---|
1044 | for tvar in timevars: |
---|
1045 | tSvals = tSvals + datavalues[tvar][it] + ' ' |
---|
1046 | |
---|
1047 | timeSvals.append(tSvals[0:len(tSvals)-1]) |
---|
1048 | if debug: print it, '*' + timeSvals[it] + '*' |
---|
1049 | |
---|
1050 | timevals = Stringtimes_CF(timeSvals, description['FMTtime'], referencedate, \ |
---|
1051 | timeunits, debug) |
---|
1052 | else: |
---|
1053 | timevals = Stringtimes_CF(datavalues[description['NAMEtime']], \ |
---|
1054 | description['FMTtime'], referencedate, timeunits, debug) |
---|
1055 | |
---|
1056 | CFtimeRef = referencedate[0:4] +'-'+ referencedate[4:6] +'-'+ referencedate[6:8] + \ |
---|
1057 | ' ' + referencedate[8:10] +':'+ referencedate[10:12] +':'+ referencedate[12:14] |
---|
1058 | tunits = timeunits + ' since ' + CFtimeRef |
---|
1059 | |
---|
1060 | if objfile.variables.has_key('time'): |
---|
1061 | print warnmsg |
---|
1062 | print ' ' + main + ": variable 'time' already exist !!" |
---|
1063 | print " renaming it as 'CFtime'" |
---|
1064 | timeCFname = 'CFtime' |
---|
1065 | newdim = objfile.renameDimension('time','CFtime') |
---|
1066 | newvar = objfile.createVariable( timeCFname, 'f8', ('CFtime')) |
---|
1067 | basicvardef(newvar, timeCFname, 'time', tunits ) |
---|
1068 | else: |
---|
1069 | newdim = objfile.createDimension('time',None) |
---|
1070 | timeCFname = 'time' |
---|
1071 | newvar = objfile.createVariable( timeCFname, 'f8', ('time')) |
---|
1072 | basicvardef(newvar, timeCFname, 'time', tunits ) |
---|
1073 | |
---|
1074 | set_attribute(newvar, 'calendar', 'standard') |
---|
1075 | if obskind == 'stations-map': |
---|
1076 | newvar[:] = timevals[0] |
---|
1077 | else: |
---|
1078 | newvar[:] = timevals |
---|
1079 | |
---|
1080 | # Global attributes |
---|
1081 | ## |
---|
1082 | for descn in description.keys(): |
---|
1083 | if descn[0:3] != 'var' and descn[0:4] != 'NAME' and descn[0:3] != 'FMT': |
---|
1084 | set_attribute(objfile, descn, description[descn]) |
---|
1085 | |
---|
1086 | set_attribute(objfile,'author_nc','Lluis Fita') |
---|
1087 | set_attribute(objfile,'institution_nc','Laboratoire de Meteorology Dynamique, ' + \ |
---|
1088 | 'LMD-Jussieu, UPMC, Paris') |
---|
1089 | set_attribute(objfile,'country_nc','France') |
---|
1090 | set_attribute(objfile,'script_nc','create_OBSnetcdf.py') |
---|
1091 | set_attribute(objfile,'version_script',version) |
---|
1092 | set_attribute(objfile,'information', \ |
---|
1093 | 'http://www.lmd.jussieu.fr/~lflmd/ASCIIobs_nc/index.html') |
---|
1094 | |
---|
1095 | objfile.sync() |
---|
1096 | |
---|
1097 | # Adding new variables as function of the observational type |
---|
1098 | ## 'multi-points', 'single-station', 'trajectory' |
---|
1099 | |
---|
1100 | if obskind != 'single-station': |
---|
1101 | adding_complementary(objfile, description, obskind, datavalues, timevals, \ |
---|
1102 | referencedate, timeunits, Ndim2D, debug) |
---|
1103 | else: |
---|
1104 | # Adding three variables with the station location, longitude, latitude and height |
---|
1105 | adding_station_desc(objfile,stationdesc) |
---|
1106 | |
---|
1107 | objfile.sync() |
---|
1108 | objfile.close() |
---|
1109 | |
---|
1110 | print main + ": Successfull generation of netcdf observational file '" + ofile + "' !!" |
---|