[1679] | 1 | ## Getting statistics from a series of surface stations and soundings from any given netCDF file |
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| 2 | # L. Fita, CIMA, November 2017 |
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| 3 | # |
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| 4 | import numpy as np |
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[1690] | 5 | #import matplotlib as mpl |
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| 6 | #mpl.use('Agg') |
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| 7 | #from matplotlib.pylab import * |
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| 8 | #import matplotlib.pyplot as plt |
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| 9 | #from mpl_toolkits.basemap import Basemap |
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[1679] | 10 | import os |
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| 11 | from netCDF4 import Dataset as NetCDFFile |
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| 12 | import nc_var_tools as ncvar |
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| 13 | import generic_tools as gen |
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[1691] | 14 | #import drawing_tools as drw |
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[1679] | 15 | import diag_tools as diag |
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| 16 | |
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[1686] | 17 | # Getting configuration |
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| 18 | from config_get_stations import * |
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[1679] | 19 | |
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| 20 | ####### ###### ##### #### ### ## # |
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| 21 | |
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[1688] | 22 | # Gneric variables prepared to be computed |
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[1694] | 23 | Cvars = ['C_td', 'C_wd', 'C_ws'] |
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[1688] | 24 | |
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| 25 | # WRF specific diagnostics |
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| 26 | WRFvars = ['WRFp', 'WRFta', 'WRFtd', 'WRFtime', 'WRFua', 'WRFuas', 'WRFva', 'WRFvas',\ |
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| 27 | 'WRFzg'] |
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| 28 | |
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[1679] | 29 | # Variables not to check their existence inside file |
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[1694] | 30 | NONcheckingvars = Cvars + WRFvars + ['None'] |
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[1679] | 31 | |
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| 32 | def creation_sfcstation_file(filen, lv, Lv, hv, lab, tunits, sfcvars, dimt, ifilen): |
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| 33 | """ Function to create the structure of the surface station file |
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| 34 | filen: name of the file |
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| 35 | lv: value of the longitude of the station |
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| 36 | Lv: value of the latitude of the station |
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| 37 | hv: value of the height of the station |
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| 38 | lab: label of the station |
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| 39 | tunits: uints of time |
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| 40 | sfcvars: variables to be included |
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| 41 | dimt: quantity of time-steps |
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| 42 | ifilen: name of the file from which data is retrieved |
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| 43 | """ |
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| 44 | fname = 'creation_sfcstation_file' |
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| 45 | |
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| 46 | Lstring = 256 |
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| 47 | |
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| 48 | onewnc = NetCDFFile(filen, 'w') |
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| 49 | # Dimensions |
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| 50 | newdim = onewnc.createDimension('time', None) |
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| 51 | newdim = onewnc.createDimension('Lstring', Lstring) |
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| 52 | |
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| 53 | # Variable-dimensions |
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| 54 | newvar = onewnc.createVariable('time', 'f8', ('time')) |
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| 55 | ncvar.basicvardef(newvar, 'time', 'Time', tunits) |
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| 56 | ncvar.set_attribute(newvar, 'calendar', 'standard') |
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| 57 | newvar.setncattr('axis', 'T') |
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| 58 | newvar.setncattr('_CoordinateAxisType', 'Time') |
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| 59 | onewnc.sync() |
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| 60 | |
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| 61 | # station Variables |
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| 62 | Llab = len(lab) |
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| 63 | newvar = onewnc.createVariable('station', 'c', ('Lstring')) |
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| 64 | newvar[0:Llab] = lab[:] |
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| 65 | ncvar.basicvardef(newvar, 'station', 'Name of the station', '-') |
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| 66 | |
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| 67 | newvar = onewnc.createVariable('lon', 'f8') |
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| 68 | newvar[:] = lv |
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| 69 | ncvar.basicvardef(newvar, 'lon', 'Longitude', 'degrees_west') |
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| 70 | newvar.setncattr('axis', 'X') |
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| 71 | newvar.setncattr('_CoordinateAxisType', 'Lon') |
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| 72 | |
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| 73 | newvar = onewnc.createVariable('lat', 'f8') |
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| 74 | newvar[:] = Lv |
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| 75 | ncvar.basicvardef(newvar, 'lat', 'Latitude', 'degrees_north') |
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| 76 | newvar.setncattr('axis', 'Y') |
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| 77 | newvar.setncattr('_CoordinateAxisType', 'Lat') |
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| 78 | |
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| 79 | newvar = onewnc.createVariable('height', 'f8') |
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| 80 | newvar[:] = hv |
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| 81 | ncvar.basicvardef(newvar, 'height', 'Height', 'm') |
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| 82 | newvar.setncattr('axis', 'Z') |
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| 83 | newvar.setncattr('_CoordinateAxisType', 'Height') |
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| 84 | onewnc.sync() |
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| 85 | |
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| 86 | newvar = onewnc.createVariable('flon', 'f8') |
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| 87 | newvar[:] = lv |
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| 88 | ncvar.basicvardef(newvar, 'file_lon', 'Longitude closest grid-point from file', \ |
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| 89 | 'degrees_west') |
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| 90 | newvar.setncattr('axis', 'X') |
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| 91 | newvar.setncattr('_CoordinateAxisType', 'Lon') |
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| 92 | |
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| 93 | newvar = onewnc.createVariable('flat', 'f8') |
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| 94 | newvar[:] = Lv |
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| 95 | ncvar.basicvardef(newvar, 'file_lat', 'Latitude closest grid-point from file', \ |
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| 96 | 'degrees_north') |
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| 97 | newvar.setncattr('axis', 'Y') |
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| 98 | newvar.setncattr('_CoordinateAxisType', 'Lat') |
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| 99 | |
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| 100 | newvar = onewnc.createVariable('fheight', 'f8') |
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| 101 | newvar[:] = hv |
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| 102 | ncvar.basicvardef(newvar, 'file_height', 'Height closest grid-point from file', \ |
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| 103 | 'm') |
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| 104 | newvar.setncattr('axis', 'Z') |
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| 105 | newvar.setncattr('_CoordinateAxisType', 'Height') |
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| 106 | |
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| 107 | newvar = onewnc.createVariable('ipoint', 'i') |
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| 108 | newvar[:] = 0 |
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| 109 | ncvar.basicvardef(newvar, 'file_i', 'x-axis closest grid-point from file', '-') |
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| 110 | |
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| 111 | newvar = onewnc.createVariable('jpoint', 'i') |
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| 112 | newvar[:] = 0 |
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| 113 | ncvar.basicvardef(newvar, 'file_j', 'y-axis closest grid-point from file', '-') |
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| 114 | |
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| 115 | onewnc.sync() |
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| 116 | |
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| 117 | # Variables |
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| 118 | NOvarvals = np.ones((dimt), dtype=np.float)*gen.fillValueF |
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| 119 | for vn in sfcvars: |
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| 120 | CFvalues = gen.variables_values(vn) |
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| 121 | newvar = onewnc.createVariable(vn, 'f4', ('time'), fill_value=gen.fillValueF) |
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| 122 | newvar[:] = NOvarvals[:] |
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| 123 | ncvar.basicvardef(newvar, CFvalues[0], CFvalues[4].replace('|',' '), \ |
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| 124 | CFvalues[5]) |
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| 125 | |
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| 126 | # Global attributes |
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| 127 | ncvar.add_global_PyNCplot(onewnc, 'get_stations.py', fname, '0.1') |
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| 128 | ncvar.set_attribute(newvar, 'data_origin', 'SMN') |
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| 129 | |
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| 130 | onewnc.sync() |
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| 131 | onewnc.close() |
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| 132 | |
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| 133 | return |
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| 134 | |
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| 135 | def creation_sndstation_file(filen, lv, Lv, hv, lab, tunits, punits, ptime, sndvars, \ |
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| 136 | dimt, dimz, ifilen): |
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| 137 | """ Function to create the structure of the surface station file |
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| 138 | filen: name of the file |
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| 139 | lv: value of the longitude of the station |
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| 140 | Lv: value of the latitude of the station |
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| 141 | hv: value of the height of the station |
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| 142 | lab: label of the station |
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| 143 | tunits: uints of time |
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| 144 | punits: uints of pressure |
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| 145 | ptime: does pressure evolves in time? (True/False) |
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| 146 | sndvars: variables to be included |
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| 147 | dimt: quantity of time-steps |
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| 148 | dimz: quantity of vertical levels |
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| 149 | ifilen: name of the file from which data is retrieved |
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| 150 | """ |
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| 151 | fname = 'creation_sndstation_file' |
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| 152 | |
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| 153 | Lstring = 256 |
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| 154 | |
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| 155 | onewnc = NetCDFFile(filen, 'w') |
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| 156 | # Dimensions |
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| 157 | newdim = onewnc.createDimension('time', None) |
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| 158 | newdim = onewnc.createDimension('plev', dimz) |
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| 159 | newdim = onewnc.createDimension('Lstring', Lstring) |
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| 160 | |
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| 161 | # Variable-dimensions |
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| 162 | newvar = onewnc.createVariable('time', 'f8', ('time')) |
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| 163 | ncvar.basicvardef(newvar, 'time', 'Time', tunits) |
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| 164 | ncvar.set_attribute(newvar, 'calendar', 'standard') |
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| 165 | newvar.setncattr('axis', 'T') |
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| 166 | newvar.setncattr('_CoordinateAxisType', 'Time') |
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| 167 | |
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| 168 | if ptime: |
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| 169 | newvar = onewnc.createVariable('plev', 'f8', ('time','plev')) |
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| 170 | ncvar.basicvardef(newvar, 'plev', 'air pressure', punits) |
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| 171 | ncvar.set_attribute(newvar, 'down', 'up') |
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| 172 | newvar.setncattr('axis', 'Z') |
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| 173 | newvar.setncattr('_CoordinateAxisType', 'pressure') |
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| 174 | else: |
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| 175 | newvar = onewnc.createVariable('plev', 'f8', ('plev')) |
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| 176 | ncvar.basicvardef(newvar, 'plev', 'air pressure', punits) |
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| 177 | ncvar.set_attribute(newvar, 'down', 'up') |
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| 178 | newvar.setncattr('axis', 'Z') |
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| 179 | newvar.setncattr('_CoordinateAxisType', 'pressure') |
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| 180 | onewnc.sync() |
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| 181 | |
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| 182 | # station Variables |
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| 183 | Llab = len(lab) |
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| 184 | newvar = onewnc.createVariable('station', 'c', ('Lstring')) |
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| 185 | newvar[0:Llab] = lab[:] |
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| 186 | ncvar.basicvardef(newvar, 'station', 'Name of the station', '-') |
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| 187 | |
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| 188 | newvar = onewnc.createVariable('lon', 'f8') |
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| 189 | newvar[:] = lv |
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| 190 | ncvar.basicvardef(newvar, 'lon', 'Longitude', 'degrees_west') |
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| 191 | newvar.setncattr('axis', 'X') |
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| 192 | newvar.setncattr('_CoordinateAxisType', 'Lon') |
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| 193 | |
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| 194 | newvar = onewnc.createVariable('lat', 'f8') |
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| 195 | newvar[:] = Lv |
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| 196 | ncvar.basicvardef(newvar, 'lat', 'Latitude', 'degrees_north') |
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| 197 | newvar.setncattr('axis', 'Y') |
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| 198 | newvar.setncattr('_CoordinateAxisType', 'Lat') |
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| 199 | |
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| 200 | newvar = onewnc.createVariable('height', 'f8') |
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| 201 | newvar[:] = hv |
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| 202 | ncvar.basicvardef(newvar, 'height', 'Height', 'm') |
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| 203 | newvar.setncattr('axis', 'Z') |
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| 204 | newvar.setncattr('_CoordinateAxisType', 'Height') |
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| 205 | onewnc.sync() |
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| 206 | |
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| 207 | newvar = onewnc.createVariable('flon', 'f8') |
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| 208 | newvar[:] = lv |
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| 209 | ncvar.basicvardef(newvar, 'file_lon', 'Longitude closest grid-point from file', \ |
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| 210 | 'degrees_west') |
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| 211 | newvar.setncattr('axis', 'X') |
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| 212 | newvar.setncattr('_CoordinateAxisType', 'Lon') |
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| 213 | |
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| 214 | newvar = onewnc.createVariable('flat', 'f8') |
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| 215 | newvar[:] = Lv |
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| 216 | ncvar.basicvardef(newvar, 'file_lat', 'Latitude closest grid-point from file', \ |
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| 217 | 'degrees_north') |
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| 218 | newvar.setncattr('axis', 'Y') |
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| 219 | newvar.setncattr('_CoordinateAxisType', 'Lat') |
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| 220 | |
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| 221 | newvar = onewnc.createVariable('fheight', 'f8') |
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| 222 | newvar[:] = hv |
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| 223 | ncvar.basicvardef(newvar, 'file_height', 'Height closest grid-point from file', \ |
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| 224 | 'm') |
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| 225 | newvar.setncattr('axis', 'Z') |
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| 226 | newvar.setncattr('_CoordinateAxisType', 'Height') |
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| 227 | |
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| 228 | newvar = onewnc.createVariable('ipoint', 'i') |
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| 229 | newvar[:] = 0 |
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| 230 | ncvar.basicvardef(newvar, 'file_i', 'x-axis closest grid-point from file', '-') |
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| 231 | |
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| 232 | newvar = onewnc.createVariable('jpoint', 'i') |
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| 233 | newvar[:] = 0 |
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| 234 | ncvar.basicvardef(newvar, 'file_j', 'y-axis closest grid-point from file', '-') |
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| 235 | |
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| 236 | onewnc.sync() |
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| 237 | |
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| 238 | # Variables |
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| 239 | NOvarvals = np.ones((dimt,dimz), dtype=np.float)*gen.fillValueF |
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| 240 | for vn in sndvars: |
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| 241 | if not onewnc.variables.has_key(vn): |
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| 242 | CFvalues = gen.variables_values(vn) |
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| 243 | newvar = onewnc.createVariable(vn, 'f4', ('time', 'plev'), \ |
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| 244 | fill_value=gen.fillValueF) |
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| 245 | newvar[:] = NOvarvals[:] |
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| 246 | ncvar.basicvardef(newvar, CFvalues[0], CFvalues[4].replace('|',' '), \ |
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| 247 | CFvalues[5]) |
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| 248 | |
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| 249 | # Global attributes |
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| 250 | ncvar.add_global_PyNCplot(onewnc, 'get_stations.py', fname, '0.1') |
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| 251 | ncvar.set_attribute(newvar, 'data_origin', 'SMN') |
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| 252 | |
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| 253 | onewnc.sync() |
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| 254 | onewnc.close() |
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| 255 | |
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| 256 | return |
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| 257 | |
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| 258 | |
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| 259 | ####### ####### |
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| 260 | ## MAIN |
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| 261 | ####### |
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| 262 | |
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[1688] | 263 | Wcomputed = {} |
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| 264 | for vn in diag.Wavailablediags: |
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| 265 | Wcomputed[vn] = False |
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| 266 | |
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| 267 | Ccomputed = {} |
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| 268 | for vn in diag.Cavailablediags: |
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| 269 | Ccomputed[vn] = False |
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| 270 | |
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[1679] | 271 | yrref = ReferenceDate[0:4] |
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| 272 | monref = ReferenceDate[4:6] |
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| 273 | dayref = ReferenceDate[6:8] |
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| 274 | horref = ReferenceDate[8:10] |
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| 275 | minref = ReferenceDate[10:12] |
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| 276 | secref = ReferenceDate[12:14] |
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| 277 | |
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| 278 | utime = UnitsTime + ' since ' + yrref + '-' + monref + '-' + dayref + ' ' + horref + \ |
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| 279 | ':' + minref + ':' + secref |
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| 280 | |
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| 281 | # surface stations |
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[1692] | 282 | if sfcstatfile != 'None': |
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[1689] | 283 | osfcstatf = open(sfcstatfile, 'r') |
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[1679] | 284 | |
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[1689] | 285 | sfclonvals = [] |
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| 286 | sfclatvals = [] |
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| 287 | sfclabvals = [] |
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| 288 | sfchgtvals = [] |
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[1679] | 289 | |
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[1689] | 290 | for line in osfcstatf: |
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| 291 | if line[0:1] != comchar and len(line) > 1: |
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| 292 | vals = line.replace('\n','').split(sepchar) |
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| 293 | if not gen.searchInlist(missvalS, vals[sfcloncol]) and \ |
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| 294 | not gen.searchInlist(missvalS, vals[sfclatcol]): |
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| 295 | stlon = np.float(vals[sfcloncol]) |
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| 296 | stlat = np.float(vals[sfclatcol]) |
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| 297 | if stlon >= nlon and stlon <= xlon and stlat >= nlat and stlat <= xlat: |
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| 298 | sfclonvals.append(stlon) |
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| 299 | sfclatvals.append(stlat) |
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| 300 | sfclabvals.append(vals[sfclabcol]) |
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| 301 | if gen.searchInlist(missvalS, vals[sfchgtcol]): |
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| 302 | if vals[sfchgtcol] == '0': |
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| 303 | sfchgtvals.append(np.float(vals[sfchgtcol])) |
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| 304 | else: |
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| 305 | sfchgtvals.append(gen.fillValueF) |
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| 306 | else: |
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[1679] | 307 | sfchgtvals.append(np.float(vals[sfchgtcol])) |
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[1689] | 308 | |
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| 309 | osfcstatf.close() |
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| 310 | Nsfcstats = len(sfclonvals) |
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| 311 | print ' Number of surface stations: ', Nsfcstats |
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| 312 | else: |
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| 313 | Nsfcstats = 0 |
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| 314 | print ' No surface stations !!' |
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[1679] | 315 | |
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[1689] | 316 | # sounding stations |
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[1692] | 317 | if sndstatfile != 'None': |
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[1689] | 318 | osndstatf = open(sndstatfile, 'r') |
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[1679] | 319 | |
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[1689] | 320 | sndlonvals = [] |
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| 321 | sndlatvals = [] |
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| 322 | sndlabvals = [] |
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| 323 | sndhgtvals = [] |
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[1679] | 324 | |
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[1689] | 325 | for line in osndstatf: |
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| 326 | if line[0:1] != comchar and len(line) > 1: |
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| 327 | vals = line.replace('\n','').split(sepchar) |
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| 328 | if vals[sndloncol] != missvalS and vals[sndlatcol] != missvalS: |
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| 329 | stlon = np.float(vals[sndloncol]) |
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| 330 | stlat = np.float(vals[sndlatcol]) |
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| 331 | if stlon >= nlon and stlon <= xlon and stlat >= nlat and stlat <= xlat: |
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| 332 | sndlonvals.append(stlon) |
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| 333 | sndlatvals.append(stlat) |
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| 334 | sndlabvals.append(vals[sndlabcol]) |
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| 335 | sndhgtvals.append(np.float(vals[sndhgtcol])) |
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[1679] | 336 | |
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[1689] | 337 | osndstatf.close() |
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| 338 | Nsndstats = len(sndlonvals) |
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| 339 | print ' Number of sounding stations: ', Nsndstats |
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| 340 | else: |
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| 341 | Nsndstats = 0 |
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| 342 | print ' No sounding stations !!' |
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[1679] | 343 | |
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| 344 | |
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| 345 | if not os.path.isfile(simfilen): |
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| 346 | print gen.errormsg |
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| 347 | print " file '" + simfilen + "' does not exist !!" |
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| 348 | quit(-1) |
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| 349 | |
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| 350 | onc = NetCDFFile(simfilen, 'r') |
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| 351 | olistv = onc.variables.keys() |
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| 352 | olistv.sort() |
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| 353 | |
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| 354 | # Getting basic values for each dimension |
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| 355 | dimvarvalues = {} |
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| 356 | for dimn in dimvariables.keys(): |
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| 357 | varn = dimvariables[dimn] |
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| 358 | if not gen.searchInlist(NONcheckingvars, varn) and not gen.searchInlist(olistv, varn): |
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| 359 | print gen.errormsg |
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| 360 | print " file '" + simfilen + "' does not have variable '" + varn + "' !!" |
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| 361 | print ' available ones: ', olistv |
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| 362 | quit(-1) |
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| 363 | |
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[1694] | 364 | if not gen.searchInlist(NONcheckingvars, varn): |
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| 365 | # Except for temporal variables, we don't want dimensions with time-axis |
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| 366 | # (assuming fixed) |
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| 367 | if varn == 'WRFtime': |
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| 368 | varvalues, CFtu = ncvar.compute_WRFtime(onc.variables['Times'], \ |
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| 369 | ReferenceDate, UnitsTime) |
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| 370 | dt = varvalues.shape[0] |
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| 371 | dimvarvalues[varn] = varvalues |
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[1679] | 372 | else: |
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[1694] | 373 | ovar = onc.variables[varn] |
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| 374 | slicevar = {} |
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| 375 | if not gen.searchInlist(axesvars['T'], varn): |
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| 376 | for dn in ovar.dimensions: |
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| 377 | if not gen.searchInlist(axesdims['T'], dn): |
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| 378 | slicevar[dn] = -1 |
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| 379 | else: |
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| 380 | slicevar[dn] = 0 |
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| 381 | else: |
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| 382 | slicevar[dn] = -1 |
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| 383 | dt = len(onc.dimensions[dn]) |
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| 384 | slicevar, vardims = ncvar.SliceVarDict(ovar, slicevar) |
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| 385 | dimvarvalues[varn] = ovar[tuple(slicevar)] |
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[1679] | 386 | |
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| 387 | if dimn == Pressdimref: dz = len(onc.dimensions[dimn]) |
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| 388 | |
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[1694] | 389 | # Looking for 2D 'lon', 'lat' related variables |
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| 390 | Xvarvals = dimvarvalues[dimvariables['lon']] |
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| 391 | Yvarvals = dimvarvalues[dimvariables['lat']] |
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| 392 | if len(Xvarvals.shape) == 1: |
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| 393 | newXvarvals, newYvarvals = np.meshgrid(Xvarvals, Yvarvals) |
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| 394 | dimvarvalues[dimvariables['lon']] = newXvarvals |
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| 395 | dimvarvalues[dimvariables['lat']] = newYvarvals |
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| 396 | |
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[1679] | 397 | # Retrieving surface data |
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| 398 | ## |
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| 399 | |
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| 400 | # Diagnosted variables |
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| 401 | diagvars = {} |
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| 402 | |
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| 403 | # Coinident surface station |
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| 404 | sfccoinc = {} |
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| 405 | |
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| 406 | for ist in range(Nsfcstats): |
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| 407 | jumpstation = False |
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| 408 | |
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| 409 | lonv = sfclonvals[ist] |
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| 410 | latv = sfclatvals[ist] |
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| 411 | labelv = sfclabvals[ist] |
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| 412 | heightv = sfchgtvals[ist] |
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| 413 | |
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| 414 | stfilen = 'sfc_station_' + labelv + '.nc' |
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| 415 | |
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| 416 | creation_sfcstation_file(stfilen, lonv, latv, heightv, labelv, utime, \ |
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| 417 | sfcvariables.keys(), dt, simfilen) |
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| 418 | |
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| 419 | onewnc = NetCDFFile(stfilen, 'a') |
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| 420 | |
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| 421 | stationsji = np.ones((Nsfcstats,2), dtype=int)*gen.fillValueI |
---|
| 422 | coincstats = np.ones((Nsfcstats), dtype=int)*gen.fillValueI |
---|
| 423 | |
---|
| 424 | for sfcv in sfcvariables.keys(): |
---|
| 425 | fvn = sfcvariables[sfcv] |
---|
| 426 | if not gen.searchInlist(NONcheckingvars,fvn) and \ |
---|
| 427 | not onewnc.variables.has_key(sfcv): |
---|
| 428 | print gen.errormsg |
---|
| 429 | print " Newfile for the station '" + stfilen + "' does not content " + \ |
---|
| 430 | " variable '" + sfcv + "' !!" |
---|
| 431 | print ' variables:', onewnc.variables.keys() |
---|
| 432 | quit(-1) |
---|
| 433 | |
---|
| 434 | if not gen.searchInlist(NONcheckingvars,fvn): |
---|
| 435 | ogetvar = onc.variables[fvn] |
---|
| 436 | getdims = ogetvar.dimensions |
---|
| 437 | else: |
---|
[1694] | 438 | getdims = list(onc.variables[sfcrefvar].dimensions) |
---|
| 439 | getvdims = [dimvariables[getdims[0]], dimvariables[getdims[1]], \ |
---|
| 440 | dimvariables[getdims[2]]] |
---|
[1679] | 441 | |
---|
| 442 | # Looking for the X,Y axis for location of station within file |
---|
| 443 | for dn in getdims: |
---|
| 444 | axis = gen.dictionary_key_list(axesdims, dn) |
---|
| 445 | if not dimvariables.has_key(dn): |
---|
| 446 | print gen.errormsg |
---|
| 447 | print " dimension '" + dn + "' not ready in 'dimvariables' !!" |
---|
| 448 | print ' add it to proceed' |
---|
| 449 | quit(-1) |
---|
| 450 | if axis == 'X': |
---|
| 451 | lvals = dimvarvalues[dimvariables[dn]] |
---|
| 452 | xdiff = (lvals-lonv)**2 |
---|
| 453 | elif axis == 'Y': |
---|
| 454 | Lvals = dimvarvalues[dimvariables[dn]] |
---|
| 455 | ydiff = (Lvals-latv)**2 |
---|
| 456 | |
---|
| 457 | # Looking for the closest point |
---|
| 458 | diff = np.sqrt(xdiff + ydiff) |
---|
| 459 | mindiff = np.min(diff) |
---|
| 460 | minji = gen.index_mat(diff, mindiff) |
---|
| 461 | |
---|
| 462 | coincstats = (stationsji[:,0] - minji[0]) + (stationsji[:,1] - minji[1]) |
---|
| 463 | if np.any(coincstats == 0): |
---|
| 464 | print ' Surface station coincidence by closest grid point from file !!' |
---|
| 465 | iist = gen.index_vec(coincstats, 0) |
---|
| 466 | print ' ' + labelv, '&', sfclabvals[iist] |
---|
| 467 | onewnc.close() |
---|
| 468 | sub.call('rm ' + stfilen, shell=True) |
---|
| 469 | sub.call('cp ' + 'sfc_station_' + sfclabvals[iist] + '.nc ' + stfilen, \ |
---|
| 470 | shell=True) |
---|
| 471 | onewnc = NetCDFFile(stfilen, 'a') |
---|
| 472 | ostlab = onewnc.variables['station'] |
---|
| 473 | Llab = len(labelv) |
---|
| 474 | ostlab[0:Llab] = labelv |
---|
| 475 | onewnc.sync() |
---|
| 476 | onewnc.close() |
---|
| 477 | if sfccoinc.has_key(sfclabvals[iist]): |
---|
| 478 | lvals = sfccoinc[sfclabvals[iist]] |
---|
| 479 | lvals.append(labelv) |
---|
| 480 | sfccoinc[sfclabvals[iist]] = lvals |
---|
| 481 | else: |
---|
| 482 | sfccoinc[sfclabvals[iist]] = [labelv] |
---|
| 483 | continue |
---|
| 484 | |
---|
| 485 | # Writting information to file |
---|
| 486 | if sfcv == sfcrefvar: |
---|
| 487 | ojvar = onewnc.variables['jpoint'] |
---|
| 488 | ojvar[:] = minji[0] |
---|
| 489 | ojvar = onewnc.variables['ipoint'] |
---|
| 490 | ojvar[:] = minji[1] |
---|
[1692] | 491 | ohvar = onewnc.variables['fheight'] |
---|
| 492 | ohvar[:] = dimvarvalues[dimvariables['H']][minji[0],minji[1]] |
---|
[1679] | 493 | onewnc.sync() |
---|
| 494 | |
---|
| 495 | # Computing a single time the diagnosted variables |
---|
| 496 | if gen.searchInlist(NONcheckingvars,fvn): |
---|
| 497 | if ist == 0: |
---|
[1688] | 498 | if fvn[0:3] == 'WRF': |
---|
| 499 | fvn_diag = fvn[3:len(fvn)] |
---|
| 500 | if not Wcomputed[fvn_diag]: |
---|
| 501 | # Using a given series of prepared diagnostics |
---|
| 502 | Wcomputed[fvn_diag] = True |
---|
| 503 | vardiag = diag.W_diagnostic(fvn_diag, onc, \ |
---|
| 504 | sfcvariables, sndvariables, getdims, getvdims, CFdims) |
---|
| 505 | diagvars[fvn] = vardiag.values |
---|
| 506 | elif fvn[0:2] == 'C_': |
---|
| 507 | fvn_diag = fvn.split('_')[1] |
---|
| 508 | if not Ccomputed[fvn_diag]: |
---|
| 509 | # Using a given series of prepared diagnostics |
---|
| 510 | Ccomputed[fvn_diag] = True |
---|
| 511 | vardiag = C_diagnostic(fvn_diag, onc, sfcvariables, \ |
---|
| 512 | sndvariables, CFdims) |
---|
| 513 | diagvars[fvn] = vardiag.values |
---|
| 514 | ogetvar = diagvars[fvn] |
---|
[1679] | 515 | else: |
---|
| 516 | ogetvar = diagvars[fvn] |
---|
| 517 | |
---|
| 518 | slicevar = [] |
---|
| 519 | for dn in getdims: |
---|
| 520 | axis = gen.dictionary_key_list(axesdims, dn) |
---|
| 521 | if axis == 'X': slicevar.append(minji[1]) |
---|
| 522 | elif axis == 'Y': slicevar.append(minji[0]) |
---|
| 523 | else: slicevar.append(slice(0,len(onc.dimensions[dn]))) |
---|
| 524 | |
---|
| 525 | # Writting data and slicing |
---|
| 526 | onewvar = onewnc.variables[sfcv] |
---|
| 527 | onewvar[:] = ogetvar[tuple(slicevar)] |
---|
| 528 | onewnc.sync() |
---|
| 529 | |
---|
| 530 | if jumpstation: continue |
---|
| 531 | |
---|
| 532 | onewnc.close() |
---|
| 533 | |
---|
| 534 | if len(sfccoinc.keys()) > 0: |
---|
| 535 | print 'Coincident surface stations _______' |
---|
| 536 | gen.printing_dictionary(sfccoinc) |
---|
| 537 | |
---|
| 538 | # Retrieving sounding data |
---|
| 539 | |
---|
| 540 | # Diagnosted variables |
---|
| 541 | diagvars = {} |
---|
| 542 | |
---|
| 543 | # Coinident sounding station |
---|
| 544 | sndcoinc = {} |
---|
| 545 | |
---|
| 546 | for ist in range(Nsndstats): |
---|
| 547 | jumpstation = False |
---|
| 548 | |
---|
| 549 | lonv = sndlonvals[ist] |
---|
| 550 | latv = sndlatvals[ist] |
---|
| 551 | labelv = sndlabvals[ist] |
---|
| 552 | heightv = sndhgtvals[ist] |
---|
| 553 | |
---|
| 554 | stfilen = 'snd_station_' + labelv + '.nc' |
---|
| 555 | |
---|
| 556 | creation_sndstation_file(stfilen, lonv, latv, heightv, labelv, utime, UnitsPress,\ |
---|
| 557 | presstime, sndvariables.keys(), dt, dz, simfilen) |
---|
| 558 | |
---|
| 559 | onewnc = NetCDFFile(stfilen, 'a') |
---|
| 560 | |
---|
| 561 | stationsji = np.ones((Nsfcstats,2), dtype=int)*gen.fillValueI |
---|
| 562 | coincstats = np.ones((Nsfcstats), dtype=int)*gen.fillValueI |
---|
| 563 | |
---|
| 564 | for sndv in sndvariables.keys(): |
---|
| 565 | fvn = sndvariables[sndv] |
---|
| 566 | if not gen.searchInlist(NONcheckingvars,fvn) and \ |
---|
| 567 | not onewnc.variables.has_key(sndv): |
---|
| 568 | print gen.errormsg |
---|
| 569 | print " Newfile for the station '" + stfilen + "' does not content " + \ |
---|
| 570 | " variable '" + sndv + "' !!" |
---|
| 571 | print ' variables:', onewnc.variables.keys() |
---|
| 572 | quit(-1) |
---|
| 573 | |
---|
| 574 | if not gen.searchInlist(NONcheckingvars,fvn): |
---|
| 575 | ogetvar = onc.variables[fvn] |
---|
| 576 | getdims = ogetvar.dimensions |
---|
| 577 | else: |
---|
[1694] | 578 | getdims = list(onc.variables[sndrefvar].dimensions) |
---|
| 579 | getvdims = [dimvariables[getdims[0]], dimvariables[getdims[1]], \ |
---|
| 580 | dimvariables[getdims[2]], dimvariables[getdims[3]]] |
---|
[1679] | 581 | |
---|
| 582 | # Looking for the X,Y axis for location of station within file |
---|
| 583 | for dn in getdims: |
---|
| 584 | axis = gen.dictionary_key_list(axesdims, dn) |
---|
| 585 | if not dimvariables.has_key(dn): |
---|
| 586 | print gen.errormsg |
---|
| 587 | print " dimension '" + dn + "' not ready in 'dimvariables' !!" |
---|
| 588 | print ' add it to proceed' |
---|
| 589 | quit(-1) |
---|
| 590 | if axis == 'X': |
---|
| 591 | lvals = dimvarvalues[dimvariables[dn]] |
---|
| 592 | xdiff = (lvals-lonv)**2 |
---|
| 593 | elif axis == 'Y': |
---|
| 594 | Lvals = dimvarvalues[dimvariables[dn]] |
---|
| 595 | ydiff = (Lvals-latv)**2 |
---|
| 596 | |
---|
| 597 | # Looking for the closest point |
---|
| 598 | diff = np.sqrt(xdiff + ydiff) |
---|
| 599 | mindiff = np.min(diff) |
---|
| 600 | minji = gen.index_mat(diff, mindiff) |
---|
| 601 | |
---|
| 602 | coincstats = (stationsji[:,0] - minji[0]) + (stationsji[:,1] - minji[1]) |
---|
| 603 | if np.any(coincstats == 0): |
---|
| 604 | print ' Sounding station coincidence by closest grid point from file !!' |
---|
| 605 | iist = gen.index_vec(coincstats, 0) |
---|
| 606 | print ' ' + labelv, '&', sndlabvals[iist] |
---|
| 607 | onewnc.close() |
---|
| 608 | sub.call('rm ' + stfilen, shell=True) |
---|
| 609 | sub.call('cp ' + 'snd_station_' + sndlabvals[iist] + '.nc ' + stfilen, \ |
---|
| 610 | shell=True) |
---|
| 611 | onewnc = NetCDFFile(stfilen, 'a') |
---|
| 612 | ostlab = onewnc.variables['station'] |
---|
| 613 | Llab = len(labelv) |
---|
| 614 | ostlab[0:Llab] = labelv |
---|
| 615 | onewnc.sync() |
---|
| 616 | onewnc.close() |
---|
| 617 | if sndcoinc.has_key(sndlabvals[iist]): |
---|
| 618 | lvals = sfccoinc[sndlabvals[iist]] |
---|
| 619 | lvals.append(labelv) |
---|
| 620 | sndcoinc[sndlabvals[iist]] = lvals |
---|
| 621 | else: |
---|
| 622 | sndcoinc[sndlabvals[iist]] = [labelv] |
---|
| 623 | continue |
---|
| 624 | |
---|
| 625 | # Writting information to file |
---|
[1694] | 626 | if sndv == sndrefvar: |
---|
[1679] | 627 | ojvar = onewnc.variables['jpoint'] |
---|
| 628 | ojvar[:] = minji[0] |
---|
| 629 | ojvar = onewnc.variables['ipoint'] |
---|
| 630 | ojvar[:] = minji[1] |
---|
[1694] | 631 | if dimvariables['H'] != 'None': |
---|
| 632 | ohvar = onewnc.variables['fheight'] |
---|
| 633 | ohvar[:] = dimvarvalues[dimvariables['H']][minji[0],minji[1]] |
---|
[1679] | 634 | onewnc.sync() |
---|
| 635 | |
---|
| 636 | # Computing a single time the diagnosted variables |
---|
| 637 | if gen.searchInlist(NONcheckingvars,fvn): |
---|
| 638 | if ist == 0: |
---|
[1688] | 639 | if fvn[0:3] == 'WRF': |
---|
| 640 | fvn_diag = fvn[3:len(fvn)] |
---|
| 641 | if not Wcomputed[fvn_diag]: |
---|
| 642 | # Using a given series of prepared diagnostics |
---|
| 643 | Wcomputed[fvn_diag] = True |
---|
| 644 | vardiag = diag.W_diagnostic(fvn_diag, onc, \ |
---|
| 645 | sfcvariables, sndvariables, getdims, getvdims, CFdims) |
---|
| 646 | diagvars[fvn] = vardiag.values |
---|
| 647 | elif fvn[0:2] == 'C_': |
---|
| 648 | fvn_diag = fvn.split('_')[1] |
---|
| 649 | if not Ccomputed[fvn_diag]: |
---|
| 650 | # Using a given series of prepared diagnostics |
---|
| 651 | Ccomputed[fvn_diag] = True |
---|
| 652 | vardiag = diag.C_diagnostic(fvn_diag, onc, sfcvariables, \ |
---|
| 653 | sndvariables, CFdims) |
---|
| 654 | diagvars[fvn] = vardiag.values |
---|
| 655 | |
---|
[1679] | 656 | ogetvar = diagvars[fvn] |
---|
| 657 | else: |
---|
| 658 | ogetvar = diagvars[fvn] |
---|
| 659 | |
---|
| 660 | slicevar = [] |
---|
| 661 | for dn in getdims: |
---|
| 662 | axis = gen.dictionary_key_list(axesdims, dn) |
---|
| 663 | if axis == 'X': slicevar.append(minji[1]) |
---|
| 664 | elif axis == 'Y': slicevar.append(minji[0]) |
---|
| 665 | else: slicevar.append(slice(0,len(onc.dimensions[dn]))) |
---|
| 666 | |
---|
| 667 | # Writting data and slicing |
---|
| 668 | onewvar = onewnc.variables[sndv] |
---|
[1694] | 669 | print 'Lluis sndv:', sndv, ' shapes onewvar:', onewvar.shape, 'slice:', slicevar |
---|
[1679] | 670 | onewvar[:] = ogetvar[tuple(slicevar)] |
---|
| 671 | onewnc.sync() |
---|
| 672 | |
---|
| 673 | if jumpstation: continue |
---|
| 674 | |
---|
| 675 | onewnc.close() |
---|
| 676 | |
---|
| 677 | if len(sndcoinc.keys()) > 0: |
---|
| 678 | print 'Coincident sounding stations _______' |
---|
| 679 | gen.printing_dictionary(sndcoinc) |
---|
| 680 | |
---|