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1 import netCDF4
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2 from netCDF4 import Dataset
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3 import numpy as np
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4 import matplotlib
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5 matplotlib.use("Agg")
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6 import matplotlib.pyplot as plt
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7 from pylab import *
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8 import sys
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9 import os
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10 from scipy import spatial
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11 from math import radians, cos, sin, asin, sqrt
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12 import itertools
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13
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14 #####################
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15 #####################
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16
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17 def checklist(dim_list, dim_name, filtre, threshold):
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18 if not dim_list:
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19 error="Error "+str(dim_name)+" has no value "+str(filtre)+" "+str(threshold)
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20 sys.exit(error)
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21
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22
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23 #Return dist in km between two coord
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24 #Thx to : https://stackoverflow.com/questions/4913349/haversine-formula-in-python-bearing-and-distance-between-two-gps-points
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25 def haversine(lon1, lat1, lon2, lat2):
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26 """
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27 Calculate the great circle distance between two points
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28 on the earth (specified in decimal degrees)
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29 """
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30 # convert decimal degrees to radians
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31 lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
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32
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33 # haversine formula
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34 dlon = lon2 - lon1
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35 dlat = lat2 - lat1
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36 a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
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37 c = 2 * asin(sqrt(a))
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38 r = 6371 # Radius of earth in kilometers. Use 3956 for miles
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39 return c * r
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40
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41
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42 #Comparison functions, return a list of indexes for the user conditions
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43 def is_strict_inf(filename, dim_name, threshold):
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44 list_dim=[]
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45 for i in range(0,filename.variables[dim_name].size):
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46 if filename.variables[dim_name][i] < threshold:
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47 list_dim.append(i)
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48 checklist(list_dim,dim_name,"<",threshold)
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49 return list_dim
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50
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51 def is_equal_inf(filename, dim_name, threshold):
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52 list_dim=[]
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53 for i in range(0,filename.variables[dim_name].size):
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54 if filename.variables[dim_name][i] <= threshold:
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55 list_dim.append(i)
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56 checklist(list_dim,dim_name,"<=",threshold)
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57 return list_dim
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58
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59 def is_equal_sup(filename, dim_name, threshold):
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60 list_dim=[]
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61 for i in range(0,filename.variables[dim_name].size):
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62 if filename.variables[dim_name][i] >= threshold:
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63 list_dim.append(i)
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64 checklist(list_dim,dim_name,">=",threshold)
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65 return list_dim
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66
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67 def is_strict_sup(filename, dim_name, threshold):
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68 list_dim=[]
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69 for i in range(0,filename.variables[dim_name].size):
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70 if filename.variables[dim_name][i] > threshold:
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71 list_dim.append(i)
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72 checklist(list_dim,dim_name,">",threshold)
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73 return list_dim
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74
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75 def find_nearest(array,value):
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76 index = (np.abs(array-value)).argmin()
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77 return index
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78
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79 def is_equal(filename, dim_name, value):
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80 try:
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81 index=filename.variables[dim_name][:].tolist().index(value)
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82 except:
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83 index=find_nearest(filename.variables[dim_name][:],value)
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84 return index
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85
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86 def is_between_include(filename, dim_name, threshold1, threshold2):
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87 list_dim=[]
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88 for i in range(0,filename.variables[dim_name].size):
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89 if filename.variables[dim_name][i] >= threshold1 and filename.variables[dim_name][i] <= threshold2:
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90 list_dim.append(i)
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91 checklist(list_dim,dim_name,">=",threshold1)
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92 checklist(list_dim,dim_name,"=<",threshold2)
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93 return list_dim
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94
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95 def is_between_exclude(filename, dim_name, threshold1, threshold2):
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96 list_dim=[]
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97 for i in range(0,filename.variables[dim_name].size):
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98 if filename.variables[dim_name][i] > threshold1 and filename.variables[dim_name][i] < threshold2:
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99 list_dim.append(i)
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100 checklist(list_dim,dim_name,">",threshold1)
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101 checklist(list_dim,dim_name,"<",threshold2)
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102 return list_dim
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103
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104 #######################
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105 #######################
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106
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107 #Get args
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108 #Get Input file
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109 inputfile=Dataset(sys.argv[1])
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110 var_file_tab=sys.argv[2]
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111 var=sys.argv[3] #Var chosen by user
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112
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113 Coord_bool=False
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114
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115
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116 ######################
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117 ######################
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118 #len_threshold=1000000
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119 len_threshold=7000
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120 x_percent=0.75
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121 threshold_latlon=100
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122
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123
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124 #Check if coord is passed as parameter
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125 arg_n=len(sys.argv)-1
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126 if(((arg_n-3)%3)!=0):
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127 Coord_bool=True #Useful to get closest coord
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128 arg_n=arg_n-4 #Number of arg minus lat & lon
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129 name_dim_lat=str(sys.argv[-4])
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130 name_dim_lon=str(sys.argv[-2])
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131 value_dim_lat=float(sys.argv[-3])
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132 value_dim_lon=float(sys.argv[-1])
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133
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134 #Get all lat & lon
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135 #try:
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136 if True:
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137 latitude=np.ma.MaskedArray(inputfile.variables[name_dim_lat])
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138 longitude=np.ma.MaskedArray(inputfile.variables[name_dim_lon])
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139 lat=latitude;lon=longitude #Usefull to keep the originals lat/lon vect before potentially resize it bellow.
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140 len_all_coord=len(lat)*len(lon)
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141
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142 #print("len all coord "+str(len_all_coord)+" threshold "+str(len_threshold))
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143
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144 #To avoid case when all_coord is to big and need to much memory
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145 #If the vector is too big, reduce it to its third in a loop until its < to the threshold
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146 while len_all_coord > len_threshold:
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147
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148 if len(lat)<threshold_latlon: #If lat and lon are very different and lon is >> than lat. This way only lon is reduce and not lat.
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149 x_percent_len_lat=99999999
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150 else:
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151 x_percent_len_lat=int(x_percent*len(lat))
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152
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153 if len(lon)<threshold_latlon: #If lat and lon are very different and lat is >> than lon. This way only lat is reduce and not lon.
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154 x_percent_len_lon=99999999
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155 else:
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156 x_percent_len_lon=int(x_percent*len(lon))
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157
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158 #print("len(lat) :"+str(len(lat))+" x_percent_len_lat "+str(x_percent_len_lat))
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159 #print("len(lon) :"+str(len(lon))+" x_percent_len_lon "+str(x_percent_len_lon))
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160
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161
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162 pos_lat_user=find_nearest(lat,value_dim_lat)
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163 pos_lon_user=find_nearest(lon,value_dim_lon)
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164
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165
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166 #This part is to avoid having a vector that start bellow 0
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167 lat_reduced=int(pos_lat_user-x_percent_len_lat/2-1)
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168 if lat_reduced<0:
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169 lat_reduced=0
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170 lon_reduced=int(pos_lon_user-x_percent_len_lon/2-1)
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171 if lon_reduced<0:
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172 lon_reduced=0
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173 #Opposite here to avoid having vector with len > to len(vector)
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174 lat_extended=int(pos_lat_user+x_percent_len_lat/2-1)
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175 if lat_extended>len(lat):
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176 lat_extended=len(lat)
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177 lon_extended=int(pos_lon_user+x_percent_len_lon/2-1)
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178 if lon_extended>len(lon):
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179 lon_extended=len(lon)
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180
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181 lat=lat[lat_reduced:lat_extended] #add a test to check if pos_lat_user-x_percent_len_lat/2-1 >0
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182 lon=lon[lon_reduced:lon_extended]
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183 #print("latreduced : "+str(lat_reduced)+" latextended "+str(lat_extended))
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184 #print("lonreduced : "+str(lon_reduced)+" lonextended "+str(lon_extended))
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185 #print("lat : "+str(lat))
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186 #print("lon : "+str(lon))
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187 len_all_coord=len(lat)*len(lon)
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188
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189 #print ("len_all_coord : "+str(len_all_coord)+". len_lat : "+str(len(lat))+" .len_lon : "+str(len(lon)))
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190
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191 else:
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192 #except:
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193 sys.exit("Latitude & Longitude not found")
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194
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195 #Set all lat-lon pair avaible in list_coord
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196 list_coord_dispo=[]
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197 for i in lat:
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198 for j in lon:
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199 list_coord_dispo.append(i);list_coord_dispo.append(j)
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200
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201 #Reshape
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202 all_coord=np.reshape(list_coord_dispo,(lat.size*lon.size,2))
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203 #np.set_printoptions(threshold='nan')#to print full vec
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204 #print(str(all_coord))
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205 noval=True
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206
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207
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208
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209 #########################
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210 #########################
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211
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212
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213 #Get the file of variables and number of dims : var.tab
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214 var_file=open(var_file_tab,"r") #read
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215 lines=var_file.readlines() #line
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216 dim_names=[]
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217 for line in lines: #for every lines
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218 words=line.split()
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219 if (words[0]==var): #When line match user input var
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220 varndim=int(words[1]) #Get number of dim for the var
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221 for dim in range(2,varndim*2+2,2): #Get dim names
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222 dim_names.append(words[dim])
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223 #print ("Chosen var : "+sys.argv[3]+". Number of dimensions : "+str(varndim)+". Dimensions : "+str(dim_names)) #Standard msg
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224
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225
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226 ########################
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227 ########################
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228
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229
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230 #Use a dictionary to save every lists of indexes
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231 my_dic={} ##d["string{0}".format(x)]
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232
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233 for i in range(4,arg_n,3):
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234 #print("\nDimension name : "+sys.argv[i]+" action : "+sys.argv[i+1]+" .Value : "+sys.argv[i+2]+"\n") #Standard msg
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235
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236 #Check if the dim selected for filtering is present in the var dimensions.
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237 if (sys.argv[i] not in dim_names):
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238 print("Warning ! "+sys.argv[i]+" is not a dimension of "+var+".\nThis filter will be skipped\nCheck in the file \"variables\" the dimensions available.\n\n")
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239 pass
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240
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241 my_dic["string{0}".format(i)]="list_index_dim"
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242 my_dic_index="list_index_dim"+str(sys.argv[i]) #Possible improvement: Check if lon/lat are not parsed again
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243
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244 #Apply every user filter. Call function and return list of index wich validate condition for every dim.
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245 if (sys.argv[i+1]=="l"): #<
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246 my_dic[my_dic_index]=is_strict_inf(inputfile, sys.argv[i], float(sys.argv[i+2]))
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247 if (sys.argv[i+1]=="le"): #<=
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248 my_dic[my_dic_index]=is_equal_inf(inputfile, sys.argv[i], float(sys.argv[i+2]))
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249 if (sys.argv[i+1]=="g"): #>
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250 my_dic[my_dic_index]=is_strict_sup(inputfile, sys.argv[i], float(sys.argv[i+2]))
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251 if (sys.argv[i+1]=="ge"): #>=
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252 my_dic[my_dic_index]=is_equal_sup(inputfile, sys.argv[i], float(sys.argv[i+2]))
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253 if (sys.argv[i+1]=="e"): #==
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254 my_dic[my_dic_index]=is_equal(inputfile, sys.argv[i], float(sys.argv[i+2]))
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255 if (sys.argv[i+1]==":"): #all
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256 my_dic[my_dic_index]=np.arange(inputfile.variables[sys.argv[i]].size)
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257 if (sys.argv[i+1]=="be"): #between_exclude
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258 #Get the 2 thresholds from the arg which looks like "threshold1-threshold2"
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259 threshold1=sys.argv[i+2].split("-")[0]
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260 threshold2=sys.argv[i+2].split("-")[1]
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261 my_dic[my_dic_index]=is_between_exclude(inputfile, sys.argv[i], float(threshold1), float(threshold2))
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262 if (sys.argv[i+1]=="bi"): #between_include
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263 #Get the 2 thresholds from the arg which looks like "threshold1-threshold2"
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264 threshold1=sys.argv[i+2].split("-")[0]
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265 threshold2=sys.argv[i+2].split("-")[1]
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266 my_dic[my_dic_index]=is_between_include(inputfile, sys.argv[i], float(threshold1), float(threshold2))
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267
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268 #####################
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269 #####################
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270
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271
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272 #If precise coord given.
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273 if Coord_bool:
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274 while noval: #While no closest coord with valid values is found
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275 #Return closest coord avaible
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276 tree=spatial.KDTree(all_coord)
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277 closest_coord=(tree.query([(value_dim_lat,value_dim_lon)]))
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278 cc_index=closest_coord[1]
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279
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280 closest_lat=float(all_coord[closest_coord[1]][0][0])
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281 closest_lon=float(all_coord[closest_coord[1]][0][1])
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282
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283 #Get coord index into dictionary
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284 my_dic_index="list_index_dim"+str(name_dim_lat)
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285 my_dic[my_dic_index]=latitude.tolist().index(closest_lat)
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286
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287 my_dic_index="list_index_dim"+str(name_dim_lon)
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288 my_dic[my_dic_index]=longitude.tolist().index(closest_lon)
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289
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290
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291 #All dictionary are saved in the string exec2 which will be exec(). Value got are in vec2
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292 exec2="vec2=inputfile.variables['"+var+"']["
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293 first=True
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294 for i in dim_names: #Every dim are in the right order
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295 if not first:
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296 exec2=exec2+","
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297 dimension_indexes="my_dic[\"list_index_dim"+i+"\"]" #new dim, custom name dic
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298 try: #If some error or no specific user choices; every indexes are used for the selected dim.
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299 exec(dimension_indexes)
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300 except:
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301 dimension_indexes=":"
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302 exec2=exec2+dimension_indexes #Concatenate dim
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303 first=False #Not the first element now
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304 exec2=exec2+"]"
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305 #print exec2 #To check integrity of the string
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306 exec(exec2) #Execution, value are in vec2.
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307 #print vec2 #Get the value, standard output
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308
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309 #Check integrity of vec2. We don't want NA values
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310 i=0
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311 #Check every value, if at least one non NA is found vec2 and the current closest coords are validated
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312 vecsize=vec2.size
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313 #print (str(vecsize))
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314 if vecsize>1:
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315 while i<vecsize:
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316 #print (str(vec2))
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317 if vec2[i]!="nan":
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318 break
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319 else:
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320 i=i+1
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321 else:
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322 if vec2!="nan":
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323 break
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324 else:
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325 i=i+1
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326
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327 if i<vecsize: #There is at least 1 nonNA value
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328 noval=False
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329 else: #If only NA : pop the closest coord and search in the second closest coord in the next loop.
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330 all_coord=np.delete(all_coord,cc_index,0)
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331
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332
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333 #Same as before, dictionary use in exec2. exec(exec2) give vec2 and the values wanted.
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334 else:
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335 exec2="vec2=inputfile.variables['"+str(sys.argv[3])+"']["
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336 first=True
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337 for i in dim_names: #Respect order
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338 if not first:
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339 exec2=exec2+","
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340 dimension_indexes="my_dic[\"list_index_dim"+i+"\"]"
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341 try: #Avoid error and exit
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342 exec(dimension_indexes)
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343 except:
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344 dimension_indexes=":"
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345 exec2=exec2+dimension_indexes
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346 first=False
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347 exec2=exec2+"]"
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348 exec(exec2)
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349
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350
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351 ########################
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352 ########################
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353
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354
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355 #This part create the header of every value.
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356 #Values of every dim from the var is saved in a list : b[].
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357 #All the lists b are saved in the unique list a[]
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358 #All the combinations of the dim values inside a[] are the headers of the vec2 values
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359
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360 #Also write dim_name into a file to make clear header.
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361 fo=open("header_names",'w')
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362
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363 a=[]
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364 for i in dim_names:
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365 try: #If it doesn't work here its because my_dic= : so there is no size. Except will direcly take size of the dim.
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366 size_dim=inputfile[i][my_dic['list_index_dim'+i]].size
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367 except:
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368 size_dim=inputfile[i].size
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369 my_dic['list_index_dim'+i]=range(size_dim)
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370
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371 #print (i,size_dim) #Standard msg
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372 b=[]
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373 #Check size is useful since b.append(inputfile[i][my_dic['list_index_dim'+i][0]]) won't work
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374 if size_dim>1:
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375 for s in range(0,size_dim):
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376 b.append(inputfile[i][my_dic['list_index_dim'+i][s]])
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377 #print (i,inputfile[i][my_dic['list_index_dim'+i][s]])
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378 else:
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379 b.append(inputfile[i][my_dic['list_index_dim'+i]])
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380 #print (i,inputfile[i][my_dic['list_index_dim'+i]])
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381
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382 a.append(b)
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383 fo.write(i+"\t")
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384 if Coord_bool:
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385 fo.write("input_lat\t"+"input_lon\t")
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386 fo.write(var+"\n")
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387 fo.close()
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388
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389
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390 ######################
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391 ######################
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392
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393
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394 #Write header in file
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395 fo=open("header",'w')
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396 for combination in itertools.product(*a):
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397 if Coord_bool:
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398 fo.write(str(combination)+"_"+str(value_dim_lat)+"_"+str(value_dim_lon)+"\t")
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399 else:
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400 fo.write(str(combination)+"\t")
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401 fo.write("\n")
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402 fo.close()
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403
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404
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405 #Write vec2 in a tabular formated file
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406 fo=open("sortie.tabular",'w')
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407 #print(str(vec2))
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408 try:
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409 vec2.tofile(fo,sep="\t",format="%s")
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410 except:
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411 vec3=np.ma.filled(vec2,np.nan)
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412 vec3.tofile(fo,sep="\t",format="%s")
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413 fo.close()
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414
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415
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416 ######################
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417 ######################
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418
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419
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420 #Final sweet msg
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421 print (var+" values successffuly extracted from "+sys.argv[1]+" !")
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