@@ -1,1148 +1,1154 | |||
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1 | 1 | |
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2 | 2 | import os |
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3 | 3 | import time |
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4 | 4 | import glob |
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5 | 5 | import datetime |
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6 | 6 | from multiprocessing import Process |
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7 | 7 | |
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8 | 8 | import zmq |
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9 | 9 | import numpy |
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10 | 10 | import matplotlib |
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11 | 11 | import matplotlib.pyplot as plt |
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12 | 12 | from matplotlib.patches import Polygon |
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13 | 13 | from mpl_toolkits.axes_grid1 import make_axes_locatable |
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14 | 14 | from matplotlib.ticker import FuncFormatter, LinearLocator, MultipleLocator |
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15 | 15 | |
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16 | 16 | from schainpy.model.proc.jroproc_base import Operation |
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17 | 17 | from schainpy.utils import log |
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18 | 18 | |
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19 | 19 | jet_values = matplotlib.pyplot.get_cmap('jet', 100)(numpy.arange(100))[10:90] |
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20 | 20 | blu_values = matplotlib.pyplot.get_cmap( |
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21 | 21 | 'seismic_r', 20)(numpy.arange(20))[10:15] |
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22 | 22 | ncmap = matplotlib.colors.LinearSegmentedColormap.from_list( |
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23 | 23 | 'jro', numpy.vstack((blu_values, jet_values))) |
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24 | 24 | matplotlib.pyplot.register_cmap(cmap=ncmap) |
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25 | 25 | |
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26 | 26 | CMAPS = [plt.get_cmap(s) for s in ('jro', 'jet', 'viridis', 'plasma', 'inferno', 'Greys', 'seismic', 'bwr', 'coolwarm')] |
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27 | 27 | |
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28 | 28 | EARTH_RADIUS = 6.3710e3 |
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29 | 29 | |
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30 | 30 | def ll2xy(lat1, lon1, lat2, lon2): |
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31 | 31 | |
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32 | 32 | p = 0.017453292519943295 |
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33 | 33 | a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2 |
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34 | 34 | r = 12742 * numpy.arcsin(numpy.sqrt(a)) |
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35 | 35 | theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p)*numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p)) |
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36 | 36 | theta = -theta + numpy.pi/2 |
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37 | 37 | return r*numpy.cos(theta), r*numpy.sin(theta) |
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38 | 38 | |
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39 | 39 | def km2deg(km): |
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40 | 40 | ''' |
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41 | 41 | Convert distance in km to degrees |
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42 | 42 | ''' |
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43 | 43 | |
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44 | 44 | return numpy.rad2deg(km/EARTH_RADIUS) |
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45 | 45 | |
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46 | 46 | def figpause(interval): |
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47 | 47 | backend = plt.rcParams['backend'] |
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48 | 48 | if backend in matplotlib.rcsetup.interactive_bk: |
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49 | 49 | figManager = matplotlib._pylab_helpers.Gcf.get_active() |
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50 | 50 | if figManager is not None: |
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51 | 51 | canvas = figManager.canvas |
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52 | 52 | if canvas.figure.stale: |
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53 | 53 | canvas.draw() |
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54 | 54 | try: |
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55 | 55 | canvas.start_event_loop(interval) |
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56 | 56 | except: |
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57 | 57 | pass |
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58 | 58 | return |
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59 | 59 | |
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60 | 60 | def popup(message): |
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61 | 61 | ''' |
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62 | 62 | ''' |
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63 | 63 | |
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64 | 64 | fig = plt.figure(figsize=(12, 8), facecolor='r') |
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65 | 65 | text = '\n'.join([s.strip() for s in message.split(':')]) |
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66 | 66 | fig.text(0.01, 0.5, text, ha='left', va='center', size='20', weight='heavy', color='w') |
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67 | 67 | fig.show() |
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68 | 68 | figpause(1000) |
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69 | 69 | |
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70 | 70 | |
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71 | 71 | class PlotData(Operation, Process): |
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72 | 72 | ''' |
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73 | 73 | Base class for Schain plotting operations |
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74 | 74 | ''' |
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75 | 75 | |
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76 | 76 | CODE = 'Figure' |
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77 | 77 | colormap = 'jro' |
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78 | 78 | bgcolor = 'white' |
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79 | 79 | CONFLATE = False |
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80 | 80 | __missing = 1E30 |
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81 | 81 | |
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82 | 82 | __attrs__ = ['show', 'save', 'xmin', 'xmax', 'ymin', 'ymax', 'zmin', 'zmax', |
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83 | 83 | 'zlimits', 'xlabel', 'ylabel', 'xaxis','cb_label', 'title', |
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84 | 84 | 'colorbar', 'bgcolor', 'width', 'height', 'localtime', 'oneFigure', |
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85 | 85 | 'showprofile', 'decimation', 'ftp'] |
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86 | 86 | |
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87 | 87 | def __init__(self, **kwargs): |
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88 | 88 | |
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89 | 89 | Operation.__init__(self, plot=True, **kwargs) |
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90 | 90 | Process.__init__(self) |
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91 | 91 | |
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92 | 92 | self.kwargs['code'] = self.CODE |
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93 | 93 | self.mp = False |
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94 | 94 | self.data = None |
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95 | 95 | self.isConfig = False |
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96 | 96 | self.figures = [] |
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97 | 97 | self.axes = [] |
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98 | 98 | self.cb_axes = [] |
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99 | 99 | self.localtime = kwargs.pop('localtime', True) |
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100 | 100 | self.show = kwargs.get('show', True) |
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101 | 101 | self.save = kwargs.get('save', False) |
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102 | 102 | self.ftp = kwargs.get('ftp', False) |
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103 | 103 | self.colormap = kwargs.get('colormap', self.colormap) |
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104 | 104 | self.colormap_coh = kwargs.get('colormap_coh', 'jet') |
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105 | 105 | self.colormap_phase = kwargs.get('colormap_phase', 'RdBu_r') |
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106 | 106 | self.colormaps = kwargs.get('colormaps', None) |
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107 | 107 | self.bgcolor = kwargs.get('bgcolor', self.bgcolor) |
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108 | 108 | self.showprofile = kwargs.get('showprofile', False) |
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109 | 109 | self.title = kwargs.get('wintitle', self.CODE.upper()) |
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110 | 110 | self.cb_label = kwargs.get('cb_label', None) |
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111 | 111 | self.cb_labels = kwargs.get('cb_labels', None) |
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112 | 112 | self.labels = kwargs.get('labels', None) |
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113 | 113 | self.xaxis = kwargs.get('xaxis', 'frequency') |
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114 | 114 | self.zmin = kwargs.get('zmin', None) |
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115 | 115 | self.zmax = kwargs.get('zmax', None) |
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116 | 116 | self.zlimits = kwargs.get('zlimits', None) |
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117 | 117 | self.xmin = kwargs.get('xmin', None) |
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118 | 118 | self.xmax = kwargs.get('xmax', None) |
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119 | 119 | self.xrange = kwargs.get('xrange', 24) |
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120 | 120 | self.xscale = kwargs.get('xscale', None) |
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121 | 121 | self.ymin = kwargs.get('ymin', None) |
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122 | 122 | self.ymax = kwargs.get('ymax', None) |
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123 | 123 | self.yscale = kwargs.get('yscale', None) |
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124 | 124 | self.xlabel = kwargs.get('xlabel', None) |
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125 | 125 | self.decimation = kwargs.get('decimation', None) |
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126 | 126 | self.showSNR = kwargs.get('showSNR', False) |
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127 | 127 | self.oneFigure = kwargs.get('oneFigure', True) |
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128 | 128 | self.width = kwargs.get('width', None) |
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129 | 129 | self.height = kwargs.get('height', None) |
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130 | 130 | self.colorbar = kwargs.get('colorbar', True) |
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131 | 131 | self.factors = kwargs.get('factors', [1, 1, 1, 1, 1, 1, 1, 1]) |
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132 | 132 | self.channels = kwargs.get('channels', None) |
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133 | 133 | self.titles = kwargs.get('titles', []) |
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134 | 134 | self.polar = False |
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135 | 135 | self.grid = kwargs.get('grid', False) |
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136 | 136 | |
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137 | 137 | def __fmtTime(self, x, pos): |
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138 | 138 | ''' |
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139 | 139 | ''' |
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140 | 140 | |
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141 | 141 | return '{}'.format(self.getDateTime(x).strftime('%H:%M')) |
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142 | 142 | |
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143 | 143 | def __setup(self): |
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144 | 144 | ''' |
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145 | 145 | Common setup for all figures, here figures and axes are created |
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146 | 146 | ''' |
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147 | 147 | |
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148 | 148 | if self.CODE not in self.data: |
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149 | 149 | raise ValueError(log.error('Missing data for {}'.format(self.CODE), |
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150 | 150 | self.name)) |
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151 | 151 | |
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152 | 152 | self.setup() |
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153 | 153 | |
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154 | 154 | self.time_label = 'LT' if self.localtime else 'UTC' |
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155 | 155 | if self.data.localtime: |
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156 | 156 | self.getDateTime = datetime.datetime.fromtimestamp |
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157 | 157 | else: |
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158 | 158 | self.getDateTime = datetime.datetime.utcfromtimestamp |
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159 | 159 | |
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160 | 160 | if self.width is None: |
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161 | 161 | self.width = 8 |
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162 | 162 | |
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163 | 163 | self.figures = [] |
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164 | 164 | self.axes = [] |
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165 | 165 | self.cb_axes = [] |
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166 | 166 | self.pf_axes = [] |
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167 | 167 | self.cmaps = [] |
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168 | 168 | |
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169 | 169 | size = '15%' if self.ncols == 1 else '30%' |
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170 | 170 | pad = '4%' if self.ncols == 1 else '8%' |
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171 | 171 | |
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172 | 172 | if self.oneFigure: |
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173 | 173 | if self.height is None: |
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174 | 174 | self.height = 1.4 * self.nrows + 1 |
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175 | 175 | fig = plt.figure(figsize=(self.width, self.height), |
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176 | 176 | edgecolor='k', |
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177 | 177 | facecolor='w') |
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178 | 178 | self.figures.append(fig) |
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179 | 179 | for n in range(self.nplots): |
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180 | 180 | ax = fig.add_subplot(self.nrows, self.ncols, |
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181 | 181 | n + 1, polar=self.polar) |
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182 | 182 | ax.tick_params(labelsize=8) |
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183 | 183 | ax.firsttime = True |
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184 | 184 | ax.index = 0 |
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185 | 185 | ax.press = None |
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186 | 186 | self.axes.append(ax) |
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187 | 187 | if self.showprofile: |
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188 | 188 | cax = self.__add_axes(ax, size=size, pad=pad) |
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189 | 189 | cax.tick_params(labelsize=8) |
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190 | 190 | self.pf_axes.append(cax) |
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191 | 191 | else: |
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192 | 192 | if self.height is None: |
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193 | 193 | self.height = 3 |
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194 | 194 | for n in range(self.nplots): |
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195 | 195 | fig = plt.figure(figsize=(self.width, self.height), |
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196 | 196 | edgecolor='k', |
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197 | 197 | facecolor='w') |
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198 | 198 | ax = fig.add_subplot(1, 1, 1, polar=self.polar) |
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199 | 199 | ax.tick_params(labelsize=8) |
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200 | 200 | ax.firsttime = True |
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201 | 201 | ax.index = 0 |
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202 | 202 | ax.press = None |
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203 | 203 | self.figures.append(fig) |
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204 | 204 | self.axes.append(ax) |
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205 | 205 | if self.showprofile: |
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206 | 206 | cax = self.__add_axes(ax, size=size, pad=pad) |
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207 | 207 | cax.tick_params(labelsize=8) |
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208 | 208 | self.pf_axes.append(cax) |
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209 | 209 | |
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210 | 210 | for n in range(self.nrows): |
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211 | 211 | if self.colormaps is not None: |
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212 | 212 | cmap = plt.get_cmap(self.colormaps[n]) |
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213 | 213 | else: |
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214 | 214 | cmap = plt.get_cmap(self.colormap) |
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215 | 215 | cmap.set_bad(self.bgcolor, 1.) |
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216 | 216 | self.cmaps.append(cmap) |
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217 | 217 | |
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218 | 218 | for fig in self.figures: |
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219 | 219 | fig.canvas.mpl_connect('key_press_event', self.OnKeyPress) |
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220 | 220 | fig.canvas.mpl_connect('scroll_event', self.OnBtnScroll) |
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221 | 221 | fig.canvas.mpl_connect('button_press_event', self.onBtnPress) |
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222 | 222 | fig.canvas.mpl_connect('motion_notify_event', self.onMotion) |
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223 | 223 | fig.canvas.mpl_connect('button_release_event', self.onBtnRelease) |
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224 | 224 | if self.show: |
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225 | 225 | fig.show() |
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226 | 226 | |
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227 | 227 | def OnKeyPress(self, event): |
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228 | 228 | ''' |
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229 | 229 | Event for pressing keys (up, down) change colormap |
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230 | 230 | ''' |
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231 | 231 | ax = event.inaxes |
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232 | 232 | if ax in self.axes: |
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233 | 233 | if event.key == 'down': |
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234 | 234 | ax.index += 1 |
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235 | 235 | elif event.key == 'up': |
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236 | 236 | ax.index -= 1 |
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237 | 237 | if ax.index < 0: |
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238 | 238 | ax.index = len(CMAPS) - 1 |
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239 | 239 | elif ax.index == len(CMAPS): |
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240 | 240 | ax.index = 0 |
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241 | 241 | cmap = CMAPS[ax.index] |
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242 | 242 | ax.cbar.set_cmap(cmap) |
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243 | 243 | ax.cbar.draw_all() |
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244 | 244 | ax.plt.set_cmap(cmap) |
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245 | 245 | ax.cbar.patch.figure.canvas.draw() |
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246 | 246 | self.colormap = cmap.name |
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247 | 247 | |
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248 | 248 | def OnBtnScroll(self, event): |
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249 | 249 | ''' |
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250 | 250 | Event for scrolling, scale figure |
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251 | 251 | ''' |
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252 | 252 | cb_ax = event.inaxes |
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253 | 253 | if cb_ax in [ax.cbar.ax for ax in self.axes if ax.cbar]: |
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254 | 254 | ax = [ax for ax in self.axes if cb_ax == ax.cbar.ax][0] |
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255 | 255 | pt = ax.cbar.ax.bbox.get_points()[:, 1] |
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256 | 256 | nrm = ax.cbar.norm |
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257 | 257 | vmin, vmax, p0, p1, pS = ( |
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258 | 258 | nrm.vmin, nrm.vmax, pt[0], pt[1], event.y) |
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259 | 259 | scale = 2 if event.step == 1 else 0.5 |
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260 | 260 | point = vmin + (vmax - vmin) / (p1 - p0) * (pS - p0) |
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261 | 261 | ax.cbar.norm.vmin = point - scale * (point - vmin) |
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262 | 262 | ax.cbar.norm.vmax = point - scale * (point - vmax) |
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263 | 263 | ax.plt.set_norm(ax.cbar.norm) |
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264 | 264 | ax.cbar.draw_all() |
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265 | 265 | ax.cbar.patch.figure.canvas.draw() |
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266 | 266 | |
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267 | 267 | def onBtnPress(self, event): |
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268 | 268 | ''' |
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269 | 269 | Event for mouse button press |
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270 | 270 | ''' |
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271 | 271 | cb_ax = event.inaxes |
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272 | 272 | if cb_ax is None: |
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273 | 273 | return |
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274 | 274 | |
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275 | 275 | if cb_ax in [ax.cbar.ax for ax in self.axes if ax.cbar]: |
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276 | 276 | cb_ax.press = event.x, event.y |
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277 | 277 | else: |
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278 | 278 | cb_ax.press = None |
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279 | 279 | |
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280 | 280 | def onMotion(self, event): |
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281 | 281 | ''' |
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282 | 282 | Event for move inside colorbar |
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283 | 283 | ''' |
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284 | 284 | cb_ax = event.inaxes |
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285 | 285 | if cb_ax is None: |
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286 | 286 | return |
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287 | 287 | if cb_ax not in [ax.cbar.ax for ax in self.axes if ax.cbar]: |
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288 | 288 | return |
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289 | 289 | if cb_ax.press is None: |
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290 | 290 | return |
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291 | 291 | |
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292 | 292 | ax = [ax for ax in self.axes if cb_ax == ax.cbar.ax][0] |
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293 | 293 | xprev, yprev = cb_ax.press |
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294 | 294 | dx = event.x - xprev |
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295 | 295 | dy = event.y - yprev |
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296 | 296 | cb_ax.press = event.x, event.y |
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297 | 297 | scale = ax.cbar.norm.vmax - ax.cbar.norm.vmin |
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298 | 298 | perc = 0.03 |
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299 | 299 | |
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300 | 300 | if event.button == 1: |
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301 | 301 | ax.cbar.norm.vmin -= (perc * scale) * numpy.sign(dy) |
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302 | 302 | ax.cbar.norm.vmax -= (perc * scale) * numpy.sign(dy) |
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303 | 303 | elif event.button == 3: |
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304 | 304 | ax.cbar.norm.vmin -= (perc * scale) * numpy.sign(dy) |
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305 | 305 | ax.cbar.norm.vmax += (perc * scale) * numpy.sign(dy) |
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306 | 306 | |
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307 | 307 | ax.cbar.draw_all() |
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308 | 308 | ax.plt.set_norm(ax.cbar.norm) |
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309 | 309 | ax.cbar.patch.figure.canvas.draw() |
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310 | 310 | |
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311 | 311 | def onBtnRelease(self, event): |
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312 | 312 | ''' |
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313 | 313 | Event for mouse button release |
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314 | 314 | ''' |
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315 | 315 | cb_ax = event.inaxes |
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316 | 316 | if cb_ax is not None: |
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317 | 317 | cb_ax.press = None |
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318 | 318 | |
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319 | 319 | def __add_axes(self, ax, size='30%', pad='8%'): |
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320 | 320 | ''' |
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321 | 321 | Add new axes to the given figure |
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322 | 322 | ''' |
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323 | 323 | divider = make_axes_locatable(ax) |
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324 | 324 | nax = divider.new_horizontal(size=size, pad=pad) |
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325 | 325 | ax.figure.add_axes(nax) |
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326 | 326 | return nax |
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327 | 327 | |
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328 | 328 | self.setup() |
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329 | 329 | |
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330 | 330 | def setup(self): |
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331 | 331 | ''' |
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332 | 332 | This method should be implemented in the child class, the following |
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333 | 333 | attributes should be set: |
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334 | 334 | |
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335 | 335 | self.nrows: number of rows |
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336 | 336 | self.ncols: number of cols |
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337 | 337 | self.nplots: number of plots (channels or pairs) |
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338 | 338 | self.ylabel: label for Y axes |
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339 | 339 | self.titles: list of axes title |
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340 | 340 | |
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341 | 341 | ''' |
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342 | 342 | raise(NotImplementedError, 'Implement this method in child class') |
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343 | 343 | |
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344 | 344 | def fill_gaps(self, x_buffer, y_buffer, z_buffer): |
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345 | 345 | ''' |
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346 | 346 | Create a masked array for missing data |
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347 | 347 | ''' |
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348 | 348 | if x_buffer.shape[0] < 2: |
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349 | 349 | return x_buffer, y_buffer, z_buffer |
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350 | 350 | |
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351 | 351 | deltas = x_buffer[1:] - x_buffer[0:-1] |
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352 | 352 | x_median = numpy.median(deltas) |
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353 | 353 | |
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354 | 354 | index = numpy.where(deltas > 5 * x_median) |
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355 | 355 | |
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356 | 356 | if len(index[0]) != 0: |
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357 | 357 | z_buffer[::, index[0], ::] = self.__missing |
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358 | 358 | z_buffer = numpy.ma.masked_inside(z_buffer, |
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359 | 359 | 0.99 * self.__missing, |
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360 | 360 | 1.01 * self.__missing) |
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361 | 361 | |
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362 | 362 | return x_buffer, y_buffer, z_buffer |
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363 | 363 | |
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364 | 364 | def decimate(self): |
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365 | 365 | |
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366 | 366 | # dx = int(len(self.x)/self.__MAXNUMX) + 1 |
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367 | 367 | dy = int(len(self.y) / self.decimation) + 1 |
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368 | 368 | |
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369 | 369 | # x = self.x[::dx] |
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370 | 370 | x = self.x |
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371 | 371 | y = self.y[::dy] |
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372 | 372 | z = self.z[::, ::, ::dy] |
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373 | 373 | |
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374 | 374 | return x, y, z |
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375 | 375 | |
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376 | 376 | def format(self): |
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377 | 377 | ''' |
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378 | 378 | Set min and max values, labels, ticks and titles |
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379 | 379 | ''' |
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380 | 380 | |
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381 | 381 | if self.xmin is None: |
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382 | 382 | xmin = self.min_time |
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383 | 383 | else: |
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384 | 384 | if self.xaxis is 'time': |
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385 | 385 | dt = self.getDateTime(self.min_time) |
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386 | 386 | xmin = (dt.replace(hour=int(self.xmin), minute=0, second=0) - |
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387 | 387 | datetime.datetime(1970, 1, 1)).total_seconds() |
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388 | 388 | if self.data.localtime: |
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389 | 389 | xmin += time.timezone |
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390 | 390 | else: |
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391 | 391 | xmin = self.xmin |
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392 | 392 | |
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393 | 393 | if self.xmax is None: |
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394 | 394 | xmax = xmin + self.xrange * 60 * 60 |
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395 | 395 | else: |
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396 | 396 | if self.xaxis is 'time': |
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397 | 397 | dt = self.getDateTime(self.max_time) |
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398 | 398 | xmax = (dt.replace(hour=int(self.xmax), minute=59, second=59) - |
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399 | 399 | datetime.datetime(1970, 1, 1) + datetime.timedelta(seconds=1)).total_seconds() |
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400 | 400 | if self.data.localtime: |
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401 | 401 | xmax += time.timezone |
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402 | 402 | else: |
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403 | 403 | xmax = self.xmax |
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404 | 404 | |
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405 | 405 | ymin = self.ymin if self.ymin else numpy.nanmin(self.y) |
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406 | 406 | ymax = self.ymax if self.ymax else numpy.nanmax(self.y) |
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407 | 407 | |
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408 | 408 | Y = numpy.array([1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000, 5000]) |
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409 | 409 | i = 1 if numpy.where(abs(ymax-ymin) <= Y)[0][0] < 0 else numpy.where(abs(ymax-ymin) <= Y)[0][0] |
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410 | 410 | ystep = Y[i] / 10. |
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411 | 411 | |
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412 | if self.xaxis is not 'time': | |
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413 | X = numpy.array([1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000, 5000])/2. | |
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414 | i = 1 if numpy.where(abs(xmax-xmin) <= X)[0][0] < 0 else numpy.where(abs(xmax-xmin) <= X)[0][0] | |
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415 | xstep = X[i] / 10. | |
|
416 | ||
|
412 | 417 | for n, ax in enumerate(self.axes): |
|
413 | 418 | if ax.firsttime: |
|
414 | 419 | ax.set_facecolor(self.bgcolor) |
|
415 | 420 | ax.yaxis.set_major_locator(MultipleLocator(ystep)) |
|
416 | ax.xaxis.set_major_locator(MultipleLocator(ystep)) | |
|
417 | 421 | if self.xscale: |
|
418 | 422 | ax.xaxis.set_major_formatter(FuncFormatter(lambda x, pos: '{0:g}'.format(x*self.xscale))) |
|
419 | 423 | if self.xscale: |
|
420 | 424 | ax.yaxis.set_major_formatter(FuncFormatter(lambda x, pos: '{0:g}'.format(x*self.yscale))) |
|
421 | 425 | if self.xaxis is 'time': |
|
422 | 426 | ax.xaxis.set_major_formatter(FuncFormatter(self.__fmtTime)) |
|
423 | 427 | ax.xaxis.set_major_locator(LinearLocator(9)) |
|
428 | else: | |
|
429 | ax.xaxis.set_major_locator(MultipleLocator(xstep)) | |
|
424 | 430 | if self.xlabel is not None: |
|
425 | 431 | ax.set_xlabel(self.xlabel) |
|
426 | 432 | ax.set_ylabel(self.ylabel) |
|
427 | 433 | ax.firsttime = False |
|
428 | 434 | if self.showprofile: |
|
429 | 435 | self.pf_axes[n].set_ylim(ymin, ymax) |
|
430 | 436 | self.pf_axes[n].set_xlim(self.zmin, self.zmax) |
|
431 | 437 | self.pf_axes[n].set_xlabel('dB') |
|
432 | 438 | self.pf_axes[n].grid(b=True, axis='x') |
|
433 | 439 | [tick.set_visible(False) |
|
434 | 440 | for tick in self.pf_axes[n].get_yticklabels()] |
|
435 | 441 | if self.colorbar: |
|
436 | 442 | ax.cbar = plt.colorbar( |
|
437 | 443 | ax.plt, ax=ax, fraction=0.05, pad=0.02, aspect=10) |
|
438 | 444 | ax.cbar.ax.tick_params(labelsize=8) |
|
439 | 445 | ax.cbar.ax.press = None |
|
440 | 446 | if self.cb_label: |
|
441 | 447 | ax.cbar.set_label(self.cb_label, size=8) |
|
442 | 448 | elif self.cb_labels: |
|
443 | 449 | ax.cbar.set_label(self.cb_labels[n], size=8) |
|
444 | 450 | else: |
|
445 | 451 | ax.cbar = None |
|
446 | 452 | if self.grid: |
|
447 | 453 | ax.grid(True) |
|
448 | 454 | |
|
449 | 455 | if not self.polar: |
|
450 | 456 | ax.set_xlim(xmin, xmax) |
|
451 | 457 | ax.set_ylim(ymin, ymax) |
|
452 | 458 | ax.set_title('{} {} {}'.format( |
|
453 | 459 | self.titles[n], |
|
454 | 460 | self.getDateTime(self.max_time).strftime('%Y-%m-%dT%H:%M:%S'), |
|
455 | 461 | self.time_label), |
|
456 | 462 | size=8) |
|
457 | 463 | else: |
|
458 | 464 | ax.set_title('{}'.format(self.titles[n]), size=8) |
|
459 | 465 | ax.set_ylim(0, 90) |
|
460 | 466 | ax.set_yticks(numpy.arange(0, 90, 20)) |
|
461 | 467 | ax.yaxis.labelpad = 40 |
|
462 | 468 | |
|
463 | 469 | def __plot(self): |
|
464 | 470 | ''' |
|
465 | 471 | ''' |
|
466 | 472 | log.log('Plotting', self.name) |
|
467 | 473 | |
|
468 | 474 | try: |
|
469 | 475 | self.plot() |
|
470 | 476 | self.format() |
|
471 | 477 | except Exception as e: |
|
472 | 478 | log.warning('{} Plot could not be updated... check data'.format(self.CODE), self.name) |
|
473 | 479 | log.error(str(e), '') |
|
474 | 480 | return |
|
475 | 481 | |
|
476 | 482 | for n, fig in enumerate(self.figures): |
|
477 | 483 | if self.nrows == 0 or self.nplots == 0: |
|
478 | 484 | log.warning('No data', self.name) |
|
479 | 485 | fig.text(0.5, 0.5, 'No Data', fontsize='large', ha='center') |
|
480 | 486 | fig.canvas.manager.set_window_title(self.CODE) |
|
481 | 487 | continue |
|
482 | 488 | |
|
483 | 489 | fig.tight_layout() |
|
484 | 490 | fig.canvas.manager.set_window_title('{} - {}'.format(self.title, |
|
485 | 491 | self.getDateTime(self.max_time).strftime('%Y/%m/%d'))) |
|
486 | 492 | fig.canvas.draw() |
|
487 | 493 | |
|
488 | 494 | if self.save and (self.data.ended or not self.data.buffering): |
|
489 | 495 | |
|
490 | 496 | if self.save_labels: |
|
491 | 497 | labels = self.save_labels |
|
492 | 498 | else: |
|
493 | 499 | labels = range(self.nrows) |
|
494 | 500 | |
|
495 | 501 | if self.oneFigure: |
|
496 | 502 | label = '' |
|
497 | 503 | else: |
|
498 | 504 | label = '-{}'.format(labels[n]) |
|
499 | 505 | figname = os.path.join( |
|
500 | 506 | self.save, |
|
501 | 507 | self.CODE, |
|
502 | 508 | '{}{}_{}.png'.format( |
|
503 | 509 | self.CODE, |
|
504 | 510 | label, |
|
505 | 511 | self.getDateTime(self.saveTime).strftime( |
|
506 | 512 | '%Y%m%d_%H%M%S'), |
|
507 | 513 | ) |
|
508 | 514 | ) |
|
509 | 515 | log.log('Saving figure: {}'.format(figname), self.name) |
|
510 | 516 | if not os.path.isdir(os.path.dirname(figname)): |
|
511 | 517 | os.makedirs(os.path.dirname(figname)) |
|
512 | 518 | fig.savefig(figname) |
|
513 | 519 | |
|
514 | 520 | def plot(self): |
|
515 | 521 | ''' |
|
516 | 522 | ''' |
|
517 | 523 | raise(NotImplementedError, 'Implement this method in child class') |
|
518 | 524 | |
|
519 | 525 | def run(self): |
|
520 | 526 | |
|
521 | 527 | log.log('Starting', self.name) |
|
522 | 528 | |
|
523 | 529 | context = zmq.Context() |
|
524 | 530 | receiver = context.socket(zmq.SUB) |
|
525 | 531 | receiver.setsockopt(zmq.SUBSCRIBE, '') |
|
526 | 532 | receiver.setsockopt(zmq.CONFLATE, self.CONFLATE) |
|
527 | 533 | |
|
528 | 534 | if 'server' in self.kwargs['parent']: |
|
529 | 535 | receiver.connect( |
|
530 | 536 | 'ipc:///tmp/{}.plots'.format(self.kwargs['parent']['server'])) |
|
531 | 537 | else: |
|
532 | 538 | receiver.connect("ipc:///tmp/zmq.plots") |
|
533 | 539 | |
|
534 | 540 | while True: |
|
535 | 541 | try: |
|
536 | 542 | self.data = receiver.recv_pyobj(flags=zmq.NOBLOCK) |
|
537 | 543 | if self.data.localtime and self.localtime: |
|
538 | 544 | self.times = self.data.times |
|
539 | 545 | elif self.data.localtime and not self.localtime: |
|
540 | 546 | self.times = self.data.times + time.timezone |
|
541 | 547 | elif not self.data.localtime and self.localtime: |
|
542 | 548 | self.times = self.data.times - time.timezone |
|
543 | 549 | else: |
|
544 | 550 | self.times = self.data.times |
|
545 | 551 | |
|
546 | 552 | self.min_time = self.times[0] |
|
547 | 553 | self.max_time = self.times[-1] |
|
548 | 554 | |
|
549 | 555 | if self.isConfig is False: |
|
550 | 556 | self.__setup() |
|
551 | 557 | self.isConfig = True |
|
552 | 558 | |
|
553 | 559 | self.__plot() |
|
554 | 560 | |
|
555 | 561 | except zmq.Again as e: |
|
556 | 562 | if self.data and self.data.ended: |
|
557 | 563 | break |
|
558 | 564 | log.log('Waiting for data...') |
|
559 | 565 | if self.data: |
|
560 | 566 | figpause(self.data.throttle) |
|
561 | 567 | else: |
|
562 | 568 | time.sleep(2) |
|
563 | 569 | |
|
564 | 570 | def close(self): |
|
565 | 571 | if self.data: |
|
566 | 572 | self.__plot() |
|
567 | 573 | |
|
568 | 574 | |
|
569 | 575 | class PlotSpectraData(PlotData): |
|
570 | 576 | ''' |
|
571 | 577 | Plot for Spectra data |
|
572 | 578 | ''' |
|
573 | 579 | |
|
574 | 580 | CODE = 'spc' |
|
575 | 581 | colormap = 'jro' |
|
576 | 582 | |
|
577 | 583 | def setup(self): |
|
578 | 584 | self.nplots = len(self.data.channels) |
|
579 | 585 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) |
|
580 | 586 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
|
581 | 587 | self.width = 3.4 * self.ncols |
|
582 | 588 | self.height = 3 * self.nrows |
|
583 | 589 | self.cb_label = 'dB' |
|
584 | 590 | if self.showprofile: |
|
585 | 591 | self.width += 0.8 * self.ncols |
|
586 | 592 | |
|
587 | 593 | self.ylabel = 'Range [km]' |
|
588 | 594 | |
|
589 | 595 | def plot(self): |
|
590 | 596 | if self.xaxis == "frequency": |
|
591 | 597 | x = self.data.xrange[0] |
|
592 | 598 | self.xlabel = "Frequency (kHz)" |
|
593 | 599 | elif self.xaxis == "time": |
|
594 | 600 | x = self.data.xrange[1] |
|
595 | 601 | self.xlabel = "Time (ms)" |
|
596 | 602 | else: |
|
597 | 603 | x = self.data.xrange[2] |
|
598 | 604 | self.xlabel = "Velocity (m/s)" |
|
599 | 605 | |
|
600 | 606 | if self.CODE == 'spc_mean': |
|
601 | 607 | x = self.data.xrange[2] |
|
602 | 608 | self.xlabel = "Velocity (m/s)" |
|
603 | 609 | |
|
604 | 610 | self.titles = [] |
|
605 | 611 | |
|
606 | 612 | y = self.data.heights |
|
607 | 613 | self.y = y |
|
608 | 614 | z = self.data['spc'] |
|
609 | 615 | |
|
610 | 616 | for n, ax in enumerate(self.axes): |
|
611 | 617 | noise = self.data['noise'][n][-1] |
|
612 | 618 | if self.CODE == 'spc_mean': |
|
613 | 619 | mean = self.data['mean'][n][-1] |
|
614 | 620 | if ax.firsttime: |
|
615 | 621 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
616 | 622 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
617 | 623 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
618 | 624 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
619 | 625 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
620 | 626 | vmin=self.zmin, |
|
621 | 627 | vmax=self.zmax, |
|
622 | 628 | cmap=plt.get_cmap(self.colormap) |
|
623 | 629 | ) |
|
624 | 630 | |
|
625 | 631 | if self.showprofile: |
|
626 | 632 | ax.plt_profile = self.pf_axes[n].plot( |
|
627 | 633 | self.data['rti'][n][-1], y)[0] |
|
628 | 634 | ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y, |
|
629 | 635 | color="k", linestyle="dashed", lw=1)[0] |
|
630 | 636 | if self.CODE == 'spc_mean': |
|
631 | 637 | ax.plt_mean = ax.plot(mean, y, color='k')[0] |
|
632 | 638 | else: |
|
633 | 639 | ax.plt.set_array(z[n].T.ravel()) |
|
634 | 640 | if self.showprofile: |
|
635 | 641 | ax.plt_profile.set_data(self.data['rti'][n][-1], y) |
|
636 | 642 | ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) |
|
637 | 643 | if self.CODE == 'spc_mean': |
|
638 | 644 | ax.plt_mean.set_data(mean, y) |
|
639 | 645 | |
|
640 | 646 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) |
|
641 | 647 | self.saveTime = self.max_time |
|
642 | 648 | |
|
643 | 649 | |
|
644 | 650 | class PlotCrossSpectraData(PlotData): |
|
645 | 651 | |
|
646 | 652 | CODE = 'cspc' |
|
647 | 653 | zmin_coh = None |
|
648 | 654 | zmax_coh = None |
|
649 | 655 | zmin_phase = None |
|
650 | 656 | zmax_phase = None |
|
651 | 657 | |
|
652 | 658 | def setup(self): |
|
653 | 659 | |
|
654 | 660 | self.ncols = 4 |
|
655 | 661 | self.nrows = len(self.data.pairs) |
|
656 | 662 | self.nplots = self.nrows * 4 |
|
657 | 663 | self.width = 3.4 * self.ncols |
|
658 | 664 | self.height = 3 * self.nrows |
|
659 | 665 | self.ylabel = 'Range [km]' |
|
660 | 666 | self.showprofile = False |
|
661 | 667 | |
|
662 | 668 | def plot(self): |
|
663 | 669 | |
|
664 | 670 | if self.xaxis == "frequency": |
|
665 | 671 | x = self.data.xrange[0] |
|
666 | 672 | self.xlabel = "Frequency (kHz)" |
|
667 | 673 | elif self.xaxis == "time": |
|
668 | 674 | x = self.data.xrange[1] |
|
669 | 675 | self.xlabel = "Time (ms)" |
|
670 | 676 | else: |
|
671 | 677 | x = self.data.xrange[2] |
|
672 | 678 | self.xlabel = "Velocity (m/s)" |
|
673 | 679 | |
|
674 | 680 | self.titles = [] |
|
675 | 681 | |
|
676 | 682 | y = self.data.heights |
|
677 | 683 | self.y = y |
|
678 | 684 | spc = self.data['spc'] |
|
679 | 685 | cspc = self.data['cspc'] |
|
680 | 686 | |
|
681 | 687 | for n in range(self.nrows): |
|
682 | 688 | noise = self.data['noise'][n][-1] |
|
683 | 689 | pair = self.data.pairs[n] |
|
684 | 690 | ax = self.axes[4 * n] |
|
685 | 691 | ax3 = self.axes[4 * n + 3] |
|
686 | 692 | if ax.firsttime: |
|
687 | 693 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
688 | 694 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
689 | 695 | self.zmin = self.zmin if self.zmin else numpy.nanmin(spc) |
|
690 | 696 | self.zmax = self.zmax if self.zmax else numpy.nanmax(spc) |
|
691 | 697 | ax.plt = ax.pcolormesh(x, y, spc[pair[0]].T, |
|
692 | 698 | vmin=self.zmin, |
|
693 | 699 | vmax=self.zmax, |
|
694 | 700 | cmap=plt.get_cmap(self.colormap) |
|
695 | 701 | ) |
|
696 | 702 | else: |
|
697 | 703 | ax.plt.set_array(spc[pair[0]].T.ravel()) |
|
698 | 704 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) |
|
699 | 705 | |
|
700 | 706 | ax = self.axes[4 * n + 1] |
|
701 | 707 | if ax.firsttime: |
|
702 | 708 | ax.plt = ax.pcolormesh(x, y, spc[pair[1]].T, |
|
703 | 709 | vmin=self.zmin, |
|
704 | 710 | vmax=self.zmax, |
|
705 | 711 | cmap=plt.get_cmap(self.colormap) |
|
706 | 712 | ) |
|
707 | 713 | else: |
|
708 | 714 | ax.plt.set_array(spc[pair[1]].T.ravel()) |
|
709 | 715 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) |
|
710 | 716 | |
|
711 | 717 | out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) |
|
712 | 718 | coh = numpy.abs(out) |
|
713 | 719 | phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi |
|
714 | 720 | |
|
715 | 721 | ax = self.axes[4 * n + 2] |
|
716 | 722 | if ax.firsttime: |
|
717 | 723 | ax.plt = ax.pcolormesh(x, y, coh.T, |
|
718 | 724 | vmin=0, |
|
719 | 725 | vmax=1, |
|
720 | 726 | cmap=plt.get_cmap(self.colormap_coh) |
|
721 | 727 | ) |
|
722 | 728 | else: |
|
723 | 729 | ax.plt.set_array(coh.T.ravel()) |
|
724 | 730 | self.titles.append( |
|
725 | 731 | 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1])) |
|
726 | 732 | |
|
727 | 733 | ax = self.axes[4 * n + 3] |
|
728 | 734 | if ax.firsttime: |
|
729 | 735 | ax.plt = ax.pcolormesh(x, y, phase.T, |
|
730 | 736 | vmin=-180, |
|
731 | 737 | vmax=180, |
|
732 | 738 | cmap=plt.get_cmap(self.colormap_phase) |
|
733 | 739 | ) |
|
734 | 740 | else: |
|
735 | 741 | ax.plt.set_array(phase.T.ravel()) |
|
736 | 742 | self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1])) |
|
737 | 743 | |
|
738 | 744 | self.saveTime = self.max_time |
|
739 | 745 | |
|
740 | 746 | |
|
741 | 747 | class PlotSpectraMeanData(PlotSpectraData): |
|
742 | 748 | ''' |
|
743 | 749 | Plot for Spectra and Mean |
|
744 | 750 | ''' |
|
745 | 751 | CODE = 'spc_mean' |
|
746 | 752 | colormap = 'jro' |
|
747 | 753 | |
|
748 | 754 | |
|
749 | 755 | class PlotRTIData(PlotData): |
|
750 | 756 | ''' |
|
751 | 757 | Plot for RTI data |
|
752 | 758 | ''' |
|
753 | 759 | |
|
754 | 760 | CODE = 'rti' |
|
755 | 761 | colormap = 'jro' |
|
756 | 762 | |
|
757 | 763 | def setup(self): |
|
758 | 764 | self.xaxis = 'time' |
|
759 | 765 | self.ncols = 1 |
|
760 | 766 | self.nrows = len(self.data.channels) |
|
761 | 767 | self.nplots = len(self.data.channels) |
|
762 | 768 | self.ylabel = 'Range [km]' |
|
763 | 769 | self.cb_label = 'dB' |
|
764 | 770 | self.titles = ['{} Channel {}'.format( |
|
765 | 771 | self.CODE.upper(), x) for x in range(self.nrows)] |
|
766 | 772 | |
|
767 | 773 | def plot(self): |
|
768 | 774 | self.x = self.times |
|
769 | 775 | self.y = self.data.heights |
|
770 | 776 | self.z = self.data[self.CODE] |
|
771 | 777 | self.z = numpy.ma.masked_invalid(self.z) |
|
772 | 778 | |
|
773 | 779 | if self.decimation is None: |
|
774 | 780 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
775 | 781 | else: |
|
776 | 782 | x, y, z = self.fill_gaps(*self.decimate()) |
|
777 | 783 | |
|
778 | 784 | for n, ax in enumerate(self.axes): |
|
779 | 785 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) |
|
780 | 786 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) |
|
781 | 787 | if ax.firsttime: |
|
782 | 788 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
783 | 789 | vmin=self.zmin, |
|
784 | 790 | vmax=self.zmax, |
|
785 | 791 | cmap=plt.get_cmap(self.colormap) |
|
786 | 792 | ) |
|
787 | 793 | if self.showprofile: |
|
788 | 794 | ax.plot_profile = self.pf_axes[n].plot( |
|
789 | 795 | self.data['rti'][n][-1], self.y)[0] |
|
790 | 796 | ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(self.data['noise'][n][-1], len(self.y)), self.y, |
|
791 | 797 | color="k", linestyle="dashed", lw=1)[0] |
|
792 | 798 | else: |
|
793 | 799 | ax.collections.remove(ax.collections[0]) |
|
794 | 800 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
795 | 801 | vmin=self.zmin, |
|
796 | 802 | vmax=self.zmax, |
|
797 | 803 | cmap=plt.get_cmap(self.colormap) |
|
798 | 804 | ) |
|
799 | 805 | if self.showprofile: |
|
800 | 806 | ax.plot_profile.set_data(self.data['rti'][n][-1], self.y) |
|
801 | 807 | ax.plot_noise.set_data(numpy.repeat( |
|
802 | 808 | self.data['noise'][n][-1], len(self.y)), self.y) |
|
803 | 809 | |
|
804 | 810 | self.saveTime = self.min_time |
|
805 | 811 | |
|
806 | 812 | |
|
807 | 813 | class PlotCOHData(PlotRTIData): |
|
808 | 814 | ''' |
|
809 | 815 | Plot for Coherence data |
|
810 | 816 | ''' |
|
811 | 817 | |
|
812 | 818 | CODE = 'coh' |
|
813 | 819 | |
|
814 | 820 | def setup(self): |
|
815 | 821 | self.xaxis = 'time' |
|
816 | 822 | self.ncols = 1 |
|
817 | 823 | self.nrows = len(self.data.pairs) |
|
818 | 824 | self.nplots = len(self.data.pairs) |
|
819 | 825 | self.ylabel = 'Range [km]' |
|
820 | 826 | if self.CODE == 'coh': |
|
821 | 827 | self.cb_label = '' |
|
822 | 828 | self.titles = [ |
|
823 | 829 | 'Coherence Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] |
|
824 | 830 | else: |
|
825 | 831 | self.cb_label = 'Degrees' |
|
826 | 832 | self.titles = [ |
|
827 | 833 | 'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] |
|
828 | 834 | |
|
829 | 835 | |
|
830 | 836 | class PlotPHASEData(PlotCOHData): |
|
831 | 837 | ''' |
|
832 | 838 | Plot for Phase map data |
|
833 | 839 | ''' |
|
834 | 840 | |
|
835 | 841 | CODE = 'phase' |
|
836 | 842 | colormap = 'seismic' |
|
837 | 843 | |
|
838 | 844 | |
|
839 | 845 | class PlotNoiseData(PlotData): |
|
840 | 846 | ''' |
|
841 | 847 | Plot for noise |
|
842 | 848 | ''' |
|
843 | 849 | |
|
844 | 850 | CODE = 'noise' |
|
845 | 851 | |
|
846 | 852 | def setup(self): |
|
847 | 853 | self.xaxis = 'time' |
|
848 | 854 | self.ncols = 1 |
|
849 | 855 | self.nrows = 1 |
|
850 | 856 | self.nplots = 1 |
|
851 | 857 | self.ylabel = 'Intensity [dB]' |
|
852 | 858 | self.titles = ['Noise'] |
|
853 | 859 | self.colorbar = False |
|
854 | 860 | |
|
855 | 861 | def plot(self): |
|
856 | 862 | |
|
857 | 863 | x = self.times |
|
858 | 864 | xmin = self.min_time |
|
859 | 865 | xmax = xmin + self.xrange * 60 * 60 |
|
860 | 866 | Y = self.data[self.CODE] |
|
861 | 867 | |
|
862 | 868 | if self.axes[0].firsttime: |
|
863 | 869 | for ch in self.data.channels: |
|
864 | 870 | y = Y[ch] |
|
865 | 871 | self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch)) |
|
866 | 872 | plt.legend() |
|
867 | 873 | else: |
|
868 | 874 | for ch in self.data.channels: |
|
869 | 875 | y = Y[ch] |
|
870 | 876 | self.axes[0].lines[ch].set_data(x, y) |
|
871 | 877 | |
|
872 | 878 | self.ymin = numpy.nanmin(Y) - 5 |
|
873 | 879 | self.ymax = numpy.nanmax(Y) + 5 |
|
874 | 880 | self.saveTime = self.min_time |
|
875 | 881 | |
|
876 | 882 | |
|
877 | 883 | class PlotSNRData(PlotRTIData): |
|
878 | 884 | ''' |
|
879 | 885 | Plot for SNR Data |
|
880 | 886 | ''' |
|
881 | 887 | |
|
882 | 888 | CODE = 'snr' |
|
883 | 889 | colormap = 'jet' |
|
884 | 890 | |
|
885 | 891 | |
|
886 | 892 | class PlotDOPData(PlotRTIData): |
|
887 | 893 | ''' |
|
888 | 894 | Plot for DOPPLER Data |
|
889 | 895 | ''' |
|
890 | 896 | |
|
891 | 897 | CODE = 'dop' |
|
892 | 898 | colormap = 'jet' |
|
893 | 899 | |
|
894 | 900 | |
|
895 | 901 | class PlotSkyMapData(PlotData): |
|
896 | 902 | ''' |
|
897 | 903 | Plot for meteors detection data |
|
898 | 904 | ''' |
|
899 | 905 | |
|
900 | 906 | CODE = 'param' |
|
901 | 907 | |
|
902 | 908 | def setup(self): |
|
903 | 909 | |
|
904 | 910 | self.ncols = 1 |
|
905 | 911 | self.nrows = 1 |
|
906 | 912 | self.width = 7.2 |
|
907 | 913 | self.height = 7.2 |
|
908 | 914 | self.nplots = 1 |
|
909 | 915 | self.xlabel = 'Zonal Zenith Angle (deg)' |
|
910 | 916 | self.ylabel = 'Meridional Zenith Angle (deg)' |
|
911 | 917 | self.polar = True |
|
912 | 918 | self.ymin = -180 |
|
913 | 919 | self.ymax = 180 |
|
914 | 920 | self.colorbar = False |
|
915 | 921 | |
|
916 | 922 | def plot(self): |
|
917 | 923 | |
|
918 | 924 | arrayParameters = numpy.concatenate(self.data['param']) |
|
919 | 925 | error = arrayParameters[:, -1] |
|
920 | 926 | indValid = numpy.where(error == 0)[0] |
|
921 | 927 | finalMeteor = arrayParameters[indValid, :] |
|
922 | 928 | finalAzimuth = finalMeteor[:, 3] |
|
923 | 929 | finalZenith = finalMeteor[:, 4] |
|
924 | 930 | |
|
925 | 931 | x = finalAzimuth * numpy.pi / 180 |
|
926 | 932 | y = finalZenith |
|
927 | 933 | |
|
928 | 934 | ax = self.axes[0] |
|
929 | 935 | |
|
930 | 936 | if ax.firsttime: |
|
931 | 937 | ax.plot = ax.plot(x, y, 'bo', markersize=5)[0] |
|
932 | 938 | else: |
|
933 | 939 | ax.plot.set_data(x, y) |
|
934 | 940 | |
|
935 | 941 | dt1 = self.getDateTime(self.min_time).strftime('%y/%m/%d %H:%M:%S') |
|
936 | 942 | dt2 = self.getDateTime(self.max_time).strftime('%y/%m/%d %H:%M:%S') |
|
937 | 943 | title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1, |
|
938 | 944 | dt2, |
|
939 | 945 | len(x)) |
|
940 | 946 | self.titles[0] = title |
|
941 | 947 | self.saveTime = self.max_time |
|
942 | 948 | |
|
943 | 949 | |
|
944 | 950 | class PlotParamData(PlotRTIData): |
|
945 | 951 | ''' |
|
946 | 952 | Plot for data_param object |
|
947 | 953 | ''' |
|
948 | 954 | |
|
949 | 955 | CODE = 'param' |
|
950 | 956 | colormap = 'seismic' |
|
951 | 957 | |
|
952 | 958 | def setup(self): |
|
953 | 959 | self.xaxis = 'time' |
|
954 | 960 | self.ncols = 1 |
|
955 | 961 | self.nrows = self.data.shape(self.CODE)[0] |
|
956 | 962 | self.nplots = self.nrows |
|
957 | 963 | if self.showSNR: |
|
958 | 964 | self.nrows += 1 |
|
959 | 965 | self.nplots += 1 |
|
960 | 966 | |
|
961 | 967 | self.ylabel = 'Height [km]' |
|
962 | 968 | if not self.titles: |
|
963 | 969 | self.titles = self.data.parameters \ |
|
964 | 970 | if self.data.parameters else ['Param {}'.format(x) for x in xrange(self.nrows)] |
|
965 | 971 | if self.showSNR: |
|
966 | 972 | self.titles.append('SNR') |
|
967 | 973 | |
|
968 | 974 | def plot(self): |
|
969 | 975 | self.data.normalize_heights() |
|
970 | 976 | self.x = self.times |
|
971 | 977 | self.y = self.data.heights |
|
972 | 978 | if self.showSNR: |
|
973 | 979 | self.z = numpy.concatenate( |
|
974 | 980 | (self.data[self.CODE], self.data['snr']) |
|
975 | 981 | ) |
|
976 | 982 | else: |
|
977 | 983 | self.z = self.data[self.CODE] |
|
978 | 984 | |
|
979 | 985 | self.z = numpy.ma.masked_invalid(self.z) |
|
980 | 986 | |
|
981 | 987 | if self.decimation is None: |
|
982 | 988 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
983 | 989 | else: |
|
984 | 990 | x, y, z = self.fill_gaps(*self.decimate()) |
|
985 | 991 | |
|
986 | 992 | for n, ax in enumerate(self.axes): |
|
987 | 993 | |
|
988 | 994 | self.zmax = self.zmax if self.zmax is not None else numpy.max( |
|
989 | 995 | self.z[n]) |
|
990 | 996 | self.zmin = self.zmin if self.zmin is not None else numpy.min( |
|
991 | 997 | self.z[n]) |
|
992 | 998 | |
|
993 | 999 | if ax.firsttime: |
|
994 | 1000 | if self.zlimits is not None: |
|
995 | 1001 | self.zmin, self.zmax = self.zlimits[n] |
|
996 | 1002 | |
|
997 | 1003 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], |
|
998 | 1004 | vmin=self.zmin, |
|
999 | 1005 | vmax=self.zmax, |
|
1000 | 1006 | cmap=self.cmaps[n] |
|
1001 | 1007 | ) |
|
1002 | 1008 | else: |
|
1003 | 1009 | if self.zlimits is not None: |
|
1004 | 1010 | self.zmin, self.zmax = self.zlimits[n] |
|
1005 | 1011 | ax.collections.remove(ax.collections[0]) |
|
1006 | 1012 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], |
|
1007 | 1013 | vmin=self.zmin, |
|
1008 | 1014 | vmax=self.zmax, |
|
1009 | 1015 | cmap=self.cmaps[n] |
|
1010 | 1016 | ) |
|
1011 | 1017 | |
|
1012 | 1018 | self.saveTime = self.min_time |
|
1013 | 1019 | |
|
1014 | 1020 | |
|
1015 | 1021 | class PlotOutputData(PlotParamData): |
|
1016 | 1022 | ''' |
|
1017 | 1023 | Plot data_output object |
|
1018 | 1024 | ''' |
|
1019 | 1025 | |
|
1020 | 1026 | CODE = 'output' |
|
1021 | 1027 | colormap = 'seismic' |
|
1022 | 1028 | |
|
1023 | 1029 | |
|
1024 | 1030 | class PlotPolarMapData(PlotData): |
|
1025 | 1031 | ''' |
|
1026 | 1032 | Plot for meteors detection data |
|
1027 | 1033 | ''' |
|
1028 | 1034 | |
|
1029 | 1035 | CODE = 'param' |
|
1030 | 1036 | colormap = 'seismic' |
|
1031 | 1037 | |
|
1032 | 1038 | def setup(self): |
|
1033 | 1039 | self.ncols = 1 |
|
1034 | 1040 | self.nrows = 1 |
|
1035 | 1041 | self.width = 9 |
|
1036 | 1042 | self.height = 8 |
|
1037 | 1043 | self.mode = self.data.meta['mode'] |
|
1038 | 1044 | if self.channels is not None: |
|
1039 | 1045 | self.nplots = len(self.channels) |
|
1040 | 1046 | self.nrows = len(self.channels) |
|
1041 | 1047 | else: |
|
1042 | 1048 | self.nplots = self.data.shape(self.CODE)[0] |
|
1043 | 1049 | self.nrows = self.nplots |
|
1044 | 1050 | self.channels = range(self.nplots) |
|
1045 | 1051 | if self.mode == 'E': |
|
1046 | 1052 | self.xlabel = 'Longitude' |
|
1047 | 1053 | self.ylabel = 'Latitude' |
|
1048 | 1054 | else: |
|
1049 | 1055 | self.xlabel = 'Range (km)' |
|
1050 | 1056 | self.ylabel = 'Height (km)' |
|
1051 | 1057 | self.bgcolor = 'white' |
|
1052 | 1058 | self.cb_labels = self.data.meta['units'] |
|
1053 | 1059 | self.lat = self.data.meta['latitude'] |
|
1054 | 1060 | self.lon = self.data.meta['longitude'] |
|
1055 | 1061 | self.xmin, self.xmax = float(km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon) |
|
1056 | 1062 | self.ymin, self.ymax = float(km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat) |
|
1057 | 1063 | # self.polar = True |
|
1058 | 1064 | |
|
1059 | 1065 | def plot(self): |
|
1060 | 1066 | |
|
1061 | 1067 | for n, ax in enumerate(self.axes): |
|
1062 | 1068 | data = self.data['param'][self.channels[n]] |
|
1063 | 1069 | |
|
1064 | 1070 | zeniths = numpy.linspace(0, self.data.meta['max_range'], data.shape[1]) |
|
1065 | 1071 | if self.mode == 'E': |
|
1066 | 1072 | azimuths = -numpy.radians(self.data.heights)+numpy.pi/2 |
|
1067 | 1073 | r, theta = numpy.meshgrid(zeniths, azimuths) |
|
1068 | 1074 | x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])) |
|
1069 | 1075 | x = km2deg(x) + self.lon |
|
1070 | 1076 | y = km2deg(y) + self.lat |
|
1071 | 1077 | else: |
|
1072 | 1078 | azimuths = numpy.radians(self.data.heights) |
|
1073 | 1079 | r, theta = numpy.meshgrid(zeniths, azimuths) |
|
1074 | 1080 | x, y = r*numpy.cos(theta), r*numpy.sin(theta) |
|
1075 | 1081 | self.y = zeniths |
|
1076 | 1082 | |
|
1077 | 1083 | if ax.firsttime: |
|
1078 | 1084 | if self.zlimits is not None: |
|
1079 | 1085 | self.zmin, self.zmax = self.zlimits[n] |
|
1080 | 1086 | ax.plt = ax.pcolormesh(#r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
1081 | 1087 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
1082 | 1088 | vmin=self.zmin, |
|
1083 | 1089 | vmax=self.zmax, |
|
1084 | 1090 | cmap=self.cmaps[n]) |
|
1085 | 1091 | else: |
|
1086 | 1092 | if self.zlimits is not None: |
|
1087 | 1093 | self.zmin, self.zmax = self.zlimits[n] |
|
1088 | 1094 | ax.collections.remove(ax.collections[0]) |
|
1089 | 1095 | ax.plt = ax.pcolormesh(# r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
1090 | 1096 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
1091 | 1097 | vmin=self.zmin, |
|
1092 | 1098 | vmax=self.zmax, |
|
1093 | 1099 | cmap=self.cmaps[n]) |
|
1094 | 1100 | |
|
1095 | 1101 | if self.mode == 'A': |
|
1096 | 1102 | continue |
|
1097 | 1103 | |
|
1098 | 1104 | # plot district names |
|
1099 | 1105 | f = open('/data/workspace/schain_scripts/distrito.csv') |
|
1100 | 1106 | for line in f: |
|
1101 | 1107 | label, lon, lat = [s.strip() for s in line.split(',') if s] |
|
1102 | 1108 | lat = float(lat) |
|
1103 | 1109 | lon = float(lon) |
|
1104 | 1110 | # ax.plot(lon, lat, '.b', ms=2) |
|
1105 | 1111 | ax.text(lon, lat, label.decode('utf8'), ha='center', va='bottom', size='8', color='black') |
|
1106 | 1112 | |
|
1107 | 1113 | # plot limites |
|
1108 | 1114 | limites =[] |
|
1109 | 1115 | tmp = [] |
|
1110 | 1116 | for line in open('/data/workspace/schain_scripts/lima.csv'): |
|
1111 | 1117 | if '#' in line: |
|
1112 | 1118 | if tmp: |
|
1113 | 1119 | limites.append(tmp) |
|
1114 | 1120 | tmp = [] |
|
1115 | 1121 | continue |
|
1116 | 1122 | values = line.strip().split(',') |
|
1117 | 1123 | tmp.append((float(values[0]), float(values[1]))) |
|
1118 | 1124 | for points in limites: |
|
1119 | 1125 | ax.add_patch(Polygon(points, ec='k', fc='none', ls='--', lw=0.5)) |
|
1120 | 1126 | |
|
1121 | 1127 | # plot Cuencas |
|
1122 | 1128 | for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'): |
|
1123 | 1129 | f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca)) |
|
1124 | 1130 | values = [line.strip().split(',') for line in f] |
|
1125 | 1131 | points = [(float(s[0]), float(s[1])) for s in values] |
|
1126 | 1132 | ax.add_patch(Polygon(points, ec='b', fc='none')) |
|
1127 | 1133 | |
|
1128 | 1134 | # plot grid |
|
1129 | 1135 | for r in (15, 30, 45, 60): |
|
1130 | 1136 | ax.add_artist(plt.Circle((self.lon, self.lat), km2deg(r), color='0.6', fill=False, lw=0.2)) |
|
1131 | 1137 | ax.text( |
|
1132 | 1138 | self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180), |
|
1133 | 1139 | self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180), |
|
1134 | 1140 | '{}km'.format(r), |
|
1135 | 1141 | ha='center', va='bottom', size='8', color='0.6', weight='heavy') |
|
1136 | 1142 | |
|
1137 | 1143 | if self.mode == 'E': |
|
1138 | 1144 | title = 'El={}$^\circ$'.format(self.data.meta['elevation']) |
|
1139 | 1145 | label = 'E{:02d}'.format(int(self.data.meta['elevation'])) |
|
1140 | 1146 | else: |
|
1141 | 1147 | title = 'Az={}$^\circ$'.format(self.data.meta['azimuth']) |
|
1142 | 1148 | label = 'A{:02d}'.format(int(self.data.meta['azimuth'])) |
|
1143 | 1149 | |
|
1144 | 1150 | self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels] |
|
1145 | 1151 | self.titles = ['{} {}'.format(self.data.parameters[x], title) for x in self.channels] |
|
1146 | 1152 | self.saveTime = self.max_time |
|
1147 | 1153 | |
|
1148 | 1154 |
@@ -1,679 +1,679 | |||
|
1 | 1 | ''' |
|
2 | 2 | Created on Jul 2, 2014 |
|
3 | 3 | |
|
4 | 4 | @author: roj-idl71 |
|
5 | 5 | ''' |
|
6 | 6 | import numpy |
|
7 | 7 | |
|
8 | 8 | from jroIO_base import LOCALTIME, JRODataReader, JRODataWriter |
|
9 | 9 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation |
|
10 | 10 | from schainpy.model.data.jroheaderIO import PROCFLAG, BasicHeader, SystemHeader, RadarControllerHeader, ProcessingHeader |
|
11 | 11 | from schainpy.model.data.jrodata import Spectra |
|
12 | 12 | |
|
13 | 13 | class SpectraReader(JRODataReader, ProcessingUnit): |
|
14 | 14 | """ |
|
15 | 15 | Esta clase permite leer datos de espectros desde archivos procesados (.pdata). La lectura |
|
16 | 16 | de los datos siempre se realiza por bloques. Los datos leidos (array de 3 dimensiones) |
|
17 | 17 | son almacenados en tres buffer's para el Self Spectra, el Cross Spectra y el DC Channel. |
|
18 | 18 | |
|
19 | 19 | paresCanalesIguales * alturas * perfiles (Self Spectra) |
|
20 | 20 | paresCanalesDiferentes * alturas * perfiles (Cross Spectra) |
|
21 | 21 | canales * alturas (DC Channels) |
|
22 | 22 | |
|
23 | 23 | Esta clase contiene instancias (objetos) de las clases BasicHeader, SystemHeader, |
|
24 | 24 | RadarControllerHeader y Spectra. Los tres primeros se usan para almacenar informacion de la |
|
25 | 25 | cabecera de datos (metadata), y el cuarto (Spectra) para obtener y almacenar un bloque de |
|
26 | 26 | datos desde el "buffer" cada vez que se ejecute el metodo "getData". |
|
27 | 27 | |
|
28 | 28 | Example: |
|
29 | 29 | dpath = "/home/myuser/data" |
|
30 | 30 | |
|
31 | 31 | startTime = datetime.datetime(2010,1,20,0,0,0,0,0,0) |
|
32 | 32 | |
|
33 | 33 | endTime = datetime.datetime(2010,1,21,23,59,59,0,0,0) |
|
34 | 34 | |
|
35 | 35 | readerObj = SpectraReader() |
|
36 | 36 | |
|
37 | 37 | readerObj.setup(dpath, startTime, endTime) |
|
38 | 38 | |
|
39 | 39 | while(True): |
|
40 | 40 | |
|
41 | 41 | readerObj.getData() |
|
42 | 42 | |
|
43 | 43 | print readerObj.data_spc |
|
44 | 44 | |
|
45 | 45 | print readerObj.data_cspc |
|
46 | 46 | |
|
47 | 47 | print readerObj.data_dc |
|
48 | 48 | |
|
49 | 49 | if readerObj.flagNoMoreFiles: |
|
50 | 50 | break |
|
51 | 51 | |
|
52 | 52 | """ |
|
53 | 53 | |
|
54 | 54 | pts2read_SelfSpectra = 0 |
|
55 | 55 | |
|
56 | 56 | pts2read_CrossSpectra = 0 |
|
57 | 57 | |
|
58 | 58 | pts2read_DCchannels = 0 |
|
59 | 59 | |
|
60 | 60 | ext = ".pdata" |
|
61 | 61 | |
|
62 | 62 | optchar = "P" |
|
63 | 63 | |
|
64 | 64 | dataOut = None |
|
65 | 65 | |
|
66 | 66 | nRdChannels = None |
|
67 | 67 | |
|
68 | 68 | nRdPairs = None |
|
69 | 69 | |
|
70 | 70 | rdPairList = [] |
|
71 | 71 | |
|
72 | 72 | def __init__(self, **kwargs): |
|
73 | 73 | """ |
|
74 | 74 | Inicializador de la clase SpectraReader para la lectura de datos de espectros. |
|
75 | 75 | |
|
76 | 76 | Inputs: |
|
77 | 77 | dataOut : Objeto de la clase Spectra. Este objeto sera utilizado para |
|
78 | 78 | almacenar un perfil de datos cada vez que se haga un requerimiento |
|
79 | 79 | (getData). El perfil sera obtenido a partir del buffer de datos, |
|
80 | 80 | si el buffer esta vacio se hara un nuevo proceso de lectura de un |
|
81 | 81 | bloque de datos. |
|
82 | 82 | Si este parametro no es pasado se creara uno internamente. |
|
83 | 83 | |
|
84 | 84 | Affected: |
|
85 | 85 | self.dataOut |
|
86 | 86 | |
|
87 | 87 | Return : None |
|
88 | 88 | """ |
|
89 | 89 | |
|
90 | 90 | #Eliminar de la base la herencia |
|
91 | 91 | ProcessingUnit.__init__(self, **kwargs) |
|
92 | 92 | |
|
93 | 93 | # self.isConfig = False |
|
94 | 94 | |
|
95 | 95 | self.pts2read_SelfSpectra = 0 |
|
96 | 96 | |
|
97 | 97 | self.pts2read_CrossSpectra = 0 |
|
98 | 98 | |
|
99 | 99 | self.pts2read_DCchannels = 0 |
|
100 | 100 | |
|
101 | 101 | self.datablock = None |
|
102 | 102 | |
|
103 | 103 | self.utc = None |
|
104 | 104 | |
|
105 | 105 | self.ext = ".pdata" |
|
106 | 106 | |
|
107 | 107 | self.optchar = "P" |
|
108 | 108 | |
|
109 | 109 | self.basicHeaderObj = BasicHeader(LOCALTIME) |
|
110 | 110 | |
|
111 | 111 | self.systemHeaderObj = SystemHeader() |
|
112 | 112 | |
|
113 | 113 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
114 | 114 | |
|
115 | 115 | self.processingHeaderObj = ProcessingHeader() |
|
116 | 116 | |
|
117 | 117 | self.online = 0 |
|
118 | 118 | |
|
119 | 119 | self.fp = None |
|
120 | 120 | |
|
121 | 121 | self.idFile = None |
|
122 | 122 | |
|
123 | 123 | self.dtype = None |
|
124 | 124 | |
|
125 | 125 | self.fileSizeByHeader = None |
|
126 | 126 | |
|
127 | 127 | self.filenameList = [] |
|
128 | 128 | |
|
129 | 129 | self.filename = None |
|
130 | 130 | |
|
131 | 131 | self.fileSize = None |
|
132 | 132 | |
|
133 | 133 | self.firstHeaderSize = 0 |
|
134 | 134 | |
|
135 | 135 | self.basicHeaderSize = 24 |
|
136 | 136 | |
|
137 | 137 | self.pathList = [] |
|
138 | 138 | |
|
139 | 139 | self.lastUTTime = 0 |
|
140 | 140 | |
|
141 | 141 | self.maxTimeStep = 30 |
|
142 | 142 | |
|
143 | 143 | self.flagNoMoreFiles = 0 |
|
144 | 144 | |
|
145 | 145 | self.set = 0 |
|
146 | 146 | |
|
147 | 147 | self.path = None |
|
148 | 148 | |
|
149 | 149 | self.delay = 60 #seconds |
|
150 | 150 | |
|
151 | 151 | self.nTries = 3 #quantity tries |
|
152 | 152 | |
|
153 | 153 | self.nFiles = 3 #number of files for searching |
|
154 | 154 | |
|
155 | 155 | self.nReadBlocks = 0 |
|
156 | 156 | |
|
157 | 157 | self.flagIsNewFile = 1 |
|
158 | 158 | |
|
159 | 159 | self.__isFirstTimeOnline = 1 |
|
160 | 160 | |
|
161 | 161 | # self.ippSeconds = 0 |
|
162 | 162 | |
|
163 | 163 | self.flagDiscontinuousBlock = 0 |
|
164 | 164 | |
|
165 | 165 | self.flagIsNewBlock = 0 |
|
166 | 166 | |
|
167 | 167 | self.nTotalBlocks = 0 |
|
168 | 168 | |
|
169 | 169 | self.blocksize = 0 |
|
170 | 170 | |
|
171 | 171 | self.dataOut = self.createObjByDefault() |
|
172 | 172 | |
|
173 | 173 | self.profileIndex = 1 #Always |
|
174 | 174 | |
|
175 | 175 | |
|
176 | 176 | def createObjByDefault(self): |
|
177 | 177 | |
|
178 | 178 | dataObj = Spectra() |
|
179 | 179 | |
|
180 | 180 | return dataObj |
|
181 | 181 | |
|
182 | 182 | def __hasNotDataInBuffer(self): |
|
183 | 183 | return 1 |
|
184 | 184 | |
|
185 | 185 | |
|
186 | 186 | def getBlockDimension(self): |
|
187 | 187 | """ |
|
188 | 188 | Obtiene la cantidad de puntos a leer por cada bloque de datos |
|
189 | 189 | |
|
190 | 190 | Affected: |
|
191 | 191 | self.nRdChannels |
|
192 | 192 | self.nRdPairs |
|
193 | 193 | self.pts2read_SelfSpectra |
|
194 | 194 | self.pts2read_CrossSpectra |
|
195 | 195 | self.pts2read_DCchannels |
|
196 | 196 | self.blocksize |
|
197 | 197 | self.dataOut.nChannels |
|
198 | 198 | self.dataOut.nPairs |
|
199 | 199 | |
|
200 | 200 | Return: |
|
201 | 201 | None |
|
202 | 202 | """ |
|
203 | 203 | self.nRdChannels = 0 |
|
204 | 204 | self.nRdPairs = 0 |
|
205 | 205 | self.rdPairList = [] |
|
206 | 206 | |
|
207 | 207 | for i in range(0, self.processingHeaderObj.totalSpectra*2, 2): |
|
208 | 208 | if self.processingHeaderObj.spectraComb[i] == self.processingHeaderObj.spectraComb[i+1]: |
|
209 | 209 | self.nRdChannels = self.nRdChannels + 1 #par de canales iguales |
|
210 | 210 | else: |
|
211 | 211 | self.nRdPairs = self.nRdPairs + 1 #par de canales diferentes |
|
212 | 212 | self.rdPairList.append((self.processingHeaderObj.spectraComb[i], self.processingHeaderObj.spectraComb[i+1])) |
|
213 | 213 | |
|
214 | 214 | pts2read = self.processingHeaderObj.nHeights * self.processingHeaderObj.profilesPerBlock |
|
215 | 215 | |
|
216 | 216 | self.pts2read_SelfSpectra = int(self.nRdChannels * pts2read) |
|
217 | 217 | self.blocksize = self.pts2read_SelfSpectra |
|
218 | 218 | |
|
219 | 219 | if self.processingHeaderObj.flag_cspc: |
|
220 | 220 | self.pts2read_CrossSpectra = int(self.nRdPairs * pts2read) |
|
221 | 221 | self.blocksize += self.pts2read_CrossSpectra |
|
222 | 222 | |
|
223 | 223 | if self.processingHeaderObj.flag_dc: |
|
224 | 224 | self.pts2read_DCchannels = int(self.systemHeaderObj.nChannels * self.processingHeaderObj.nHeights) |
|
225 | 225 | self.blocksize += self.pts2read_DCchannels |
|
226 | 226 | |
|
227 | 227 | # self.blocksize = self.pts2read_SelfSpectra + self.pts2read_CrossSpectra + self.pts2read_DCchannels |
|
228 | 228 | |
|
229 | 229 | |
|
230 | 230 | def readBlock(self): |
|
231 | 231 | """ |
|
232 | 232 | Lee el bloque de datos desde la posicion actual del puntero del archivo |
|
233 | 233 | (self.fp) y actualiza todos los parametros relacionados al bloque de datos |
|
234 | 234 | (metadata + data). La data leida es almacenada en el buffer y el contador del buffer |
|
235 | 235 | es seteado a 0 |
|
236 | 236 | |
|
237 | 237 | Return: None |
|
238 | 238 | |
|
239 | 239 | Variables afectadas: |
|
240 | 240 | |
|
241 | 241 | self.flagIsNewFile |
|
242 | 242 | self.flagIsNewBlock |
|
243 | 243 | self.nTotalBlocks |
|
244 | 244 | self.data_spc |
|
245 | 245 | self.data_cspc |
|
246 | 246 | self.data_dc |
|
247 | 247 | |
|
248 | 248 | Exceptions: |
|
249 | 249 | Si un bloque leido no es un bloque valido |
|
250 | 250 | """ |
|
251 | 251 | blockOk_flag = False |
|
252 | 252 | fpointer = self.fp.tell() |
|
253 | 253 | |
|
254 | 254 | spc = numpy.fromfile( self.fp, self.dtype[0], self.pts2read_SelfSpectra ) |
|
255 | 255 | spc = spc.reshape( (self.nRdChannels, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D |
|
256 | 256 | |
|
257 | 257 | if self.processingHeaderObj.flag_cspc: |
|
258 | 258 | cspc = numpy.fromfile( self.fp, self.dtype, self.pts2read_CrossSpectra ) |
|
259 | 259 | cspc = cspc.reshape( (self.nRdPairs, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D |
|
260 | 260 | |
|
261 | 261 | if self.processingHeaderObj.flag_dc: |
|
262 | 262 | dc = numpy.fromfile( self.fp, self.dtype, self.pts2read_DCchannels ) #int(self.processingHeaderObj.nHeights*self.systemHeaderObj.nChannels) ) |
|
263 | 263 | dc = dc.reshape( (self.systemHeaderObj.nChannels, self.processingHeaderObj.nHeights) ) #transforma a un arreglo 2D |
|
264 | 264 | |
|
265 | 265 | |
|
266 | if self.processingHeaderObj.shif_fft: | |
|
266 | if not self.processingHeaderObj.shif_fft: | |
|
267 | 267 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
268 | 268 | shift = int(self.processingHeaderObj.profilesPerBlock/2) |
|
269 | 269 | spc = numpy.roll( spc, shift , axis=2 ) |
|
270 | 270 | |
|
271 | 271 | if self.processingHeaderObj.flag_cspc: |
|
272 | 272 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
273 | 273 | cspc = numpy.roll( cspc, shift, axis=2 ) |
|
274 | 274 | |
|
275 | 275 | #Dimensions : nChannels, nProfiles, nSamples |
|
276 | 276 | spc = numpy.transpose( spc, (0,2,1) ) |
|
277 | 277 | self.data_spc = spc |
|
278 | 278 | |
|
279 | 279 | if self.processingHeaderObj.flag_cspc: |
|
280 | 280 | cspc = numpy.transpose( cspc, (0,2,1) ) |
|
281 | 281 | self.data_cspc = cspc['real'] + cspc['imag']*1j |
|
282 | 282 | else: |
|
283 | 283 | self.data_cspc = None |
|
284 | 284 | |
|
285 | 285 | if self.processingHeaderObj.flag_dc: |
|
286 | 286 | self.data_dc = dc['real'] + dc['imag']*1j |
|
287 | 287 | else: |
|
288 | 288 | self.data_dc = None |
|
289 | 289 | |
|
290 | 290 | self.flagIsNewFile = 0 |
|
291 | 291 | self.flagIsNewBlock = 1 |
|
292 | 292 | |
|
293 | 293 | self.nTotalBlocks += 1 |
|
294 | 294 | self.nReadBlocks += 1 |
|
295 | 295 | |
|
296 | 296 | return 1 |
|
297 | 297 | |
|
298 | 298 | def getFirstHeader(self): |
|
299 | 299 | |
|
300 | 300 | self.getBasicHeader() |
|
301 | 301 | |
|
302 | 302 | self.dataOut.systemHeaderObj = self.systemHeaderObj.copy() |
|
303 | 303 | |
|
304 | 304 | self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy() |
|
305 | 305 | |
|
306 | 306 | # self.dataOut.ippSeconds = self.ippSeconds |
|
307 | 307 | |
|
308 | 308 | # self.dataOut.timeInterval = self.radarControllerHeaderObj.ippSeconds * self.processingHeaderObj.nCohInt * self.processingHeaderObj.nIncohInt * self.processingHeaderObj.profilesPerBlock |
|
309 | 309 | |
|
310 | 310 | self.dataOut.dtype = self.dtype |
|
311 | 311 | |
|
312 | 312 | # self.dataOut.nPairs = self.nPairs |
|
313 | 313 | |
|
314 | 314 | self.dataOut.pairsList = self.rdPairList |
|
315 | 315 | |
|
316 | 316 | self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock |
|
317 | 317 | |
|
318 | 318 | self.dataOut.nFFTPoints = self.processingHeaderObj.profilesPerBlock |
|
319 | 319 | |
|
320 | 320 | self.dataOut.nCohInt = self.processingHeaderObj.nCohInt |
|
321 | 321 | |
|
322 | 322 | self.dataOut.nIncohInt = self.processingHeaderObj.nIncohInt |
|
323 | 323 | |
|
324 | 324 | xf = self.processingHeaderObj.firstHeight + self.processingHeaderObj.nHeights*self.processingHeaderObj.deltaHeight |
|
325 | 325 | |
|
326 | 326 | self.dataOut.heightList = numpy.arange(self.processingHeaderObj.firstHeight, xf, self.processingHeaderObj.deltaHeight) |
|
327 | 327 | |
|
328 | 328 | self.dataOut.channelList = range(self.systemHeaderObj.nChannels) |
|
329 | 329 | |
|
330 | 330 | self.dataOut.flagShiftFFT = True #Data is always shifted |
|
331 | 331 | |
|
332 | 332 | self.dataOut.flagDecodeData = self.processingHeaderObj.flag_decode #asumo q la data no esta decodificada |
|
333 | 333 | |
|
334 | 334 | self.dataOut.flagDeflipData = self.processingHeaderObj.flag_deflip #asumo q la data esta sin flip |
|
335 | 335 | |
|
336 | 336 | def getData(self): |
|
337 | 337 | """ |
|
338 | 338 | First method to execute before "RUN" is called. |
|
339 | 339 | |
|
340 | 340 | Copia el buffer de lectura a la clase "Spectra", |
|
341 | 341 | con todos los parametros asociados a este (metadata). cuando no hay datos en el buffer de |
|
342 | 342 | lectura es necesario hacer una nueva lectura de los bloques de datos usando "readNextBlock" |
|
343 | 343 | |
|
344 | 344 | Return: |
|
345 | 345 | 0 : Si no hay mas archivos disponibles |
|
346 | 346 | 1 : Si hizo una buena copia del buffer |
|
347 | 347 | |
|
348 | 348 | Affected: |
|
349 | 349 | self.dataOut |
|
350 | 350 | |
|
351 | 351 | self.flagDiscontinuousBlock |
|
352 | 352 | self.flagIsNewBlock |
|
353 | 353 | """ |
|
354 | 354 | |
|
355 | 355 | if self.flagNoMoreFiles: |
|
356 | 356 | self.dataOut.flagNoData = True |
|
357 | 357 | print 'Process finished' |
|
358 | 358 | return 0 |
|
359 | 359 | |
|
360 | 360 | self.flagDiscontinuousBlock = 0 |
|
361 | 361 | self.flagIsNewBlock = 0 |
|
362 | 362 | |
|
363 | 363 | if self.__hasNotDataInBuffer(): |
|
364 | 364 | |
|
365 | 365 | if not( self.readNextBlock() ): |
|
366 | 366 | self.dataOut.flagNoData = True |
|
367 | 367 | return 0 |
|
368 | 368 | |
|
369 | 369 | #data es un numpy array de 3 dmensiones (perfiles, alturas y canales) |
|
370 | 370 | |
|
371 | 371 | if self.data_spc is None: |
|
372 | 372 | self.dataOut.flagNoData = True |
|
373 | 373 | return 0 |
|
374 | 374 | |
|
375 | 375 | self.getBasicHeader() |
|
376 | 376 | |
|
377 | 377 | self.getFirstHeader() |
|
378 | 378 | |
|
379 | 379 | self.dataOut.data_spc = self.data_spc |
|
380 | 380 | |
|
381 | 381 | self.dataOut.data_cspc = self.data_cspc |
|
382 | 382 | |
|
383 | 383 | self.dataOut.data_dc = self.data_dc |
|
384 | 384 | |
|
385 | 385 | self.dataOut.flagNoData = False |
|
386 | 386 | |
|
387 | 387 | self.dataOut.realtime = self.online |
|
388 | 388 | |
|
389 | 389 | return self.dataOut.data_spc |
|
390 | 390 | |
|
391 | 391 | class SpectraWriter(JRODataWriter, Operation): |
|
392 | 392 | |
|
393 | 393 | """ |
|
394 | 394 | Esta clase permite escribir datos de espectros a archivos procesados (.pdata). La escritura |
|
395 | 395 | de los datos siempre se realiza por bloques. |
|
396 | 396 | """ |
|
397 | 397 | |
|
398 | 398 | ext = ".pdata" |
|
399 | 399 | |
|
400 | 400 | optchar = "P" |
|
401 | 401 | |
|
402 | 402 | shape_spc_Buffer = None |
|
403 | 403 | |
|
404 | 404 | shape_cspc_Buffer = None |
|
405 | 405 | |
|
406 | 406 | shape_dc_Buffer = None |
|
407 | 407 | |
|
408 | 408 | data_spc = None |
|
409 | 409 | |
|
410 | 410 | data_cspc = None |
|
411 | 411 | |
|
412 | 412 | data_dc = None |
|
413 | 413 | |
|
414 | 414 | # dataOut = None |
|
415 | 415 | |
|
416 | 416 | def __init__(self, **kwargs): |
|
417 | 417 | """ |
|
418 | 418 | Inicializador de la clase SpectraWriter para la escritura de datos de espectros. |
|
419 | 419 | |
|
420 | 420 | Affected: |
|
421 | 421 | self.dataOut |
|
422 | 422 | self.basicHeaderObj |
|
423 | 423 | self.systemHeaderObj |
|
424 | 424 | self.radarControllerHeaderObj |
|
425 | 425 | self.processingHeaderObj |
|
426 | 426 | |
|
427 | 427 | Return: None |
|
428 | 428 | """ |
|
429 | 429 | |
|
430 | 430 | Operation.__init__(self, **kwargs) |
|
431 | 431 | |
|
432 | 432 | self.isConfig = False |
|
433 | 433 | |
|
434 | 434 | self.nTotalBlocks = 0 |
|
435 | 435 | |
|
436 | 436 | self.data_spc = None |
|
437 | 437 | |
|
438 | 438 | self.data_cspc = None |
|
439 | 439 | |
|
440 | 440 | self.data_dc = None |
|
441 | 441 | |
|
442 | 442 | self.fp = None |
|
443 | 443 | |
|
444 | 444 | self.flagIsNewFile = 1 |
|
445 | 445 | |
|
446 | 446 | self.nTotalBlocks = 0 |
|
447 | 447 | |
|
448 | 448 | self.flagIsNewBlock = 0 |
|
449 | 449 | |
|
450 | 450 | self.setFile = None |
|
451 | 451 | |
|
452 | 452 | self.dtype = None |
|
453 | 453 | |
|
454 | 454 | self.path = None |
|
455 | 455 | |
|
456 | 456 | self.noMoreFiles = 0 |
|
457 | 457 | |
|
458 | 458 | self.filename = None |
|
459 | 459 | |
|
460 | 460 | self.basicHeaderObj = BasicHeader(LOCALTIME) |
|
461 | 461 | |
|
462 | 462 | self.systemHeaderObj = SystemHeader() |
|
463 | 463 | |
|
464 | 464 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
465 | 465 | |
|
466 | 466 | self.processingHeaderObj = ProcessingHeader() |
|
467 | 467 | |
|
468 | 468 | |
|
469 | 469 | def hasAllDataInBuffer(self): |
|
470 | 470 | return 1 |
|
471 | 471 | |
|
472 | 472 | |
|
473 | 473 | def setBlockDimension(self): |
|
474 | 474 | """ |
|
475 | 475 | Obtiene las formas dimensionales del los subbloques de datos que componen un bloque |
|
476 | 476 | |
|
477 | 477 | Affected: |
|
478 | 478 | self.shape_spc_Buffer |
|
479 | 479 | self.shape_cspc_Buffer |
|
480 | 480 | self.shape_dc_Buffer |
|
481 | 481 | |
|
482 | 482 | Return: None |
|
483 | 483 | """ |
|
484 | 484 | self.shape_spc_Buffer = (self.dataOut.nChannels, |
|
485 | 485 | self.processingHeaderObj.nHeights, |
|
486 | 486 | self.processingHeaderObj.profilesPerBlock) |
|
487 | 487 | |
|
488 | 488 | self.shape_cspc_Buffer = (self.dataOut.nPairs, |
|
489 | 489 | self.processingHeaderObj.nHeights, |
|
490 | 490 | self.processingHeaderObj.profilesPerBlock) |
|
491 | 491 | |
|
492 | 492 | self.shape_dc_Buffer = (self.dataOut.nChannels, |
|
493 | 493 | self.processingHeaderObj.nHeights) |
|
494 | 494 | |
|
495 | 495 | |
|
496 | 496 | def writeBlock(self): |
|
497 | 497 | """ |
|
498 | 498 | Escribe el buffer en el file designado |
|
499 | 499 | |
|
500 | 500 | Affected: |
|
501 | 501 | self.data_spc |
|
502 | 502 | self.data_cspc |
|
503 | 503 | self.data_dc |
|
504 | 504 | self.flagIsNewFile |
|
505 | 505 | self.flagIsNewBlock |
|
506 | 506 | self.nTotalBlocks |
|
507 | 507 | self.nWriteBlocks |
|
508 | 508 | |
|
509 | 509 | Return: None |
|
510 | 510 | """ |
|
511 | 511 | |
|
512 | 512 | spc = numpy.transpose( self.data_spc, (0,2,1) ) |
|
513 | if self.processingHeaderObj.shif_fft: | |
|
513 | if not self.processingHeaderObj.shif_fft: | |
|
514 | 514 | spc = numpy.roll( spc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones |
|
515 | 515 | data = spc.reshape((-1)) |
|
516 | 516 | data = data.astype(self.dtype[0]) |
|
517 | 517 | data.tofile(self.fp) |
|
518 | 518 | |
|
519 | 519 | if self.data_cspc is not None: |
|
520 | 520 | data = numpy.zeros( self.shape_cspc_Buffer, self.dtype ) |
|
521 | 521 | cspc = numpy.transpose( self.data_cspc, (0,2,1) ) |
|
522 | if self.processingHeaderObj.shif_fft: | |
|
522 | if not self.processingHeaderObj.shif_fft: | |
|
523 | 523 | cspc = numpy.roll( cspc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones |
|
524 | 524 | data['real'] = cspc.real |
|
525 | 525 | data['imag'] = cspc.imag |
|
526 | 526 | data = data.reshape((-1)) |
|
527 | 527 | data.tofile(self.fp) |
|
528 | 528 | |
|
529 | 529 | if self.data_dc is not None: |
|
530 | 530 | data = numpy.zeros( self.shape_dc_Buffer, self.dtype ) |
|
531 | 531 | dc = self.data_dc |
|
532 | 532 | data['real'] = dc.real |
|
533 | 533 | data['imag'] = dc.imag |
|
534 | 534 | data = data.reshape((-1)) |
|
535 | 535 | data.tofile(self.fp) |
|
536 | 536 | |
|
537 | 537 | # self.data_spc.fill(0) |
|
538 | 538 | # |
|
539 | 539 | # if self.data_dc is not None: |
|
540 | 540 | # self.data_dc.fill(0) |
|
541 | 541 | # |
|
542 | 542 | # if self.data_cspc is not None: |
|
543 | 543 | # self.data_cspc.fill(0) |
|
544 | 544 | |
|
545 | 545 | self.flagIsNewFile = 0 |
|
546 | 546 | self.flagIsNewBlock = 1 |
|
547 | 547 | self.nTotalBlocks += 1 |
|
548 | 548 | self.nWriteBlocks += 1 |
|
549 | 549 | self.blockIndex += 1 |
|
550 | 550 | |
|
551 | 551 | # print "[Writing] Block = %d04" %self.blockIndex |
|
552 | 552 | |
|
553 | 553 | def putData(self): |
|
554 | 554 | """ |
|
555 | 555 | Setea un bloque de datos y luego los escribe en un file |
|
556 | 556 | |
|
557 | 557 | Affected: |
|
558 | 558 | self.data_spc |
|
559 | 559 | self.data_cspc |
|
560 | 560 | self.data_dc |
|
561 | 561 | |
|
562 | 562 | Return: |
|
563 | 563 | 0 : Si no hay data o no hay mas files que puedan escribirse |
|
564 | 564 | 1 : Si se escribio la data de un bloque en un file |
|
565 | 565 | """ |
|
566 | 566 | |
|
567 | 567 | if self.dataOut.flagNoData: |
|
568 | 568 | return 0 |
|
569 | 569 | |
|
570 | 570 | self.flagIsNewBlock = 0 |
|
571 | 571 | |
|
572 | 572 | if self.dataOut.flagDiscontinuousBlock: |
|
573 | 573 | self.data_spc.fill(0) |
|
574 | 574 | if self.dataOut.data_cspc is not None: |
|
575 | 575 | self.data_cspc.fill(0) |
|
576 | 576 | if self.dataOut.data_dc is not None: |
|
577 | 577 | self.data_dc.fill(0) |
|
578 | 578 | self.setNextFile() |
|
579 | 579 | |
|
580 | 580 | if self.flagIsNewFile == 0: |
|
581 | 581 | self.setBasicHeader() |
|
582 | 582 | |
|
583 | 583 | self.data_spc = self.dataOut.data_spc.copy() |
|
584 | 584 | |
|
585 | 585 | if self.dataOut.data_cspc is not None: |
|
586 | 586 | self.data_cspc = self.dataOut.data_cspc.copy() |
|
587 | 587 | |
|
588 | 588 | if self.dataOut.data_dc is not None: |
|
589 | 589 | self.data_dc = self.dataOut.data_dc.copy() |
|
590 | 590 | |
|
591 | 591 | # #self.processingHeaderObj.dataBlocksPerFile) |
|
592 | 592 | if self.hasAllDataInBuffer(): |
|
593 | 593 | # self.setFirstHeader() |
|
594 | 594 | self.writeNextBlock() |
|
595 | 595 | |
|
596 | 596 | return 1 |
|
597 | 597 | |
|
598 | 598 | def __getBlockSize(self): |
|
599 | 599 | ''' |
|
600 | 600 | Este metodos determina el cantidad de bytes para un bloque de datos de tipo Spectra |
|
601 | 601 | ''' |
|
602 | 602 | |
|
603 | 603 | dtype_width = self.getDtypeWidth() |
|
604 | 604 | |
|
605 | 605 | pts2write = self.dataOut.nHeights * self.dataOut.nFFTPoints |
|
606 | 606 | |
|
607 | 607 | pts2write_SelfSpectra = int(self.dataOut.nChannels * pts2write) |
|
608 | 608 | blocksize = (pts2write_SelfSpectra*dtype_width) |
|
609 | 609 | |
|
610 | 610 | if self.dataOut.data_cspc is not None: |
|
611 | 611 | pts2write_CrossSpectra = int(self.dataOut.nPairs * pts2write) |
|
612 | 612 | blocksize += (pts2write_CrossSpectra*dtype_width*2) |
|
613 | 613 | |
|
614 | 614 | if self.dataOut.data_dc is not None: |
|
615 | 615 | pts2write_DCchannels = int(self.dataOut.nChannels * self.dataOut.nHeights) |
|
616 | 616 | blocksize += (pts2write_DCchannels*dtype_width*2) |
|
617 | 617 | |
|
618 | 618 | # blocksize = blocksize #* datatypeValue * 2 #CORREGIR ESTO |
|
619 | 619 | |
|
620 | 620 | return blocksize |
|
621 | 621 | |
|
622 | 622 | def setFirstHeader(self): |
|
623 | 623 | |
|
624 | 624 | """ |
|
625 | 625 | Obtiene una copia del First Header |
|
626 | 626 | |
|
627 | 627 | Affected: |
|
628 | 628 | self.systemHeaderObj |
|
629 | 629 | self.radarControllerHeaderObj |
|
630 | 630 | self.dtype |
|
631 | 631 | |
|
632 | 632 | Return: |
|
633 | 633 | None |
|
634 | 634 | """ |
|
635 | 635 | |
|
636 | 636 | self.systemHeaderObj = self.dataOut.systemHeaderObj.copy() |
|
637 | 637 | self.systemHeaderObj.nChannels = self.dataOut.nChannels |
|
638 | 638 | self.radarControllerHeaderObj = self.dataOut.radarControllerHeaderObj.copy() |
|
639 | 639 | |
|
640 | 640 | self.processingHeaderObj.dtype = 1 # Spectra |
|
641 | 641 | self.processingHeaderObj.blockSize = self.__getBlockSize() |
|
642 | 642 | self.processingHeaderObj.profilesPerBlock = self.dataOut.nFFTPoints |
|
643 | 643 | self.processingHeaderObj.dataBlocksPerFile = self.blocksPerFile |
|
644 | 644 | self.processingHeaderObj.nWindows = 1 #podria ser 1 o self.dataOut.processingHeaderObj.nWindows |
|
645 | 645 | self.processingHeaderObj.nCohInt = self.dataOut.nCohInt# Se requiere para determinar el valor de timeInterval |
|
646 | 646 | self.processingHeaderObj.nIncohInt = self.dataOut.nIncohInt |
|
647 | 647 | self.processingHeaderObj.totalSpectra = self.dataOut.nPairs + self.dataOut.nChannels |
|
648 | 648 | self.processingHeaderObj.shif_fft = self.dataOut.flagShiftFFT |
|
649 | 649 | |
|
650 | 650 | if self.processingHeaderObj.totalSpectra > 0: |
|
651 | 651 | channelList = [] |
|
652 | 652 | for channel in range(self.dataOut.nChannels): |
|
653 | 653 | channelList.append(channel) |
|
654 | 654 | channelList.append(channel) |
|
655 | 655 | |
|
656 | 656 | pairsList = [] |
|
657 | 657 | if self.dataOut.nPairs > 0: |
|
658 | 658 | for pair in self.dataOut.pairsList: |
|
659 | 659 | pairsList.append(pair[0]) |
|
660 | 660 | pairsList.append(pair[1]) |
|
661 | 661 | |
|
662 | 662 | spectraComb = channelList + pairsList |
|
663 | 663 | spectraComb = numpy.array(spectraComb, dtype="u1") |
|
664 | 664 | self.processingHeaderObj.spectraComb = spectraComb |
|
665 | 665 | |
|
666 | 666 | if self.dataOut.code is not None: |
|
667 | 667 | self.processingHeaderObj.code = self.dataOut.code |
|
668 | 668 | self.processingHeaderObj.nCode = self.dataOut.nCode |
|
669 | 669 | self.processingHeaderObj.nBaud = self.dataOut.nBaud |
|
670 | 670 | |
|
671 | 671 | if self.processingHeaderObj.nWindows != 0: |
|
672 | 672 | self.processingHeaderObj.firstHeight = self.dataOut.heightList[0] |
|
673 | 673 | self.processingHeaderObj.deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
674 | 674 | self.processingHeaderObj.nHeights = self.dataOut.nHeights |
|
675 | 675 | self.processingHeaderObj.samplesWin = self.dataOut.nHeights |
|
676 | 676 | |
|
677 | 677 | self.processingHeaderObj.processFlags = self.getProcessFlags() |
|
678 | 678 | |
|
679 | 679 | self.setBasicHeader() |
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