| @@ -17,6 +17,8 for name, cb_table in sophy_cb_tables: | |||
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17 | 17 | ncmap = matplotlib.colors.ListedColormap(cb_table, name=name) |
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18 | 18 | matplotlib.pyplot.register_cmap(cmap=ncmap) |
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19 | 19 | #LINUX bash: export WRADLIB_DATA=/path/to/wradlib-data |
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20 | #example | |
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21 | #export WRADLIB_DATA="/home/soporte/Documents/EVENTO/HYO_PM@2022-06-09T15-05-12/paramC0N36.0/2022-06-09T18-00-00/" | |
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20 | 22 | warnings.filterwarnings('ignore') |
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21 | 23 | PARAM = { |
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22 | 24 | 'S': {'var': 'power','vmin': -45, 'vmax': -15, 'cmap': 'jet', 'label': 'Power','unit': 'dBm'}, |
| @@ -91,6 +93,22 class Readsophy(): | |||
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91 | 93 | new_h = heightList[minIndex:maxIndex] |
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92 | 94 | return new_h |
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93 | 95 | |
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96 | def readAttributes(self,obj,variable): | |
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97 | var = PARAM[variable]['var'] | |
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98 | unit = PARAM[variable]['unit'] | |
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99 | cmap = PARAM[variable]['cmap'] | |
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100 | vmin = PARAM[variable]['vmin'] | |
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101 | vmax = PARAM[variable]['vmax'] | |
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102 | label = PARAM[variable]['label'] | |
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103 | var_ = 'Data/'+var+'/H' | |
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104 | data_arr = numpy.array(obj[var_]['data']) # data | |
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105 | utc_time = numpy.array(obj['Data/time']['data']) | |
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106 | data_azi = numpy.array(obj['Metadata/azimuth']['data']) # th | |
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107 | data_ele = numpy.array(obj["Metadata/elevation"]['data']) | |
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108 | heightList = numpy.array(obj["Metadata/range"]['data']) # r | |
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109 | ||
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110 | return data_arr, utc_time, data_azi,data_ele, heightList,unit,cmap,vmin,vmax,label | |
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111 | ||
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94 | 112 | def run(self): |
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95 | 113 | count= 0 |
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96 | 114 | len_files = len(self.list_file) |
| @@ -101,24 +119,14 class Readsophy(): | |||
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101 | 119 | filename = get_wradlib_data_file(fullpathfile) |
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102 | 120 | test_hdf5 = read_generic_hdf5(filename) |
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103 | 121 | |
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104 | var = PARAM[self.variable]['var'] | |
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105 | unit = PARAM[self.variable]['unit'] | |
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106 | cmap = PARAM[self.variable]['cmap'] | |
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107 | vmin = PARAM[self.variable]['vmin'] | |
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108 | vmax = PARAM[self.variable]['vmax'] | |
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109 | label = PARAM[self.variable]['label'] | |
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110 | var_ = 'Data/'+var+'/H' | |
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111 | data_arr = numpy.array(test_hdf5[var_]['data']) # data | |
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112 | utc_time = numpy.array(test_hdf5['Data/time']['data']) | |
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113 | data_azi = numpy.array(test_hdf5['Metadata/azimuth']['data']) # th | |
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114 | data_ele = numpy.array(test_hdf5["Metadata/elevation"]['data']) | |
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115 | heightList = numpy.array(test_hdf5["Metadata/range"]['data']) # r | |
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122 | # LECTURA | |
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123 | data_arr, utc_time, data_azi,data_ele, heightList,unit,cmap,vmin,vmax,label = self.readAttributes(obj= test_hdf5,variable=self.variable) | |
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116 | 124 | |
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117 | 125 | if self.range==0: |
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118 | 126 | self.range == heightList[-1] |
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119 | 127 | new_heightList,minIndex,maxIndex = self.selectHeights(heightList,0.06,self.range) |
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120 | 128 | |
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121 | ||
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129 | # TIEMPO | |
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122 | 130 | my_time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(utc_time[0])) |
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123 | 131 | time_save = time.strftime('%Y%m%d_%H%M%S',time.localtime(utc_time[0])) |
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124 | 132 | |
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