1 | def min (field,axis=None): |
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2 | import numpy as np |
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3 | if field is None: return None |
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4 | else: return np.array(field).min(axis=axis) |
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5 | |
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6 | def max (field,axis=None): |
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7 | import numpy as np |
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8 | if field is None: return None |
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9 | else: return np.array(field).max(axis=axis) |
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10 | |
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11 | def mean (field,axis=None): |
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12 | import numpy as np |
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13 | if field is None: return None |
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14 | else: |
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15 | if type(field).__name__=='MaskedArray': |
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16 | field.set_fill_value(np.NaN) |
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17 | zout=np.ma.array(field).mean(axis=axis) |
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18 | # np.ma.masked_invalid(zout) |
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19 | zout.set_fill_value(np.NaN) |
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20 | return zout.filled() |
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21 | else: |
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22 | return np.array(field).mean(axis=axis) |
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23 | |
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24 | def deg (): |
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25 | return u'\u00b0' |
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26 | |
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27 | def writeascii ( tab, filename ): |
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28 | mydata = tab |
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29 | myfile = open(filename, 'w') |
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30 | for line in mydata: |
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31 | myfile.write(str(line) + '\n') |
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32 | myfile.close() |
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33 | return |
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34 | |
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35 | |
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36 | # A.C. routine to compute saturation temperature |
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37 | # Be Carefull, when asking for tsat-t, this routine outputs a masked array. |
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38 | # To be correctly handled, this call to tsat must be done before the call to |
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39 | # reduce_field, which handles correctly masked array with the new mean() function. |
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40 | def get_tsat(pressure,temp=None,zlon=None,zlat=None,zalt=None,ztime=None): |
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41 | import math as mt |
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42 | import numpy as np |
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43 | acond=3.2403751E-04 |
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44 | bcond=7.3383721E-03 |
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45 | # if temp is not in input, the routine simply outputs the vertical profile |
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46 | # of Tsat |
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47 | if temp is None: |
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48 | # Identify dimensions in temperature field |
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49 | output=np.zeros(np.array(pressure).shape) |
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50 | if len(np.array(pressure).shape) is 1: |
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51 | #pressure field is a 1d column, (i.e. the altitude coordinate) |
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52 | #temperature has to have a z-axis |
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53 | i=0 |
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54 | for pp in pressure: |
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55 | output[i]=1./(bcond-acond*mt.log(.0095*pp)) |
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56 | i=i+1 |
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57 | else: |
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58 | #pressure field is a field present in the file. Unhandled |
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59 | #by this routine for now, which only loads unique variables. |
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60 | print "3D pressure field not handled for now, exiting in tsat" |
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61 | print "Use a vertical pressure coordinate if you want to compute Tsat" |
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62 | exit() |
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63 | # if temp is in input, the routine computes Tsat-T by detecting where the |
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64 | # vertical axis is in temp |
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65 | else: |
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66 | output=np.zeros(np.array(temp).shape) |
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67 | vardim=get_dim(zlon,zlat,zalt,ztime,temp) |
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68 | if 'altitude' not in vardim.keys(): |
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69 | print 'no altitude coordinate in temperature field for Tsat computation' |
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70 | exit() |
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71 | zdim=vardim['altitude'] |
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72 | ndim=len(np.array(temp).shape) |
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73 | print '--- in tsat(). vardim,zdim,ndim: ',vardim,zdim,ndim |
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74 | i=0 |
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75 | for pp in pressure: |
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76 | if ndim is 1: |
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77 | output[i]=1./(bcond-acond*mt.log(.0095*pp))-temp[i] |
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78 | elif ndim is 2: |
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79 | if zdim is 0: |
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80 | output[i,:]=1./(bcond-acond*mt.log(.0095*pp))-temp[i,:] |
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81 | elif zdim is 1: |
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82 | output[:,i]=1./(bcond-acond*mt.log(.0095*pp))-temp[:,i] |
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83 | else: |
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84 | print "stop in get_tsat: zdim: ",zdim |
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85 | exit() |
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86 | elif ndim is 3: |
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87 | if zdim is 0: |
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88 | output[i,:,:]=1./(bcond-acond*mt.log(.0095*pp))-temp[i,:,:] |
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89 | elif zdim is 1: |
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90 | output[:,i,:]=1./(bcond-acond*mt.log(.0095*pp))-temp[:,i,:] |
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91 | elif zdim is 2: |
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92 | output[:,:,i]=1./(bcond-acond*mt.log(.0095*pp))-temp[:,:,i] |
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93 | else: |
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94 | print "stop in get_tsat: zdim: ",zdim |
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95 | exit() |
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96 | elif ndim is 4: |
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97 | if zdim is 0: |
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98 | output[i,:,:,:]=1./(bcond-acond*mt.log(.0095*pp))-temp[i,:,:,:] |
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99 | elif zdim is 1: |
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100 | output[:,i,:,:]=1./(bcond-acond*mt.log(.0095*pp))-temp[:,i,:,:] |
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101 | elif zdim is 2: |
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102 | output[:,:,i,:]=1./(bcond-acond*mt.log(.0095*pp))-temp[:,:,i,:] |
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103 | elif zdim is 3: |
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104 | output[:,:,:,i]=1./(bcond-acond*mt.log(.0095*pp))-temp[:,:,:,i] |
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105 | else: |
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106 | print "stop in get_tsat: zdim: ", zdim |
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107 | exit() |
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108 | else: |
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109 | print "stop in get_tsat: ndim: ",ndim |
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110 | exit() |
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111 | i=i+1 |
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112 | m=np.ma.masked_invalid(temp,copy=False) |
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113 | zoutput=np.ma.array(output,mask=m.mask,fill_value=np.NaN) |
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114 | return zoutput |
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115 | |
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116 | # A.C. Dirty routine to determine where are the axis of a variable |
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117 | def get_dim(zlon,zlat,zalt,ztime,zvar): |
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118 | import numpy as np |
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119 | nx,ny,nz,nt=0,0,0,0 |
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120 | if zlon is not None: |
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121 | nx=len(zlon) |
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122 | if zlat is not None: |
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123 | ny=len(zlat) |
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124 | if zalt is not None: |
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125 | nz=len(zalt) |
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126 | if ztime is not None: |
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127 | nt=len(ztime) |
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128 | zdims={} |
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129 | zdims['longitude']=nx |
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130 | zdims['latitude']=ny |
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131 | zdims['altitude']=nz |
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132 | zdims['Time']=nt |
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133 | zvardim=np.array(zvar).shape |
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134 | ndim=len(zvardim) |
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135 | zzvardim=[[]]*ndim |
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136 | j=0 |
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137 | output={} |
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138 | for dim in zvardim: |
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139 | if dim not in zdims.values(): |
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140 | print "WARNING -----------------------------" |
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141 | print "Dimensions given to subroutine do not match variables dimensions :" |
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142 | exit() |
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143 | else: |
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144 | a=get_key(zdims,dim) |
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145 | if len(a) is not 1: |
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146 | if j is 0: ##this should solve most conflicts with Time |
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147 | zzvardim[j]=a[1] |
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148 | else: |
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149 | zzvardim[j]=a[0] |
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150 | else: |
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151 | zzvardim[j]=a[0] |
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152 | output[zzvardim[j]]=j |
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153 | j=j+1 |
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154 | return output |
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155 | |
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156 | # A.C. routine that gets keys from a dictionnary value |
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157 | def get_key(self, value): |
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158 | """find the key(s) as a list given a value""" |
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159 | return [item[0] for item in self.items() if item[1] == value] |
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160 | |
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