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import os
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import time
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import numpy
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import datetime
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import numpy as np
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import matplotlib.pyplot as plt
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from mpl_toolkits.axes_grid1 import make_axes_locatable
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from matplotlib.ticker import FuncFormatter, LinearLocator
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from schainpy.model.proc.jroproc_base import Operation
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func = lambda x, pos: ('%s') %(datetime.datetime.utcfromtimestamp(x).strftime('%H:%M'))
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d1970 = datetime.datetime(1970,1,1)
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class PlotData(Operation):
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__code = 'Figure'
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__MAXNUMX = 80
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__MAXNUMY = 80
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__missing = 1E30
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def __init__(self):
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Operation.__init__(self)
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self.xmin = None
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self.xmax = None
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self.newdataOut = None
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self.dataOut = None
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self.isConfig = False
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self.figure = None
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self.width = 6
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self.height = 4
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def setup(self, dataOut, **kwargs):
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self.first = True
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self.localtime = kwargs.pop('localtime', True)
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self.show = kwargs.pop('show', True)
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self.save = kwargs.pop('save', False)
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self.pause = kwargs.pop('pause', False)
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self.time = []
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self.nblock = 0
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self.z = []
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self.data = [{} for __ in dataOut.channelList]
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self.axes = []
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self.colormap = kwargs.get('colormap', 'jet')
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self.title = kwargs.get('wintitle', '')
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self.xaxis = kwargs.get('xaxis', None)
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self.zmin = kwargs.get('zmin', None)
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self.zmax = kwargs.get('zmax', None)
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xmin = kwargs.get('xmin', 0)
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xmax = kwargs.get('xmax', xmin+4)
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dt = dataOut.datatime.date()
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dtmin = datetime.datetime.combine(dt, datetime.time(xmin, 0, 0))
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dtmax = datetime.datetime.combine(dt, datetime.time(xmax, 59, 59))
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self.xmin = (dtmin-d1970).total_seconds()
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self.xmax = (dtmax-d1970).total_seconds()
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self.ymin = kwargs.get('ymin', None)
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self.ymax = kwargs.get('ymax', None)
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if self.figure is None:
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self.figure = plt.figure()
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else:
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self.figure.clf()
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self.setup_fig()
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for n in range(dataOut.nChannels):
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ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
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ax.firsttime = True
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self.axes.append(ax)
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self.setup_fig()
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self.figure.set_size_inches (self.width, self.height)
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def fill_gaps(self, x_buffer, y_buffer, z_buffer):
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if x_buffer.shape[0] < 2:
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return x_buffer, y_buffer, z_buffer
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deltas = x_buffer[1:] - x_buffer[0:-1]
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x_median = np.median(deltas)
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index = np.where(deltas > 5*x_median)
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if len(index[0]) != 0:
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z_buffer[::,index[0],::] = self.__missing
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z_buffer = np.ma.masked_inside(z_buffer,
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0.99*self.__missing,
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1.01*self.__missing)
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return x_buffer, y_buffer, z_buffer
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def decimate(self):
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dx = int(len(self.x)/self.__MAXNUMX) + 1
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dy = int(len(self.y)/self.__MAXNUMY) + 1
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x = self.x[::dx]
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y = self.y[::dy]
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z = self.z[::, ::dx, ::dy]
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return x, y, z
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def _plot(self):
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self.plot()
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self.figure.suptitle(self.title+self.__code)
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if self.save:
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figname = os.path.join(self.save, '{}_{}.png'.format(self.__code,
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self.plot_dt.strftime('%y%m%d_%H%M%S')))
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print 'Saving figure: {}'.format(figname)
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self.figure.savefig(figname)
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self.figure.canvas.draw()
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if self.show:
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self.figure.show()
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if self.pause:
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raw_input('Press <ENTER> to continue')
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def update(self):
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pass
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def run(self, dataOut, **kwargs):
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self.dataOut = dataOut
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if not self.isConfig:
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self.setup(dataOut, **kwargs)
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self.isConfig = True
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self.nblock += 1
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self.update()
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if dataOut.ltctime>=self.xmax:
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self._plot()
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self.isConfig = False
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def close(self):
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if self.dataOut:
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self._plot()
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class PlotSpectraData(PlotData):
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__code = 'Spectra'
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def setup_fig(self):
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pass
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def update(self):
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for ch in self.dataOut.channelList:
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self.data[ch] = self.dataOut.data_spc[ch]
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def plot(self):
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pass
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class PlotRTIData(PlotData):
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__code = 'RTI'
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def setup_fig(self):
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self.ncols = 1
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self.nrows = self.dataOut.nChannels
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self.width = 8
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self.height = 2.2*self.nrows
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self.ylabel = 'Range [Km]'
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def update(self):
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self.time.append(self.dataOut.ltctime)
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for ch in self.dataOut.channelList:
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self.data[ch][self.dataOut.ltctime] = self.dataOut.getPower()[ch]
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def plot(self):
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self.plot_dt = datetime.datetime.utcfromtimestamp(self.time[-2])
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self.time.sort()
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self.x = self.time
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self.y = self.dataOut.getHeiRange()
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self.z = []
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for ch in self.dataOut.channelList:
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self.z.append([self.data[ch][t] for t in self.time])
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self.x = np.array(self.x)
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self.z = np.array(self.z)
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for n, ax in enumerate(self.axes):
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if self.xaxis=='time':
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ax.xaxis.set_major_formatter(FuncFormatter(func))
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ax.xaxis.set_major_locator(LinearLocator(6))
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ax.yaxis.set_major_locator(LinearLocator(4))
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ax.set_ylabel(self.ylabel)
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ax.set_xlim(self.xmin, self.xmax)
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ax.set_title('Channel {} {}'.format(self.dataOut.channelList[n],
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self.plot_dt.strftime('%y/%m/%d %H:%M:%S')),
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size=8)
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self.decimate()
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for n, ax in enumerate(self.axes):
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x, y, z = self.fill_gaps(*self.decimate())
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if ax.firsttime:
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ymin = self.ymin if self.ymin else np.nanmin(self.y)
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ymax = self.ymax if self.ymax else np.nanmax(self.y)
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zmin = self.zmin if self.zmin else np.nanmin(self.z)
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zmax = self.zmax if self.zmax else np.nanmax(self.z)
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plot = ax.pcolormesh(x, y, z[n].T,
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vmin=zmin,
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vmax=zmax,
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cmap=plt.get_cmap(self.colormap)
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)
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divider = make_axes_locatable(ax)
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cax = divider.new_horizontal(size='3%', pad=0.05)
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self.figure.add_axes(cax)
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plt.colorbar(plot, cax)
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ax.set_ylim(self.ymin, self.ymax)
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ax.firsttime = False
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else:
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plot = ax.pcolormesh(x, y, z[n].T)
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self.figure.subplots_adjust(wspace=None, hspace=0.5)
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class PlotSNRData(PlotRTIData):
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__code = 'SNR'
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def update(self):
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self.time.append(self.dataOut.ltctime)
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for ch in self.dataOut.channelList:
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self.data[ch][self.dataOut.ltctime] = 10*np.log10(self.dataOut.data_SNR[ch])
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