Mercurial > repos > siwaa > redelac_stics_e

annotate redelacPlanExpander.py @ 0:bc7ae8dd3d3c draft

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"planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
author siwaa
date Mon, 19 Jun 2023 15:51:01 +0000
parents
children 47dafd3de5ef
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bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
siwaa
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1 import sys
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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2 import pandas as pd
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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3 import numpy as np
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5 typeOfRotation = sys.argv [1]
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6 USMsFileName = sys.argv[2]
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7 Liste_plantesFileName = sys.argv[3]
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8 planFileName = sys.argv[4]
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9 maillesFileName = sys.argv[5]
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10 expandedPlanFileName = sys.argv[6]
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11 successiveFileName = sys.argv[7]
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12 StationsFileName = sys.argv[8]
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13 aclimParHorizonFileName = sys.argv[9]
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14 latitudeMailleDriasDFileName= sys.argv[10]
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15 expandedStationsFileName = sys.argv[11]
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17 # 1) reading the base list of USMs
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19 #USMsDf = pd.read_excel(basePlanFileName, sheet_name='USMs')
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20 USMsDf = pd.read_csv(USMsFileName, sep=";", keep_default_na=False, na_filter = False)
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22 # 2) reading the list of plant
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24 #plantsDf = pd.read_excel(basePlanFileName, sheet_name='Liste_plantes')
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25 plantsDf = pd.read_csv(Liste_plantesFileName, sep=";")
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27 # 3) reading the plan
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29 planDf = pd.read_csv(planFileName, sep=";")
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31 # 4) reading the "mailles" file
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32 maillesDf = pd.read_csv(maillesFileName, sep=";")
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34 # 5) reading the stations template
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35 StationsDf = pd.read_csv(StationsFileName, sep=";")
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37 aclimParHorizonDf = pd.read_csv(aclimParHorizonFileName, sep=";")
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39 latitudeMailleDriasDf = pd.read_csv(latitudeMailleDriasDFileName, sep=";")
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41 # a new dataframe to hosts the stations in expansion
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42 expandedStationsDf = pd.DataFrame()
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44 for i, row in planDf.iterrows():
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45 tmpDf = StationsDf
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47 safran = int(row['upc'].split('_')[1])
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48 drias = maillesDf[maillesDf["maille_safran"] == safran].reset_index(drop=True)["maille_drias"][0]
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50 tmpDfBis = tmpDf;
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52 for j, rowS in tmpDf.iterrows():
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53 horizon = rowS['Sta_name'].split('_')[1]
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54 tmpDfBis.at[j, 'Sta_name'] = str(drias) + '_' + horizon + '_sta.xml'
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55 tmpDfBis.at[j, 'aclim'] = aclimParHorizonDf[(aclimParHorizonDf['maille_DRIAS'] == drias) & (aclimParHorizonDf['horizon'] == horizon)].reset_index(drop=True)["aclim"][0]
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56 tmpDfBis.at[j, 'latitude'] = latitudeMailleDriasDf[(latitudeMailleDriasDf['maille_DRIAS'] == drias)].reset_index(drop=True)["latitude"][0]
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58 expandedStationsDf = pd.concat([expandedStationsDf, tmpDfBis])
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60 expandedStationsDf.to_csv(expandedStationsFileName, index = False, sep = ';')
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63 # a new dataFrame to host the list of USMs in expansion
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64 expandedDf = pd.DataFrame()
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66 for i, row in planDf.iterrows():
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67 tmpDf = USMsDf
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68
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69 safran = int(row['upc'].split('_')[1])
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70 drias = maillesDf[maillesDf["maille_safran"] == safran].reset_index(drop=True)["maille_drias"][0]
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72 tmpDf['upc'] = row['upc']
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73 tmpDf['ucs'] = row['ucs']
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74 tmpDf['num_sol'] = row['num_sol']
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75
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76 if typeOfRotation == '' :
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77 tmpDf['Norg_sols'] = row['Norg_sols_GC']
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78 tmpDf['nom_sol_sans_point'] = row['nom_sols_GC_dans_USM']
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79 else :
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80 tmpDf['Norg_sols'] = row['Norg_sols_PP']
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81 tmpDf['nom_sol_sans_point'] = row['nom_sols_PP_dans_USM']
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82
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83 tmpDf['maille_drias'] = drias
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84
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85 # Updating the id_simu column
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86 # alias =CONCATENATE(F2;"-";G2;"_";H2;"-";I2;"-";K2;"-";L2;"-";M2)
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87 # new alias = =CONCATENATE(F2;"-";I2;"-";J2;"-";L2;"-";M2;"-";N2)
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88
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89 tmpDf['id_simu'] = \
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90 tmpDf.upc + '-' + \
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91 tmpDf['nom_sol_sans_point'].astype(str) + '-' + \
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92 tmpDf['systeme'].astype(str) + '-' + \
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93 tmpDf['code_rotation'].astype(str) + '-' + \
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94 tmpDf['tete_rotation'].astype(str) + '-' + \
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95 tmpDf['horizon '].astype(str)
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96
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97 # Merging 2 sheets in order to solve the VLOOKUP
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98 plantsDf.rename(columns = {'Nom_plante':'culture'}, inplace = True)
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99 tmpDf = pd.merge(tmpDf,plantsDf, how='left', on='culture', sort=False)
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100
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101 # Updating the usm_name column
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102 # alias =CONCATENATE(F2;"-";G2;"_";H2;"-";I2;"-";K2;"-";L2;"-";M2;"-";N2;"-";VLOOKUP(O2;$Liste_plantes.$A$2:$B$7;2;0))
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103 # newalias ==CONCATENATE(F2;"-";I2;"-";J2;"-";L2;"-";M2;"-";N2;"-";P2;"-";VLOOKUP(Q2;$Liste_plantes.$A$2:$B$7;2;0))
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104
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105 tmpDf['usm_name'] = \
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106 tmpDf.upc + '-' + \
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107 tmpDf['nom_sol_sans_point'].astype(str) + '-' + \
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108 tmpDf['systeme'].astype(str) + '-' + \
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109 tmpDf['code_rotation'].astype(str) + '-' + \
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110 tmpDf['tete_rotation'].astype(str) + '-' + \
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111 tmpDf['horizon '].astype(str) + '-' + \
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112 tmpDf['annee_fin'].astype(str) + '-' + \
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113 tmpDf['Code_plante']
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114
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115
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116 # Updating the nomsol column
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117 # alias =CONCATENATE(G2;"_";H2)
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118
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119 tmpDf['nomsol'] = \
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120 tmpDf['num_sol'].astype(str) + '_' + \
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121 tmpDf['Norg_sols'].astype(str)
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122
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123
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124 # Updating the fstation column
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125 # alias =CONCATENATE($E2;"_";M2;"_sta.xml")
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126
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127 tmpDf['fstation'] = \
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128 tmpDf['maille_drias'].astype(str) + '_' + \
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129 tmpDf['horizon '].astype(str) + '_sta.xml'
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130
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131 # Updating the fclim1 column
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132 # alias =CONCATENATE($E2;".";YEAR(R2))
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133
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134 tmpDf['fclim1'] = \
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135 tmpDf['maille_drias'].astype(str) + '.' + \
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136 pd.to_datetime(tmpDf['Début'], dayfirst = True).dt.year.astype(str)
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137
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138 # Updating the fclim2 column
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139 # alias =CONCATENATE($E2;".";YEAR(S2))
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140
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141 tmpDf['fclim2'] = \
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142 tmpDf['maille_drias'].astype(str) + '.' + \
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143 pd.to_datetime(tmpDf['Fin'], dayfirst = True).dt.year.astype(str)
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144
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145 expandedDf = pd.concat([expandedDf, tmpDf])
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146
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147 # now getting the list of simu
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148
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149 sucessDf = pd.DataFrame()
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150
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151 listOfSuccessWithNA = expandedDf['id_simu'].unique()
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152
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153 # en raison des NA on filtre
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154
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155 listOfSuccess = [x for x in listOfSuccessWithNA if not x.endswith('NA')]
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156
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157 nbL = len(listOfSuccess)
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158
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159 # fixing first station before to save
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160
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161 fi = 0
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162
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163 expandedDf.reset_index(inplace = True)
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164
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165 for succ in listOfSuccess:
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166
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167 li = expandedDf[expandedDf['id_simu'] == succ].index.max()
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168
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169 expandedDf.loc[fi:li - 1, 'fstation'] = expandedDf['fstation'][fi + 5]
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170
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171 fi = li + 1
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172
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173 expandedDf.drop(['ucs', 'Code_plante', 'Fichier_plante_STICS'], axis = 1, inplace = True)
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174 expandedDf.to_csv(expandedPlanFileName, index=False, sep = ';')
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175
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176 fi = 0
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177
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178 for succ in listOfSuccess:
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179
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180 li = expandedDf[expandedDf['id_simu'] == succ].index.max()
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181
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182 listUofSuccDf = expandedDf.loc[fi:li, "usm_name"].to_frame().reset_index(drop=True)
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183
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184 fi = li + 1
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185
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186 # Adding the USM Columns Name
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187 listUofSuccDf['USM'] = 'USM_' + (listUofSuccDf.index + 1).astype(str)
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188
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189 # Number of usms inside the succession
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190 nbUofSucc = listUofSuccDf.shape[0]
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191
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192 # in order to prepare the transposition set USM column as index
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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193 listUofSuccDf = listUofSuccDf.set_index('USM')
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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194
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195 listUofSuccDf = listUofSuccDf.transpose()
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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196
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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197 # complete the data
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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198
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199 listUofSuccDf['Number_USM'] = nbUofSucc
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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200 listUofSuccDf['Treatment'] = succ
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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201
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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202 # reorder the columns
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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203
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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204 cols = listUofSuccDf.columns.tolist()
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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205 cols = cols[-1:] + cols[-2:-1] + cols [:-2]
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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206
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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207 listUofSuccDf = listUofSuccDf[cols]
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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208
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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209 # complete the list of sucessions
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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210 sucessDf = pd.concat([sucessDf,listUofSuccDf])
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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211
bc7ae8dd3d3c "planemo upload for repository https://forgemia.inra.fr/redelac commit 841d6c6ada2dad3dd575d25aab620491fda5c611"
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212 sucessDf.to_csv(successiveFileName, index=False, sep = ';')