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# Copyright (c) 2012-2020 Jicamarca Radio Observatory
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# All rights reserved.
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#
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# Distributed under the terms of the BSD 3-clause license.
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"""Classes to plo Specra Heis data
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"""
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import numpy
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from schainpy.model.graphics.jroplot_base import Plot, plt
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import matplotlib.pyplot as plt
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class SpectraHeisPlot(Plot):
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CODE = 'spc_heis'
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def setup(self):
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self.nplots = len(self.data.channels)
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self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
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self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
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self.height = 2.6 * self.nrows
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self.width = 3.5 * self.ncols
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self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.95, 'bottom': 0.08})
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self.ylabel = 'Intensity [dB]'
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self.xlabel = 'Frequency [KHz]'
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self.colorbar = False
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def update(self, dataOut):
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data = {}
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meta = {}
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spc = 10*numpy.log10(dataOut.data_spc / dataOut.normFactor)
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data['spc_heis'] = spc
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return data, meta
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def plot(self):
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c = 3E8
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deltaHeight = self.data.yrange[1] - self.data.yrange[0] # yrange = heightList
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x = numpy.arange(-1*len(self.data.yrange)/2., len(self.data.yrange)/2.)*(c/(2*deltaHeight*len(self.data.yrange)*1000))
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self.y = self.data[-1]['spc_heis']
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self.titles = []
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Maintitle = "Range from %d km to %d km" %(int(self.data.yrange[0]),int(self.data.yrange[-1]))
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for n, ax in enumerate(self.axes):
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ychannel = self.y[n,:]
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if ax.firsttime:
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self.xmin = min(x) if self.xmin is None else self.xmin
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self.xmax = max(x) if self.xmax is None else self.xmax
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ax.plt = ax.plot(x, ychannel, lw=1, color='b')[0]
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else:
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ax.plt.set_data(x, ychannel)
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self.titles.append("Channel {}: {:4.2f}dB".format(n, numpy.max(ychannel)))
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plt.suptitle(Maintitle)
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class RTIHeisPlot(Plot):
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CODE = 'rti_heis'
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def setup(self):
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self.xaxis = 'time'
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self.ncols = 1
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self.nrows = 1
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self.nplots = 1
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self.ylabel = 'Intensity [dB]'
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self.xlabel = 'Time'
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self.titles = ['RTI']
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self.colorbar = False
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self.height = 4
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self.plots_adjust.update({'right': 0.85 })
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def update(self, dataOut):
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data = {}
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meta = {}
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spc = dataOut.data_spc / dataOut.normFactor
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spc = 10*numpy.log10(numpy.average(spc, axis=1))
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data['rti_heis'] = spc
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return data, meta
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def plot(self):
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x = self.data.times
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Y = self.data['rti_heis']
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if self.axes[0].firsttime:
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self.ymin = numpy.nanmin(Y) - 5 if self.ymin == None else self.ymin
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self.ymax = numpy.nanmax(Y) + 5 if self.ymax == None else self.ymax
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for ch in self.data.channels:
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y = Y[ch]
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self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch))
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plt.legend(bbox_to_anchor=(1.18, 1.0))
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else:
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for ch in self.data.channels:
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y = Y[ch]
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self.axes[0].lines[ch].set_data(x, y)
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