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2 | import os | |
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3 | import time | |
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4 | import numpy | |
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5 | import datetime | |
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6 | import numpy as np | |
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7 | import matplotlib.pyplot as plt | |
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8 | from mpl_toolkits.axes_grid1 import make_axes_locatable | |
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9 | from matplotlib.ticker import FuncFormatter, LinearLocator | |
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10 | ||
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11 | from schainpy.model.proc.jroproc_base import Operation | |
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12 | ||
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13 | func = lambda x, pos: ('%s') %(datetime.datetime.utcfromtimestamp(x).strftime('%H:%M')) | |
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14 | ||
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15 | d1970 = datetime.datetime(1970,1,1) | |
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16 | ||
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17 | ||
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18 | class PlotData(Operation): | |
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19 | ||
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20 | __MAXNUMX = 80 | |
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21 | __MAXNUMY = 80 | |
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22 | __missing = 1E30 | |
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23 | ||
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24 | def __init__(self): | |
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25 | ||
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26 | Operation.__init__(self) | |
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27 | self.xmin = None | |
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28 | self.xmax = None | |
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29 | self.newdataOut = None | |
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30 | self.dataOut = None | |
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31 | self.isConfig = False | |
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32 | self.figure = None | |
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33 | ||
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34 | def setup(self, dataOut, **kwargs): | |
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35 | ||
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36 | self.first = True | |
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37 | self.plottype = kwargs.pop('plottype', 'rti') | |
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38 | self.localtime = kwargs.pop('localtime', True) | |
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39 | self.show = kwargs.pop('show', True) | |
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40 | self.save = kwargs.pop('save', False) | |
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41 | self.pause = kwargs.pop('pause', False) | |
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42 | self.time = [] | |
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43 | self.nblock = 0 | |
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44 | self.z = [] | |
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45 | self.data = [{} for __ in dataOut.channelList] | |
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46 | self.axes = [] | |
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47 | self.colormap = kwargs.get('colormap', 'jet') | |
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48 | self.title = kwargs.get('wintitle', self.plottype.upper()) | |
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49 | self.xaxis = kwargs.get('xaxis', None) | |
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50 | self.zmin = kwargs.get('zmin', None) | |
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51 | self.zmax = kwargs.get('zmax', None) | |
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52 | ||
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53 | xmin = kwargs.get('xmin', 0) | |
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54 | xmax = kwargs.get('xmax', xmin+4) | |
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55 | ||
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56 | dt = dataOut.datatime.date() | |
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57 | dtmin = datetime.datetime.combine(dt, datetime.time(xmin, 0, 0)) | |
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58 | dtmax = datetime.datetime.combine(dt, datetime.time(xmax, 59, 59)) | |
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59 | ||
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60 | self.xmin = (dtmin-d1970).total_seconds() | |
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61 | self.xmax = (dtmax-d1970).total_seconds() | |
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62 | ||
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63 | if self.plottype in ('rti',): | |
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64 | self.ncols = 1 | |
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65 | self.nrows = dataOut.nChannels | |
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66 | self.width = 8 | |
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67 | self.height = 2.2*self.nrows | |
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68 | self.ylabel = 'Range [Km]' | |
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69 | self.y = dataOut.getHeiRange() | |
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70 | ||
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71 | self.ymin = kwargs.get('ymin', min(self.y)) | |
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72 | self.ymax = kwargs.get('ymax', max(self.y)) | |
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73 | ||
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74 | if self.figure is None: | |
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75 | self.figure = plt.figure() | |
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76 | else: | |
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77 | self.figure.clf() | |
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78 | ||
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79 | for n in range(dataOut.nChannels): | |
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80 | ax = self.figure.add_subplot(self.nrows, self.ncols, n+1) | |
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81 | ax.firsttime = True | |
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82 | self.axes.append(ax) | |
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83 | ||
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84 | self.figure.set_size_inches (self.width, self.height) | |
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85 | ||
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86 | def fill_gaps(self, x_buffer, y_buffer, z_buffer): | |
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87 | ||
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88 | if x_buffer.shape[0] < 2: | |
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89 | return x_buffer, y_buffer, z_buffer | |
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90 | ||
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91 | deltas = x_buffer[1:] - x_buffer[0:-1] | |
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92 | x_median = np.median(deltas) | |
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93 | ||
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94 | index = np.where(deltas > 5*x_median) | |
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95 | ||
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96 | if len(index[0]) != 0: | |
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97 | z_buffer[index[0],::] = self.__missing | |
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98 | z_buffer = np.ma.masked_inside(z_buffer, | |
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99 | 0.99*self.__missing, | |
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100 | 1.01*self.__missing) | |
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101 | ||
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102 | return x_buffer, y_buffer, z_buffer | |
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103 | ||
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104 | def plot(self): | |
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105 | ||
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106 | dt = datetime.datetime.utcfromtimestamp(self.time[-2]) | |
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107 | ||
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108 | if self.plottype=='rti': | |
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109 | self.time.sort() | |
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110 | for ch in self.dataOut.channelList: | |
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111 | self.z.append([self.data[ch][t] for t in self.time]) | |
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112 | self.x = np.array(self.time) | |
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113 | self.z = np.array(self.z) | |
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114 | self.plot_rti() | |
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115 | ||
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116 | for n, ax in enumerate(self.axes): | |
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117 | ||
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118 | if self.xaxis=='time': | |
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119 | ax.xaxis.set_major_formatter(FuncFormatter(func)) | |
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120 | ax.xaxis.set_major_locator(LinearLocator(6)) | |
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121 | ||
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122 | ax.yaxis.set_major_locator(LinearLocator(4)) | |
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123 | ||
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124 | ax.set_ylabel(self.ylabel) | |
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125 | ax.set_ylim(self.ymin, self.ymax) | |
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126 | ax.set_xlim(self.xmin, self.xmax) | |
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127 | ||
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128 | ax.set_title('Channel {} {}'.format( | |
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129 | self.dataOut.channelList[n], | |
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130 | dt.strftime('%y/%m/%d %H:%M:%S'), | |
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131 | size=6)) | |
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132 | ||
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133 | if self.save: | |
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134 | figname = os.path.join(self.save, 'rti_{}.png'.format(dt.strftime('%y%m%d_%H%M%S'))) | |
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135 | print 'Saving figure: {}'.format(figname) | |
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136 | self.figure.savefig(figname) | |
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137 | ||
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138 | self.figure.canvas.draw() | |
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139 | if self.show: | |
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140 | self.figure.show() | |
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141 | if self.pause: | |
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142 | raw_input('Press <ENTER> to continue') | |
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143 | ||
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144 | def plot_rti(self): | |
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145 | ||
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146 | for n, ax in enumerate(self.axes): | |
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147 | x, y, z = self.fill_gaps(self.x, self.y, self.z[n]) | |
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148 | if ax.firsttime: | |
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149 | zmin = self.zmin if self.zmin else np.nanmin(self.z) | |
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150 | zmax = self.zmax if self.zmax else np.nanmax(self.z) | |
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151 | plot = ax.pcolormesh(x, y, z.T, | |
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152 | vmin=zmin, | |
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153 | vmax=zmax, | |
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154 | cmap=plt.get_cmap(self.colormap) | |
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155 | ) | |
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156 | divider = make_axes_locatable(ax) | |
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157 | cax = divider.new_horizontal(size='3%', pad=0.05) | |
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158 | self.figure.add_axes(cax) | |
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159 | plt.colorbar(plot, cax) | |
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160 | ax.firsttime = False | |
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161 | else: | |
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162 | plot = ax.pcolormesh(x, y, z.T, | |
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163 | vmin=zmin, | |
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164 | vmax=zmax, | |
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165 | cmap=plt.get_cmap(self.colormap) | |
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166 | ) | |
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167 | ||
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168 | self.figure.suptitle(self.title) | |
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169 | self.figure.subplots_adjust(wspace=None, hspace=0.5) | |
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170 | ||
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171 | def update(self): | |
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172 | ||
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173 | self.nblock += 1 | |
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174 | self.time.append(self.dataOut.ltctime) | |
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175 | if self.plottype=='rti': | |
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176 | for ch in self.dataOut.channelList: | |
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177 | self.data[ch][self.dataOut.ltctime] = self.dataOut.getPower()[ch] | |
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178 | ||
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179 | def run(self, dataOut, **kwargs): | |
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180 | ||
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181 | self.dataOut = dataOut | |
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182 | ||
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183 | if not self.isConfig: | |
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184 | self.setup(dataOut, **kwargs) | |
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185 | self.isConfig = True | |
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186 | ||
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187 | self.update() | |
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188 | ||
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189 | if dataOut.ltctime>=self.xmax: | |
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190 | self.plot() | |
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191 | self.isConfig = False | |
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192 | ||
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193 | def close(self): | |
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194 | ||
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195 | self.plot() | |
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196 | No newline at end of file | |
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