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import os
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import os
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import zmq
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import zmq
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import time
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import time
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import numpy
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import numpy
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import datetime
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import datetime
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import numpy as np
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import numpy as np
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import matplotlib
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import matplotlib
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import glob
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import glob
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matplotlib.use('TkAgg')
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matplotlib.use('TkAgg')
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import matplotlib.pyplot as plt
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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 mpl_toolkits.axes_grid1 import make_axes_locatable
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from matplotlib.ticker import FuncFormatter, LinearLocator
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from matplotlib.ticker import FuncFormatter, LinearLocator
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from multiprocessing import Process
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from multiprocessing import Process
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from schainpy.model.proc.jroproc_base import Operation
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from schainpy.model.proc.jroproc_base import Operation
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plt.ion()
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plt.ion()
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func = lambda x, pos: ('%s') %(datetime.datetime.fromtimestamp(x).strftime('%H:%M'))
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func = lambda x, pos: ('%s') %(datetime.datetime.fromtimestamp(x).strftime('%H:%M'))
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d1970 = datetime.datetime(1970,1,1)
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d1970 = datetime.datetime(1970,1,1)
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class PlotData(Operation, Process):
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class PlotData(Operation, Process):
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CODE = 'Figure'
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CODE = 'Figure'
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colormap = 'jro'
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colormap = 'jro'
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CONFLATE = False
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CONFLATE = False
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__MAXNUMX = 80
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__MAXNUMX = 80
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__missing = 1E30
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__missing = 1E30
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def __init__(self, **kwargs):
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def __init__(self, **kwargs):
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Operation.__init__(self, plot=True, **kwargs)
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Operation.__init__(self, plot=True, **kwargs)
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Process.__init__(self)
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Process.__init__(self)
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self.kwargs['code'] = self.CODE
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self.kwargs['code'] = self.CODE
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self.mp = False
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self.mp = False
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self.dataOut = None
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self.dataOut = None
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self.isConfig = False
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self.isConfig = False
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self.figure = None
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self.figure = None
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self.axes = []
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self.axes = []
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self.localtime = kwargs.pop('localtime', True)
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self.localtime = kwargs.pop('localtime', True)
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self.show = kwargs.get('show', True)
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self.show = kwargs.get('show', True)
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self.save = kwargs.get('save', False)
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self.save = kwargs.get('save', False)
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self.colormap = kwargs.get('colormap', self.colormap)
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self.colormap = kwargs.get('colormap', self.colormap)
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self.colormap_coh = kwargs.get('colormap_coh', 'jet')
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self.colormap_coh = kwargs.get('colormap_coh', 'jet')
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self.colormap_phase = kwargs.get('colormap_phase', 'RdBu_r')
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self.colormap_phase = kwargs.get('colormap_phase', 'RdBu_r')
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self.showprofile = kwargs.get('showprofile', True)
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self.showprofile = kwargs.get('showprofile', True)
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self.title = kwargs.get('wintitle', '')
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self.title = kwargs.get('wintitle', '')
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self.xaxis = kwargs.get('xaxis', 'frequency')
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self.xaxis = kwargs.get('xaxis', 'frequency')
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self.zmin = kwargs.get('zmin', 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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self.zmax = kwargs.get('zmax', None)
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self.xmin = kwargs.get('xmin', None)
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self.xmin = kwargs.get('xmin', None)
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self.xmax = kwargs.get('xmax', None)
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self.xmax = kwargs.get('xmax', None)
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self.xrange = kwargs.get('xrange', 24)
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self.xrange = kwargs.get('xrange', 24)
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self.ymin = kwargs.get('ymin', None)
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self.ymin = kwargs.get('ymin', None)
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self.ymax = kwargs.get('ymax', None)
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self.ymax = kwargs.get('ymax', None)
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self.__MAXNUMY = kwargs.get('decimation', 80)
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self.__MAXNUMY = kwargs.get('decimation', 80)
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self.throttle_value = 5
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self.throttle_value = 5
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self.times = []
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self.times = []
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#self.interactive = self.kwargs['parent']
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#self.interactive = self.kwargs['parent']
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'''
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'''
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this new parameter is created to plot data from varius channels at different figures
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this new parameter is created to plot data from varius channels at different figures
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1. crear una lista de figuras donde se puedan plotear las figuras,
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1. crear una lista de figuras donde se puedan plotear las figuras,
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2. dar las opciones de configuracion a cada figura, estas opciones son iguales para ambas figuras
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2. dar las opciones de configuracion a cada figura, estas opciones son iguales para ambas figuras
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3. probar?
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3. probar?
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'''
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'''
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self.ind_plt_ch = kwargs.get('ind_plt_ch', False)
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self.ind_plt_ch = kwargs.get('ind_plt_ch', False)
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self.figurelist = None
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self.figurelist = None
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def fill_gaps(self, x_buffer, y_buffer, z_buffer):
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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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if x_buffer.shape[0] < 2:
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return x_buffer, y_buffer, z_buffer
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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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deltas = x_buffer[1:] - x_buffer[0:-1]
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x_median = np.median(deltas)
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x_median = np.median(deltas)
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index = np.where(deltas > 5*x_median)
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index = np.where(deltas > 5*x_median)
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if len(index[0]) != 0:
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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[::, index[0], ::] = self.__missing
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z_buffer = np.ma.masked_inside(z_buffer,
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z_buffer = np.ma.masked_inside(z_buffer,
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0.99*self.__missing,
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0.99*self.__missing,
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1.01*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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return x_buffer, y_buffer, z_buffer
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def decimate(self):
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def decimate(self):
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# dx = int(len(self.x)/self.__MAXNUMX) + 1
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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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dy = int(len(self.y)/self.__MAXNUMY) + 1
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# x = self.x[::dx]
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# x = self.x[::dx]
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x = self.x
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x = self.x
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y = self.y[::dy]
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y = self.y[::dy]
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z = self.z[::, ::, ::dy]
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z = self.z[::, ::, ::dy]
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return x, y, z
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return x, y, z
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'''
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'''
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JM:
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JM:
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elimana las otras imagenes generadas debido a que lso workers no llegan en orden y le pueden
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elimana las otras imagenes generadas debido a que lso workers no llegan en orden y le pueden
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poner otro tiempo a la figura q no necesariamente es el ultimo.
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poner otro tiempo a la figura q no necesariamente es el ultimo.
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Solo se realiza cuando termina la imagen.
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Solo se realiza cuando termina la imagen.
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Problemas:
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Problemas:
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File "/home/ci-81/workspace/schainv2.3/schainpy/model/graphics/jroplot_data.py", line 145, in __plot
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File "/home/ci-81/workspace/schainv2.3/schainpy/model/graphics/jroplot_data.py", line 145, in __plot
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for n, eachfigure in enumerate(self.figurelist):
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for n, eachfigure in enumerate(self.figurelist):
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TypeError: 'NoneType' object is not iterable
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TypeError: 'NoneType' object is not iterable
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'''
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'''
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def deleteanotherfiles(self):
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def deleteanotherfiles(self):
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figurenames=[]
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figurenames=[]
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if self.figurelist != None:
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if self.figurelist != None:
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for n, eachfigure in enumerate(self.figurelist):
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for n, eachfigure in enumerate(self.figurelist):
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#add specific name for each channel in channelList
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#add specific name for each channel in channelList
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ghostfigname = os.path.join(self.save, '{}_{}_{}'.format(self.titles[n].replace(' ',''),self.CODE,
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ghostfigname = os.path.join(self.save, '{}_{}_{}'.format(self.titles[n].replace(' ',''),self.CODE,
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datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d')))
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datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d')))
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figname = os.path.join(self.save, '{}_{}_{}.png'.format(self.titles[n].replace(' ',''),self.CODE,
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figname = os.path.join(self.save, '{}_{}_{}.png'.format(self.titles[n].replace(' ',''),self.CODE,
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datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
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datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
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for ghostfigure in glob.glob(ghostfigname+'*'): #ghostfigure will adopt all posible names of figures
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for ghostfigure in glob.glob(ghostfigname+'*'): #ghostfigure will adopt all posible names of figures
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if ghostfigure != figname:
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if ghostfigure != figname:
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os.remove(ghostfigure)
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os.remove(ghostfigure)
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print 'Removing GhostFigures:' , figname
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print 'Removing GhostFigures:' , figname
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else :
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else :
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'''Erasing ghost images for just on******************'''
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'''Erasing ghost images for just on******************'''
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ghostfigname = os.path.join(self.save, '{}_{}'.format(self.CODE,datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d')))
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ghostfigname = os.path.join(self.save, '{}_{}'.format(self.CODE,datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d')))
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figname = os.path.join(self.save, '{}_{}.png'.format(self.CODE,datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
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figname = os.path.join(self.save, '{}_{}.png'.format(self.CODE,datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
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for ghostfigure in glob.glob(ghostfigname+'*'): #ghostfigure will adopt all posible names of figures
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for ghostfigure in glob.glob(ghostfigname+'*'): #ghostfigure will adopt all posible names of figures
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if ghostfigure != figname:
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if ghostfigure != figname:
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os.remove(ghostfigure)
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os.remove(ghostfigure)
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print 'Removing GhostFigures:' , figname
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print 'Removing GhostFigures:' , figname
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def __plot(self):
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def __plot(self):
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print 'plotting...{}'.format(self.CODE)
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print 'plotting...{}'.format(self.CODE)
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if self.ind_plt_ch is False : #standard
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if self.ind_plt_ch is False : #standard
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if self.show:
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if self.show:
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self.figure.show()
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self.figure.show()
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self.plot()
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self.plot()
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plt.tight_layout()
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plt.tight_layout()
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self.figure.canvas.manager.set_window_title('{} {} - {}'.format(self.title, self.CODE.upper(),
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self.figure.canvas.manager.set_window_title('{} {} - {}'.format(self.title, self.CODE.upper(),
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datetime.datetime.fromtimestamp(self.max_time).strftime('%Y/%m/%d')))
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datetime.datetime.fromtimestamp(self.max_time).strftime('%Y/%m/%d')))
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else :
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else :
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print 'len(self.figurelist): ',len(self.figurelist)
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print 'len(self.figurelist): ',len(self.figurelist)
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for n, eachfigure in enumerate(self.figurelist):
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for n, eachfigure in enumerate(self.figurelist):
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if self.show:
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if self.show:
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eachfigure.show()
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eachfigure.show()
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self.plot() # ok? como elijo que figura?
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self.plot() # ok? como elijo que figura?
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#eachfigure.subplots_adjust(left=0.2)
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#eachfigure.subplots_adjust(left=0.2)
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#eachfigure.subplots_adjuccst(right=0.2)
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#eachfigure.subplots_adjuccst(right=0.2)
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eachfigure.tight_layout() # ajuste de cada subplot
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eachfigure.tight_layout() # ajuste de cada subplot
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eachfigure.canvas.manager.set_window_title('{} {} - {}'.format(self.title[n], self.CODE.upper(),
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eachfigure.canvas.manager.set_window_title('{} {} - {}'.format(self.title[n], self.CODE.upper(),
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159
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datetime.datetime.fromtimestamp(self.max_time).strftime('%Y/%m/%d')))
|
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159
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datetime.datetime.fromtimestamp(self.max_time).strftime('%Y/%m/%d')))
|
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|
160
|
|
|
160
|
|
|
|
161
|
# if self.save:
|
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161
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# if self.save:
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162
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# if self.ind_plt_ch is False : #standard
|
|
162
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# if self.ind_plt_ch is False : #standard
|
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163
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# figname = os.path.join(self.save, '{}_{}.png'.format(self.CODE,
|
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163
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# figname = os.path.join(self.save, '{}_{}.png'.format(self.CODE,
|
|
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164
|
# datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
|
|
164
|
# datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
|
|
|
165
|
# print 'Saving figure: {}'.format(figname)
|
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165
|
# print 'Saving figure: {}'.format(figname)
|
|
|
166
|
# self.figure.savefig(figname)
|
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166
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# self.figure.savefig(figname)
|
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167
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# else :
|
|
167
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# else :
|
|
|
168
|
# for n, eachfigure in enumerate(self.figurelist):
|
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168
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# for n, eachfigure in enumerate(self.figurelist):
|
|
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169
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# #add specific name for each channel in channelList
|
|
169
|
# #add specific name for each channel in channelList
|
|
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170
|
# figname = os.path.join(self.save, '{}_{}_{}.png'.format(self.titles[n],self.CODE,
|
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170
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# figname = os.path.join(self.save, '{}_{}_{}.png'.format(self.titles[n],self.CODE,
|
|
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171
|
# datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
|
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171
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# datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
|
|
|
172
|
#
|
|
172
|
#
|
|
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173
|
# print 'Saving figure: {}'.format(figname)
|
|
173
|
# print 'Saving figure: {}'.format(figname)
|
|
|
174
|
# eachfigure.savefig(figname)
|
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174
|
# eachfigure.savefig(figname)
|
|
|
175
|
|
|
175
|
|
|
|
176
|
if self.ind_plt_ch is False :
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176
|
if self.ind_plt_ch is False :
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177
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self.figure.canvas.draw()
|
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177
|
self.figure.canvas.draw()
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178
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else :
|
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178
|
else :
|
|
|
179
|
for eachfigure in self.figurelist:
|
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179
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for eachfigure in self.figurelist:
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180
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eachfigure.canvas.draw()
|
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180
|
eachfigure.canvas.draw()
|
|
|
181
|
|
|
181
|
|
|
|
182
|
if self.save:
|
|
182
|
if self.save:
|
|
|
183
|
if self.ind_plt_ch is False : #standard
|
|
183
|
if self.ind_plt_ch is False : #standard
|
|
|
184
|
figname = os.path.join(self.save, '{}_{}.png'.format(self.CODE,
|
|
184
|
figname = os.path.join(self.save, '{}_{}.png'.format(self.CODE,
|
|
|
185
|
datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
|
|
185
|
datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
|
|
|
186
|
print 'Saving figure: {}'.format(figname)
|
|
186
|
print 'Saving figure: {}'.format(figname)
|
|
|
187
|
self.figure.savefig(figname)
|
|
187
|
self.figure.savefig(figname)
|
|
|
188
|
else :
|
|
188
|
else :
|
|
|
189
|
for n, eachfigure in enumerate(self.figurelist):
|
|
189
|
for n, eachfigure in enumerate(self.figurelist):
|
|
|
190
|
#add specific name for each channel in channelList
|
|
190
|
#add specific name for each channel in channelList
|
|
|
191
|
figname = os.path.join(self.save, '{}_{}_{}.png'.format(self.titles[n].replace(' ',''),self.CODE,
|
|
191
|
figname = os.path.join(self.save, '{}_{}_{}.png'.format(self.titles[n].replace(' ',''),self.CODE,
|
|
|
192
|
datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
|
|
192
|
datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
|
|
|
193
|
|
|
193
|
|
|
|
194
|
print 'Saving figure: {}'.format(figname)
|
|
194
|
print 'Saving figure: {}'.format(figname)
|
|
|
195
|
eachfigure.savefig(figname)
|
|
195
|
eachfigure.savefig(figname)
|
|
|
196
|
|
|
196
|
|
|
|
197
|
|
|
197
|
|
|
|
198
|
def plot(self):
|
|
198
|
def plot(self):
|
|
|
199
|
|
|
199
|
|
|
|
200
|
print 'plotting...{}'.format(self.CODE.upper())
|
|
200
|
print 'plotting...{}'.format(self.CODE.upper())
|
|
|
201
|
return
|
|
201
|
return
|
|
|
202
|
|
|
202
|
|
|
|
203
|
def run(self):
|
|
203
|
def run(self):
|
|
|
204
|
|
|
204
|
|
|
|
205
|
print '[Starting] {}'.format(self.name)
|
|
205
|
print '[Starting] {}'.format(self.name)
|
|
|
206
|
|
|
206
|
|
|
|
207
|
context = zmq.Context()
|
|
207
|
context = zmq.Context()
|
|
|
208
|
receiver = context.socket(zmq.SUB)
|
|
208
|
receiver = context.socket(zmq.SUB)
|
|
|
209
|
receiver.setsockopt(zmq.SUBSCRIBE, '')
|
|
209
|
receiver.setsockopt(zmq.SUBSCRIBE, '')
|
|
|
210
|
receiver.setsockopt(zmq.CONFLATE, self.CONFLATE)
|
|
210
|
receiver.setsockopt(zmq.CONFLATE, self.CONFLATE)
|
|
|
211
|
|
|
211
|
|
|
|
212
|
if 'server' in self.kwargs['parent']:
|
|
212
|
if 'server' in self.kwargs['parent']:
|
|
|
213
|
receiver.connect('ipc:///tmp/{}.plots'.format(self.kwargs['parent']['server']))
|
|
213
|
receiver.connect('ipc:///tmp/{}.plots'.format(self.kwargs['parent']['server']))
|
|
|
214
|
else:
|
|
214
|
else:
|
|
|
215
|
receiver.connect("ipc:///tmp/zmq.plots")
|
|
215
|
receiver.connect("ipc:///tmp/zmq.plots")
|
|
|
216
|
|
|
216
|
|
|
|
217
|
seconds_passed = 0
|
|
217
|
seconds_passed = 0
|
|
|
218
|
|
|
218
|
|
|
|
219
|
while True:
|
|
219
|
while True:
|
|
|
220
|
try:
|
|
220
|
try:
|
|
|
221
|
self.data = receiver.recv_pyobj(flags=zmq.NOBLOCK)#flags=zmq.NOBLOCK
|
|
221
|
self.data = receiver.recv_pyobj(flags=zmq.NOBLOCK)#flags=zmq.NOBLOCK
|
|
|
222
|
self.started = self.data['STARTED']
|
|
222
|
self.started = self.data['STARTED']
|
|
|
223
|
self.dataOut = self.data['dataOut']
|
|
223
|
self.dataOut = self.data['dataOut']
|
|
|
224
|
|
|
224
|
|
|
|
225
|
if (len(self.times) < len(self.data['times']) and not self.started and self.data['ENDED']):
|
|
225
|
if (len(self.times) < len(self.data['times']) and not self.started and self.data['ENDED']):
|
|
|
226
|
continue
|
|
226
|
continue
|
|
|
227
|
|
|
227
|
|
|
|
228
|
self.times = self.data['times']
|
|
228
|
self.times = self.data['times']
|
|
|
229
|
self.times.sort()
|
|
229
|
self.times.sort()
|
|
|
230
|
self.throttle_value = self.data['throttle']
|
|
230
|
self.throttle_value = self.data['throttle']
|
|
|
231
|
self.min_time = self.times[0]
|
|
231
|
self.min_time = self.times[0]
|
|
|
232
|
self.max_time = self.times[-1]
|
|
232
|
self.max_time = self.times[-1]
|
|
|
233
|
|
|
233
|
|
|
|
234
|
if self.isConfig is False:
|
|
234
|
if self.isConfig is False:
|
|
|
235
|
print 'setting up'
|
|
235
|
print 'setting up'
|
|
|
236
|
self.setup()
|
|
236
|
self.setup()
|
|
|
237
|
self.isConfig = True
|
|
237
|
self.isConfig = True
|
|
|
238
|
self.__plot()
|
|
238
|
self.__plot()
|
|
|
239
|
|
|
239
|
|
|
|
240
|
if self.data['ENDED'] is True:
|
|
240
|
if self.data['ENDED'] is True:
|
|
|
241
|
print '********GRAPHIC ENDED********'
|
|
241
|
print '********GRAPHIC ENDED********'
|
|
|
242
|
self.ended = True
|
|
242
|
self.ended = True
|
|
|
243
|
self.isConfig = False
|
|
243
|
self.isConfig = False
|
|
|
244
|
self.__plot()
|
|
244
|
self.__plot()
|
|
|
245
|
#TODO : AUN NO FUNCIONA PARA COHERENCIA.
|
|
245
|
#TODO : AUN NO FUNCIONA PARA COHERENCIA.
|
|
|
246
|
self.deleteanotherfiles() #CLPDG
|
|
246
|
self.deleteanotherfiles() #CLPDG
|
|
|
247
|
elif seconds_passed >= self.data['throttle']:
|
|
247
|
elif seconds_passed >= self.data['throttle']:
|
|
|
248
|
print 'passed', seconds_passed
|
|
248
|
print 'passed', seconds_passed
|
|
|
249
|
self.__plot()
|
|
249
|
self.__plot()
|
|
|
250
|
seconds_passed = 0
|
|
250
|
seconds_passed = 0
|
|
|
251
|
|
|
251
|
|
|
|
252
|
except zmq.Again as e:
|
|
252
|
except zmq.Again as e:
|
|
|
253
|
print 'Waiting for data...'
|
|
253
|
print 'Waiting for data...'
|
|
|
254
|
plt.pause(2)
|
|
254
|
plt.pause(2)
|
|
|
255
|
seconds_passed += 2
|
|
255
|
seconds_passed += 2
|
|
|
256
|
|
|
256
|
|
|
|
257
|
def close(self):
|
|
257
|
def close(self):
|
|
|
258
|
if self.dataOut:
|
|
258
|
if self.dataOut:
|
|
|
259
|
self.__plot()
|
|
259
|
self.__plot()
|
|
|
260
|
|
|
260
|
|
|
|
261
|
|
|
261
|
|
|
|
262
|
class PlotSpectraData(PlotData):
|
|
262
|
class PlotSpectraData(PlotData):
|
|
|
263
|
|
|
263
|
|
|
|
264
|
CODE = 'spc'
|
|
264
|
CODE = 'spc'
|
|
|
265
|
colormap = 'jro'
|
|
265
|
colormap = 'jro'
|
|
|
266
|
CONFLATE = False
|
|
266
|
CONFLATE = False
|
|
|
267
|
|
|
267
|
|
|
|
268
|
def setup(self):
|
|
268
|
def setup(self):
|
|
|
269
|
|
|
269
|
|
|
|
270
|
ncolspan = 1
|
|
270
|
ncolspan = 1
|
|
|
271
|
colspan = 1
|
|
271
|
colspan = 1
|
|
|
272
|
self.ncols = int(numpy.sqrt(self.dataOut.nChannels)+0.9)
|
|
272
|
self.ncols = int(numpy.sqrt(self.dataOut.nChannels)+0.9)
|
|
|
273
|
self.nrows = int(self.dataOut.nChannels*1./self.ncols + 0.9)
|
|
273
|
self.nrows = int(self.dataOut.nChannels*1./self.ncols + 0.9)
|
|
|
274
|
self.width = 3.6*self.ncols
|
|
274
|
self.width = 3.6*self.ncols
|
|
|
275
|
self.height = 3.2*self.nrows
|
|
275
|
self.height = 3.2*self.nrows
|
|
|
276
|
if self.showprofile:
|
|
276
|
if self.showprofile:
|
|
|
277
|
ncolspan = 3
|
|
277
|
ncolspan = 3
|
|
|
278
|
colspan = 2
|
|
278
|
colspan = 2
|
|
|
279
|
self.width += 1.2*self.ncols
|
|
279
|
self.width += 1.2*self.ncols
|
|
|
280
|
|
|
280
|
|
|
|
281
|
self.ylabel = 'Range [Km]'
|
|
281
|
self.ylabel = 'Range [Km]'
|
|
|
282
|
self.titles = ['Channel {}'.format(x) for x in self.dataOut.channelList]
|
|
282
|
self.titles = ['Channel {}'.format(x) for x in self.dataOut.channelList]
|
|
|
283
|
|
|
283
|
|
|
|
284
|
if self.figure is None:
|
|
284
|
if self.figure is None:
|
|
|
285
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
285
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
|
286
|
edgecolor='k',
|
|
286
|
edgecolor='k',
|
|
|
287
|
facecolor='w')
|
|
287
|
facecolor='w')
|
|
|
288
|
else:
|
|
288
|
else:
|
|
|
289
|
self.figure.clf()
|
|
289
|
self.figure.clf()
|
|
|
290
|
|
|
290
|
|
|
|
291
|
n = 0
|
|
291
|
n = 0
|
|
|
292
|
for y in range(self.nrows):
|
|
292
|
for y in range(self.nrows):
|
|
|
293
|
for x in range(self.ncols):
|
|
293
|
for x in range(self.ncols):
|
|
|
294
|
if n >= self.dataOut.nChannels:
|
|
294
|
if n >= self.dataOut.nChannels:
|
|
|
295
|
break
|
|
295
|
break
|
|
|
296
|
ax = plt.subplot2grid((self.nrows, self.ncols*ncolspan), (y, x*ncolspan), 1, colspan)
|
|
296
|
ax = plt.subplot2grid((self.nrows, self.ncols*ncolspan), (y, x*ncolspan), 1, colspan)
|
|
|
297
|
if self.showprofile:
|
|
297
|
if self.showprofile:
|
|
|
298
|
ax.ax_profile = plt.subplot2grid((self.nrows, self.ncols*ncolspan), (y, x*ncolspan+colspan), 1, 1)
|
|
298
|
ax.ax_profile = plt.subplot2grid((self.nrows, self.ncols*ncolspan), (y, x*ncolspan+colspan), 1, 1)
|
|
|
299
|
|
|
299
|
|
|
|
300
|
ax.firsttime = True
|
|
300
|
ax.firsttime = True
|
|
|
301
|
self.axes.append(ax)
|
|
301
|
self.axes.append(ax)
|
|
|
302
|
n += 1
|
|
302
|
n += 1
|
|
|
303
|
|
|
303
|
|
|
|
304
|
def plot(self):
|
|
304
|
def plot(self):
|
|
|
305
|
|
|
305
|
|
|
|
306
|
if self.xaxis == "frequency":
|
|
306
|
if self.xaxis == "frequency":
|
|
|
307
|
x = self.dataOut.getFreqRange(1)/1000.
|
|
307
|
x = self.dataOut.getFreqRange(1)/1000.
|
|
|
308
|
xlabel = "Frequency (kHz)"
|
|
308
|
xlabel = "Frequency (kHz)"
|
|
|
309
|
elif self.xaxis == "time":
|
|
309
|
elif self.xaxis == "time":
|
|
|
310
|
x = self.dataOut.getAcfRange(1)
|
|
310
|
x = self.dataOut.getAcfRange(1)
|
|
|
311
|
xlabel = "Time (ms)"
|
|
311
|
xlabel = "Time (ms)"
|
|
|
312
|
else:
|
|
312
|
else:
|
|
|
313
|
x = self.dataOut.getVelRange(1)
|
|
313
|
x = self.dataOut.getVelRange(1)
|
|
|
314
|
xlabel = "Velocity (m/s)"
|
|
314
|
xlabel = "Velocity (m/s)"
|
|
|
315
|
|
|
315
|
|
|
|
316
|
y = self.dataOut.getHeiRange()
|
|
316
|
y = self.dataOut.getHeiRange()
|
|
|
317
|
z = self.data[self.CODE]
|
|
317
|
z = self.data[self.CODE]
|
|
|
318
|
|
|
318
|
|
|
|
319
|
for n, ax in enumerate(self.axes):
|
|
319
|
for n, ax in enumerate(self.axes):
|
|
|
320
|
if ax.firsttime:
|
|
320
|
if ax.firsttime:
|
|
|
321
|
self.xmax = self.xmax if self.xmax else np.nanmax(x)
|
|
321
|
self.xmax = self.xmax if self.xmax else np.nanmax(x)
|
|
|
322
|
self.xmin = self.xmin if self.xmin else -self.xmax
|
|
322
|
self.xmin = self.xmin if self.xmin else -self.xmax
|
|
|
323
|
self.ymin = self.ymin if self.ymin else np.nanmin(y)
|
|
323
|
self.ymin = self.ymin if self.ymin else np.nanmin(y)
|
|
|
324
|
self.ymax = self.ymax if self.ymax else np.nanmax(y)
|
|
324
|
self.ymax = self.ymax if self.ymax else np.nanmax(y)
|
|
|
325
|
self.zmin = self.zmin if self.zmin else np.nanmin(z)
|
|
325
|
self.zmin = self.zmin if self.zmin else np.nanmin(z)
|
|
|
326
|
self.zmax = self.zmax if self.zmax else np.nanmax(z)
|
|
326
|
self.zmax = self.zmax if self.zmax else np.nanmax(z)
|
|
|
327
|
ax.plot = ax.pcolormesh(x, y, z[n].T,
|
|
327
|
ax.plot = ax.pcolormesh(x, y, z[n].T,
|
|
|
328
|
vmin=self.zmin,
|
|
328
|
vmin=self.zmin,
|
|
|
329
|
vmax=self.zmax,
|
|
329
|
vmax=self.zmax,
|
|
|
330
|
cmap=plt.get_cmap(self.colormap)
|
|
330
|
cmap=plt.get_cmap(self.colormap)
|
|
|
331
|
)
|
|
331
|
)
|
|
|
332
|
divider = make_axes_locatable(ax)
|
|
332
|
divider = make_axes_locatable(ax)
|
|
|
333
|
cax = divider.new_horizontal(size='3%', pad=0.05)
|
|
333
|
cax = divider.new_horizontal(size='3%', pad=0.05)
|
|
|
334
|
self.figure.add_axes(cax)
|
|
334
|
self.figure.add_axes(cax)
|
|
|
335
|
plt.colorbar(ax.plot, cax)
|
|
335
|
plt.colorbar(ax.plot, cax)
|
|
|
336
|
|
|
336
|
|
|
|
337
|
ax.set_xlim(self.xmin, self.xmax)
|
|
337
|
ax.set_xlim(self.xmin, self.xmax)
|
|
|
338
|
ax.set_ylim(self.ymin, self.ymax)
|
|
338
|
ax.set_ylim(self.ymin, self.ymax)
|
|
|
339
|
|
|
339
|
|
|
|
340
|
ax.set_ylabel(self.ylabel)
|
|
340
|
ax.set_ylabel(self.ylabel)
|
|
|
341
|
ax.set_xlabel(xlabel)
|
|
341
|
ax.set_xlabel(xlabel)
|
|
|
342
|
|
|
342
|
|
|
|
343
|
ax.firsttime = False
|
|
343
|
ax.firsttime = False
|
|
|
344
|
|
|
344
|
|
|
|
345
|
if self.showprofile:
|
|
345
|
if self.showprofile:
|
|
|
346
|
ax.plot_profile= ax.ax_profile.plot(self.data['rti'][self.max_time][n], y)[0]
|
|
346
|
ax.plot_profile= ax.ax_profile.plot(self.data['rti'][self.max_time][n], y)[0]
|
|
|
347
|
ax.ax_profile.set_xlim(self.zmin, self.zmax)
|
|
347
|
ax.ax_profile.set_xlim(self.zmin, self.zmax)
|
|
|
348
|
ax.ax_profile.set_ylim(self.ymin, self.ymax)
|
|
348
|
ax.ax_profile.set_ylim(self.ymin, self.ymax)
|
|
|
349
|
ax.ax_profile.set_xlabel('dB')
|
|
349
|
ax.ax_profile.set_xlabel('dB')
|
|
|
350
|
ax.ax_profile.grid(b=True, axis='x')
|
|
350
|
ax.ax_profile.grid(b=True, axis='x')
|
|
|
351
|
ax.plot_noise = ax.ax_profile.plot(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y,
|
|
351
|
ax.plot_noise = ax.ax_profile.plot(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y,
|
|
|
352
|
color="k", linestyle="dashed", lw=2)[0]
|
|
352
|
color="k", linestyle="dashed", lw=2)[0]
|
|
|
353
|
[tick.set_visible(False) for tick in ax.ax_profile.get_yticklabels()]
|
|
353
|
[tick.set_visible(False) for tick in ax.ax_profile.get_yticklabels()]
|
|
|
354
|
else:
|
|
354
|
else:
|
|
|
355
|
ax.plot.set_array(z[n].T.ravel())
|
|
355
|
ax.plot.set_array(z[n].T.ravel())
|
|
|
356
|
if self.showprofile:
|
|
356
|
if self.showprofile:
|
|
|
357
|
ax.plot_profile.set_data(self.data['rti'][self.max_time][n], y)
|
|
357
|
ax.plot_profile.set_data(self.data['rti'][self.max_time][n], y)
|
|
|
358
|
ax.plot_noise.set_data(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y)
|
|
358
|
ax.plot_noise.set_data(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y)
|
|
|
359
|
|
|
359
|
|
|
|
360
|
ax.set_title('{} - Noise: {:.2f} dB'.format(self.titles[n], self.data['noise'][self.max_time][n]),
|
|
360
|
ax.set_title('{} - Noise: {:.2f} dB'.format(self.titles[n], self.data['noise'][self.max_time][n]),
|
|
|
361
|
size=8)
|
|
361
|
size=8)
|
|
|
362
|
self.saveTime = self.max_time
|
|
362
|
self.saveTime = self.max_time
|
|
|
363
|
|
|
363
|
|
|
|
364
|
|
|
364
|
|
|
|
365
|
class PlotCrossSpectraData(PlotData):
|
|
365
|
class PlotCrossSpectraData(PlotData):
|
|
|
366
|
|
|
366
|
|
|
|
367
|
CODE = 'cspc'
|
|
367
|
CODE = 'cspc'
|
|
|
368
|
zmin_coh = None
|
|
368
|
zmin_coh = None
|
|
|
369
|
zmax_coh = None
|
|
369
|
zmax_coh = None
|
|
|
370
|
zmin_phase = None
|
|
370
|
zmin_phase = None
|
|
|
371
|
zmax_phase = None
|
|
371
|
zmax_phase = None
|
|
|
372
|
CONFLATE = False
|
|
372
|
CONFLATE = False
|
|
|
373
|
|
|
373
|
|
|
|
374
|
def setup(self):
|
|
374
|
def setup(self):
|
|
|
375
|
|
|
375
|
|
|
|
376
|
ncolspan = 1
|
|
376
|
ncolspan = 1
|
|
|
377
|
colspan = 1
|
|
377
|
colspan = 1
|
|
|
378
|
self.ncols = 2
|
|
378
|
self.ncols = 2
|
|
|
379
|
self.nrows = self.dataOut.nPairs
|
|
379
|
self.nrows = self.dataOut.nPairs
|
|
|
380
|
self.width = 3.6*self.ncols
|
|
380
|
self.width = 3.6*self.ncols
|
|
|
381
|
self.height = 3.2*self.nrows
|
|
381
|
self.height = 3.2*self.nrows
|
|
|
382
|
|
|
382
|
|
|
|
383
|
self.ylabel = 'Range [Km]'
|
|
383
|
self.ylabel = 'Range [Km]'
|
|
|
384
|
self.titles = ['Channel {}'.format(x) for x in self.dataOut.channelList]
|
|
384
|
self.titles = ['Channel {}'.format(x) for x in self.dataOut.channelList]
|
|
|
385
|
|
|
385
|
|
|
|
386
|
if self.figure is None:
|
|
386
|
if self.figure is None:
|
|
|
387
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
387
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
|
388
|
edgecolor='k',
|
|
388
|
edgecolor='k',
|
|
|
389
|
facecolor='w')
|
|
389
|
facecolor='w')
|
|
|
390
|
else:
|
|
390
|
else:
|
|
|
391
|
self.figure.clf()
|
|
391
|
self.figure.clf()
|
|
|
392
|
|
|
392
|
|
|
|
393
|
for y in range(self.nrows):
|
|
393
|
for y in range(self.nrows):
|
|
|
394
|
for x in range(self.ncols):
|
|
394
|
for x in range(self.ncols):
|
|
|
395
|
ax = plt.subplot2grid((self.nrows, self.ncols), (y, x), 1, 1)
|
|
395
|
ax = plt.subplot2grid((self.nrows, self.ncols), (y, x), 1, 1)
|
|
|
396
|
ax.firsttime = True
|
|
396
|
ax.firsttime = True
|
|
|
397
|
self.axes.append(ax)
|
|
397
|
self.axes.append(ax)
|
|
|
398
|
|
|
398
|
|
|
|
399
|
def plot(self):
|
|
399
|
def plot(self):
|
|
|
400
|
|
|
400
|
|
|
|
401
|
if self.xaxis == "frequency":
|
|
401
|
if self.xaxis == "frequency":
|
|
|
402
|
x = self.dataOut.getFreqRange(1)/1000.
|
|
402
|
x = self.dataOut.getFreqRange(1)/1000.
|
|
|
403
|
xlabel = "Frequency (kHz)"
|
|
403
|
xlabel = "Frequency (kHz)"
|
|
|
404
|
elif self.xaxis == "time":
|
|
404
|
elif self.xaxis == "time":
|
|
|
405
|
x = self.dataOut.getAcfRange(1)
|
|
405
|
x = self.dataOut.getAcfRange(1)
|
|
|
406
|
xlabel = "Time (ms)"
|
|
406
|
xlabel = "Time (ms)"
|
|
|
407
|
else:
|
|
407
|
else:
|
|
|
408
|
x = self.dataOut.getVelRange(1)
|
|
408
|
x = self.dataOut.getVelRange(1)
|
|
|
409
|
xlabel = "Velocity (m/s)"
|
|
409
|
xlabel = "Velocity (m/s)"
|
|
|
410
|
|
|
410
|
|
|
|
411
|
y = self.dataOut.getHeiRange()
|
|
411
|
y = self.dataOut.getHeiRange()
|
|
|
412
|
z_coh = self.data['cspc_coh']
|
|
412
|
z_coh = self.data['cspc_coh']
|
|
|
413
|
z_phase = self.data['cspc_phase']
|
|
413
|
z_phase = self.data['cspc_phase']
|
|
|
414
|
|
|
414
|
|
|
|
415
|
for n in range(self.nrows):
|
|
415
|
for n in range(self.nrows):
|
|
|
416
|
ax = self.axes[2*n]
|
|
416
|
ax = self.axes[2*n]
|
|
|
417
|
ax1 = self.axes[2*n+1]
|
|
417
|
ax1 = self.axes[2*n+1]
|
|
|
418
|
if ax.firsttime:
|
|
418
|
if ax.firsttime:
|
|
|
419
|
self.xmax = self.xmax if self.xmax else np.nanmax(x)
|
|
419
|
self.xmax = self.xmax if self.xmax else np.nanmax(x)
|
|
|
420
|
self.xmin = self.xmin if self.xmin else -self.xmax
|
|
420
|
self.xmin = self.xmin if self.xmin else -self.xmax
|
|
|
421
|
self.ymin = self.ymin if self.ymin else np.nanmin(y)
|
|
421
|
self.ymin = self.ymin if self.ymin else np.nanmin(y)
|
|
|
422
|
self.ymax = self.ymax if self.ymax else np.nanmax(y)
|
|
422
|
self.ymax = self.ymax if self.ymax else np.nanmax(y)
|
|
|
423
|
self.zmin_coh = self.zmin_coh if self.zmin_coh else 0.0
|
|
423
|
self.zmin_coh = self.zmin_coh if self.zmin_coh else 0.0
|
|
|
424
|
self.zmax_coh = self.zmax_coh if self.zmax_coh else 1.0
|
|
424
|
self.zmax_coh = self.zmax_coh if self.zmax_coh else 1.0
|
|
|
425
|
self.zmin_phase = self.zmin_phase if self.zmin_phase else -180
|
|
425
|
self.zmin_phase = self.zmin_phase if self.zmin_phase else -180
|
|
|
426
|
self.zmax_phase = self.zmax_phase if self.zmax_phase else 180
|
|
426
|
self.zmax_phase = self.zmax_phase if self.zmax_phase else 180
|
|
|
427
|
|
|
427
|
|
|
|
428
|
ax.plot = ax.pcolormesh(x, y, z_coh[n].T,
|
|
428
|
ax.plot = ax.pcolormesh(x, y, z_coh[n].T,
|
|
|
429
|
vmin=self.zmin_coh,
|
|
429
|
vmin=self.zmin_coh,
|
|
|
430
|
vmax=self.zmax_coh,
|
|
430
|
vmax=self.zmax_coh,
|
|
|
431
|
cmap=plt.get_cmap(self.colormap_coh)
|
|
431
|
cmap=plt.get_cmap(self.colormap_coh)
|
|
|
432
|
)
|
|
432
|
)
|
|
|
433
|
divider = make_axes_locatable(ax)
|
|
433
|
divider = make_axes_locatable(ax)
|
|
|
434
|
cax = divider.new_horizontal(size='3%', pad=0.05)
|
|
434
|
cax = divider.new_horizontal(size='3%', pad=0.05)
|
|
|
435
|
self.figure.add_axes(cax)
|
|
435
|
self.figure.add_axes(cax)
|
|
|
436
|
plt.colorbar(ax.plot, cax)
|
|
436
|
plt.colorbar(ax.plot, cax)
|
|
|
437
|
|
|
437
|
|
|
|
438
|
ax.set_xlim(self.xmin, self.xmax)
|
|
438
|
ax.set_xlim(self.xmin, self.xmax)
|
|
|
439
|
ax.set_ylim(self.ymin, self.ymax)
|
|
439
|
ax.set_ylim(self.ymin, self.ymax)
|
|
|
440
|
|
|
440
|
|
|
|
441
|
ax.set_ylabel(self.ylabel)
|
|
441
|
ax.set_ylabel(self.ylabel)
|
|
|
442
|
ax.set_xlabel(xlabel)
|
|
442
|
ax.set_xlabel(xlabel)
|
|
|
443
|
ax.firsttime = False
|
|
443
|
ax.firsttime = False
|
|
|
444
|
|
|
444
|
|
|
|
445
|
ax1.plot = ax1.pcolormesh(x, y, z_phase[n].T,
|
|
445
|
ax1.plot = ax1.pcolormesh(x, y, z_phase[n].T,
|
|
|
446
|
vmin=self.zmin_phase,
|
|
446
|
vmin=self.zmin_phase,
|
|
|
447
|
vmax=self.zmax_phase,
|
|
447
|
vmax=self.zmax_phase,
|
|
|
448
|
cmap=plt.get_cmap(self.colormap_phase)
|
|
448
|
cmap=plt.get_cmap(self.colormap_phase)
|
|
|
449
|
)
|
|
449
|
)
|
|
|
450
|
divider = make_axes_locatable(ax1)
|
|
450
|
divider = make_axes_locatable(ax1)
|
|
|
451
|
cax = divider.new_horizontal(size='3%', pad=0.05)
|
|
451
|
cax = divider.new_horizontal(size='3%', pad=0.05)
|
|
|
452
|
self.figure.add_axes(cax)
|
|
452
|
self.figure.add_axes(cax)
|
|
|
453
|
plt.colorbar(ax1.plot, cax)
|
|
453
|
plt.colorbar(ax1.plot, cax)
|
|
|
454
|
|
|
454
|
|
|
|
455
|
ax1.set_xlim(self.xmin, self.xmax)
|
|
455
|
ax1.set_xlim(self.xmin, self.xmax)
|
|
|
456
|
ax1.set_ylim(self.ymin, self.ymax)
|
|
456
|
ax1.set_ylim(self.ymin, self.ymax)
|
|
|
457
|
|
|
457
|
|
|
|
458
|
ax1.set_ylabel(self.ylabel)
|
|
458
|
ax1.set_ylabel(self.ylabel)
|
|
|
459
|
ax1.set_xlabel(xlabel)
|
|
459
|
ax1.set_xlabel(xlabel)
|
|
|
460
|
ax1.firsttime = False
|
|
460
|
ax1.firsttime = False
|
|
|
461
|
else:
|
|
461
|
else:
|
|
|
462
|
ax.plot.set_array(z_coh[n].T.ravel())
|
|
462
|
ax.plot.set_array(z_coh[n].T.ravel())
|
|
|
463
|
ax1.plot.set_array(z_phase[n].T.ravel())
|
|
463
|
ax1.plot.set_array(z_phase[n].T.ravel())
|
|
|
464
|
|
|
464
|
|
|
|
465
|
ax.set_title('Coherence Ch{} * Ch{}'.format(self.dataOut.pairsList[n][0], self.dataOut.pairsList[n][1]), size=8)
|
|
465
|
ax.set_title('Coherence Ch{} * Ch{}'.format(self.dataOut.pairsList[n][0], self.dataOut.pairsList[n][1]), size=8)
|
|
|
466
|
ax1.set_title('Phase Ch{} * Ch{}'.format(self.dataOut.pairsList[n][0], self.dataOut.pairsList[n][1]), size=8)
|
|
466
|
ax1.set_title('Phase Ch{} * Ch{}'.format(self.dataOut.pairsList[n][0], self.dataOut.pairsList[n][1]), size=8)
|
|
|
467
|
self.saveTime = self.max_time
|
|
467
|
self.saveTime = self.max_time
|
|
|
468
|
|
|
468
|
|
|
|
469
|
|
|
469
|
|
|
|
470
|
class PlotSpectraMeanData(PlotSpectraData):
|
|
470
|
class PlotSpectraMeanData(PlotSpectraData):
|
|
|
471
|
|
|
471
|
|
|
|
472
|
CODE = 'spc_mean'
|
|
472
|
CODE = 'spc_mean'
|
|
|
473
|
colormap = 'jet'
|
|
473
|
colormap = 'jet'
|
|
|
474
|
|
|
474
|
|
|
|
475
|
def plot(self):
|
|
475
|
def plot(self):
|
|
|
476
|
|
|
476
|
|
|
|
477
|
if self.xaxis == "frequency":
|
|
477
|
if self.xaxis == "frequency":
|
|
|
478
|
x = self.dataOut.getFreqRange(1)/1000.
|
|
478
|
x = self.dataOut.getFreqRange(1)/1000.
|
|
|
479
|
xlabel = "Frequency (kHz)"
|
|
479
|
xlabel = "Frequency (kHz)"
|
|
|
480
|
elif self.xaxis == "time":
|
|
480
|
elif self.xaxis == "time":
|
|
|
481
|
x = self.dataOut.getAcfRange(1)
|
|
481
|
x = self.dataOut.getAcfRange(1)
|
|
|
482
|
xlabel = "Time (ms)"
|
|
482
|
xlabel = "Time (ms)"
|
|
|
483
|
else:
|
|
483
|
else:
|
|
|
484
|
x = self.dataOut.getVelRange(1)
|
|
484
|
x = self.dataOut.getVelRange(1)
|
|
|
485
|
xlabel = "Velocity (m/s)"
|
|
485
|
xlabel = "Velocity (m/s)"
|
|
|
486
|
|
|
486
|
|
|
|
487
|
y = self.dataOut.getHeiRange()
|
|
487
|
y = self.dataOut.getHeiRange()
|
|
|
488
|
z = self.data['spc']
|
|
488
|
z = self.data['spc']
|
|
|
489
|
mean = self.data['mean'][self.max_time]
|
|
489
|
mean = self.data['mean'][self.max_time]
|
|
|
490
|
|
|
490
|
|
|
|
491
|
for n, ax in enumerate(self.axes):
|
|
491
|
for n, ax in enumerate(self.axes):
|
|
|
492
|
|
|
492
|
|
|
|
493
|
if ax.firsttime:
|
|
493
|
if ax.firsttime:
|
|
|
494
|
self.xmax = self.xmax if self.xmax else np.nanmax(x)
|
|
494
|
self.xmax = self.xmax if self.xmax else np.nanmax(x)
|
|
|
495
|
self.xmin = self.xmin if self.xmin else -self.xmax
|
|
495
|
self.xmin = self.xmin if self.xmin else -self.xmax
|
|
|
496
|
self.ymin = self.ymin if self.ymin else np.nanmin(y)
|
|
496
|
self.ymin = self.ymin if self.ymin else np.nanmin(y)
|
|
|
497
|
self.ymax = self.ymax if self.ymax else np.nanmax(y)
|
|
497
|
self.ymax = self.ymax if self.ymax else np.nanmax(y)
|
|
|
498
|
self.zmin = self.zmin if self.zmin else np.nanmin(z)
|
|
498
|
self.zmin = self.zmin if self.zmin else np.nanmin(z)
|
|
|
499
|
self.zmax = self.zmax if self.zmax else np.nanmax(z)
|
|
499
|
self.zmax = self.zmax if self.zmax else np.nanmax(z)
|
|
|
500
|
ax.plt = ax.pcolormesh(x, y, z[n].T,
|
|
500
|
ax.plt = ax.pcolormesh(x, y, z[n].T,
|
|
|
501
|
vmin=self.zmin,
|
|
501
|
vmin=self.zmin,
|
|
|
502
|
vmax=self.zmax,
|
|
502
|
vmax=self.zmax,
|
|
|
503
|
cmap=plt.get_cmap(self.colormap)
|
|
503
|
cmap=plt.get_cmap(self.colormap)
|
|
|
504
|
)
|
|
504
|
)
|
|
|
505
|
ax.plt_dop = ax.plot(mean[n], y,
|
|
505
|
ax.plt_dop = ax.plot(mean[n], y,
|
|
|
506
|
color='k')[0]
|
|
506
|
color='k')[0]
|
|
|
507
|
|
|
507
|
|
|
|
508
|
divider = make_axes_locatable(ax)
|
|
508
|
divider = make_axes_locatable(ax)
|
|
|
509
|
cax = divider.new_horizontal(size='3%', pad=0.05)
|
|
509
|
cax = divider.new_horizontal(size='3%', pad=0.05)
|
|
|
510
|
self.figure.add_axes(cax)
|
|
510
|
self.figure.add_axes(cax)
|
|
|
511
|
plt.colorbar(ax.plt, cax)
|
|
511
|
plt.colorbar(ax.plt, cax)
|
|
|
512
|
|
|
512
|
|
|
|
513
|
ax.set_xlim(self.xmin, self.xmax)
|
|
513
|
ax.set_xlim(self.xmin, self.xmax)
|
|
|
514
|
ax.set_ylim(self.ymin, self.ymax)
|
|
514
|
ax.set_ylim(self.ymin, self.ymax)
|
|
|
515
|
|
|
515
|
|
|
|
516
|
ax.set_ylabel(self.ylabel)
|
|
516
|
ax.set_ylabel(self.ylabel)
|
|
|
517
|
ax.set_xlabel(xlabel)
|
|
517
|
ax.set_xlabel(xlabel)
|
|
|
518
|
|
|
518
|
|
|
|
519
|
ax.firsttime = False
|
|
519
|
ax.firsttime = False
|
|
|
520
|
|
|
520
|
|
|
|
521
|
if self.showprofile:
|
|
521
|
if self.showprofile:
|
|
|
522
|
ax.plt_profile= ax.ax_profile.plot(self.data['rti'][self.max_time][n], y)[0]
|
|
522
|
ax.plt_profile= ax.ax_profile.plot(self.data['rti'][self.max_time][n], y)[0]
|
|
|
523
|
ax.ax_profile.set_xlim(self.zmin, self.zmax)
|
|
523
|
ax.ax_profile.set_xlim(self.zmin, self.zmax)
|
|
|
524
|
ax.ax_profile.set_ylim(self.ymin, self.ymax)
|
|
524
|
ax.ax_profile.set_ylim(self.ymin, self.ymax)
|
|
|
525
|
ax.ax_profile.set_xlabel('dB')
|
|
525
|
ax.ax_profile.set_xlabel('dB')
|
|
|
526
|
ax.ax_profile.grid(b=True, axis='x')
|
|
526
|
ax.ax_profile.grid(b=True, axis='x')
|
|
|
527
|
ax.plt_noise = ax.ax_profile.plot(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y,
|
|
527
|
ax.plt_noise = ax.ax_profile.plot(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y,
|
|
|
528
|
color="k", linestyle="dashed", lw=2)[0]
|
|
528
|
color="k", linestyle="dashed", lw=2)[0]
|
|
|
529
|
[tick.set_visible(False) for tick in ax.ax_profile.get_yticklabels()]
|
|
529
|
[tick.set_visible(False) for tick in ax.ax_profile.get_yticklabels()]
|
|
|
530
|
else:
|
|
530
|
else:
|
|
|
531
|
ax.plt.set_array(z[n].T.ravel())
|
|
531
|
ax.plt.set_array(z[n].T.ravel())
|
|
|
532
|
ax.plt_dop.set_data(mean[n], y)
|
|
532
|
ax.plt_dop.set_data(mean[n], y)
|
|
|
533
|
if self.showprofile:
|
|
533
|
if self.showprofile:
|
|
|
534
|
ax.plt_profile.set_data(self.data['rti'][self.max_time][n], y)
|
|
534
|
ax.plt_profile.set_data(self.data['rti'][self.max_time][n], y)
|
|
|
535
|
ax.plt_noise.set_data(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y)
|
|
535
|
ax.plt_noise.set_data(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y)
|
|
|
536
|
|
|
536
|
|
|
|
537
|
ax.set_title('{} - Noise: {:.2f} dB'.format(self.titles[n], self.data['noise'][self.max_time][n]),
|
|
537
|
ax.set_title('{} - Noise: {:.2f} dB'.format(self.titles[n], self.data['noise'][self.max_time][n]),
|
|
|
538
|
size=8)
|
|
538
|
size=8)
|
|
|
539
|
self.saveTime = self.max_time
|
|
539
|
self.saveTime = self.max_time
|
|
|
540
|
|
|
540
|
|
|
|
541
|
|
|
541
|
|
|
|
542
|
class PlotRTIData(PlotData):
|
|
542
|
class PlotRTIData(PlotData):
|
|
|
543
|
|
|
543
|
|
|
|
544
|
CODE = 'rti'
|
|
544
|
CODE = 'rti'
|
|
|
545
|
colormap = 'jro'
|
|
545
|
colormap = 'jro'
|
|
|
546
|
|
|
546
|
|
|
|
547
|
def setup(self):
|
|
547
|
def setup(self):
|
|
|
548
|
self.ncols = 1
|
|
548
|
self.ncols = 1
|
|
|
549
|
self.nrows = self.dataOut.nChannels
|
|
549
|
self.nrows = self.dataOut.nChannels
|
|
|
550
|
self.width = 10
|
|
550
|
self.width = 10
|
|
|
551
|
#TODO : arreglar la altura de la figura, esta hardcodeada.
|
|
551
|
#TODO : arreglar la altura de la figura, esta hardcodeada.
|
|
|
552
|
#Se arreglo, testear!
|
|
552
|
#Se arreglo, testear!
|
|
|
553
|
if self.ind_plt_ch:
|
|
553
|
if self.ind_plt_ch:
|
|
|
554
|
self.height = 3.2#*self.nrows if self.nrows<6 else 12
|
|
554
|
self.height = 3.2#*self.nrows if self.nrows<6 else 12
|
|
|
555
|
else:
|
|
555
|
else:
|
|
|
556
|
self.height = 2.2*self.nrows if self.nrows<6 else 12
|
|
556
|
self.height = 2.2*self.nrows if self.nrows<6 else 12
|
|
|
557
|
|
|
557
|
|
|
|
558
|
'''
|
|
558
|
'''
|
|
|
559
|
if self.nrows==1:
|
|
559
|
if self.nrows==1:
|
|
|
560
|
self.height += 1
|
|
560
|
self.height += 1
|
|
|
561
|
'''
|
|
561
|
'''
|
|
|
562
|
self.ylabel = 'Range [Km]'
|
|
562
|
self.ylabel = 'Range [Km]'
|
|
|
563
|
self.titles = ['Channel {}'.format(x) for x in self.dataOut.channelList]
|
|
563
|
self.titles = ['Channel {}'.format(x) for x in self.dataOut.channelList]
|
|
|
564
|
|
|
564
|
|
|
|
565
|
'''
|
|
565
|
'''
|
|
|
566
|
Logica:
|
|
566
|
Logica:
|
|
|
567
|
1) Si la variable ind_plt_ch es True, va a crear mas de 1 figura
|
|
567
|
1) Si la variable ind_plt_ch es True, va a crear mas de 1 figura
|
|
|
568
|
2) guardamos "Figures" en una lista y "axes" en otra, quizas se deberia guardar el
|
|
568
|
2) guardamos "Figures" en una lista y "axes" en otra, quizas se deberia guardar el
|
|
|
569
|
axis dentro de "Figures" como un diccionario.
|
|
569
|
axis dentro de "Figures" como un diccionario.
|
|
|
570
|
'''
|
|
570
|
'''
|
|
|
571
|
if self.ind_plt_ch is False: #standard mode
|
|
571
|
if self.ind_plt_ch is False: #standard mode
|
|
|
572
|
|
|
572
|
|
|
|
573
|
if self.figure is None: #solo para la priemra vez
|
|
573
|
if self.figure is None: #solo para la priemra vez
|
|
|
574
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
574
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
|
575
|
edgecolor='k',
|
|
575
|
edgecolor='k',
|
|
|
576
|
facecolor='w')
|
|
576
|
facecolor='w')
|
|
|
577
|
else:
|
|
577
|
else:
|
|
|
578
|
self.figure.clf()
|
|
578
|
self.figure.clf()
|
|
|
579
|
self.axes = []
|
|
579
|
self.axes = []
|
|
|
580
|
|
|
580
|
|
|
|
581
|
|
|
581
|
|
|
|
582
|
for n in range(self.nrows):
|
|
582
|
for n in range(self.nrows):
|
|
|
583
|
ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
|
|
583
|
ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
|
|
|
584
|
#ax = self.figure(n+1)
|
|
584
|
#ax = self.figure(n+1)
|
|
|
585
|
ax.firsttime = True
|
|
585
|
ax.firsttime = True
|
|
|
586
|
self.axes.append(ax)
|
|
586
|
self.axes.append(ax)
|
|
|
587
|
|
|
587
|
|
|
|
588
|
else : #append one figure foreach channel in channelList
|
|
588
|
else : #append one figure foreach channel in channelList
|
|
|
589
|
if self.figurelist == None:
|
|
589
|
if self.figurelist == None:
|
|
|
590
|
self.figurelist = []
|
|
590
|
self.figurelist = []
|
|
|
591
|
for n in range(self.nrows):
|
|
591
|
for n in range(self.nrows):
|
|
|
592
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
592
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
|
593
|
edgecolor='k',
|
|
593
|
edgecolor='k',
|
|
|
594
|
facecolor='w')
|
|
594
|
facecolor='w')
|
|
|
595
|
#add always one subplot
|
|
595
|
#add always one subplot
|
|
|
596
|
self.figurelist.append(self.figure)
|
|
596
|
self.figurelist.append(self.figure)
|
|
|
597
|
|
|
597
|
|
|
|
598
|
else : # cada dia nuevo limpia el axes, pero mantiene el figure
|
|
598
|
else : # cada dia nuevo limpia el axes, pero mantiene el figure
|
|
|
599
|
for eachfigure in self.figurelist:
|
|
599
|
for eachfigure in self.figurelist:
|
|
|
600
|
eachfigure.clf() # eliminaria todas las figuras de la lista?
|
|
600
|
eachfigure.clf() # eliminaria todas las figuras de la lista?
|
|
|
601
|
self.axes = []
|
|
601
|
self.axes = []
|
|
|
602
|
|
|
602
|
|
|
|
603
|
for eachfigure in self.figurelist:
|
|
603
|
for eachfigure in self.figurelist:
|
|
|
604
|
ax = eachfigure.add_subplot(1,1,1) #solo 1 axis por figura
|
|
604
|
ax = eachfigure.add_subplot(1,1,1) #solo 1 axis por figura
|
|
|
605
|
#ax = self.figure(n+1)
|
|
605
|
#ax = self.figure(n+1)
|
|
|
606
|
ax.firsttime = True
|
|
606
|
ax.firsttime = True
|
|
|
607
|
#Cada figura tiene un distinto puntero
|
|
607
|
#Cada figura tiene un distinto puntero
|
|
|
608
|
self.axes.append(ax)
|
|
608
|
self.axes.append(ax)
|
|
|
609
|
#plt.close(eachfigure)
|
|
609
|
#plt.close(eachfigure)
|
|
|
610
|
|
|
610
|
|
|
|
611
|
|
|
611
|
|
|
|
612
|
def plot(self):
|
|
612
|
def plot(self):
|
|
|
613
|
|
|
613
|
|
|
|
614
|
if self.ind_plt_ch is False: #standard mode
|
|
614
|
if self.ind_plt_ch is False: #standard mode
|
|
|
615
|
self.x = np.array(self.times)
|
|
615
|
self.x = np.array(self.times)
|
|
|
616
|
self.y = self.dataOut.getHeiRange()
|
|
616
|
self.y = self.dataOut.getHeiRange()
|
|
|
617
|
self.z = []
|
|
617
|
self.z = []
|
|
|
618
|
|
|
618
|
|
|
|
619
|
for ch in range(self.nrows):
|
|
619
|
for ch in range(self.nrows):
|
|
|
620
|
self.z.append([self.data[self.CODE][t][ch] for t in self.times])
|
|
620
|
self.z.append([self.data[self.CODE][t][ch] for t in self.times])
|
|
|
621
|
|
|
621
|
|
|
|
622
|
self.z = np.array(self.z)
|
|
622
|
self.z = np.array(self.z)
|
|
|
623
|
for n, ax in enumerate(self.axes):
|
|
623
|
for n, ax in enumerate(self.axes):
|
|
|
624
|
x, y, z = self.fill_gaps(*self.decimate())
|
|
624
|
x, y, z = self.fill_gaps(*self.decimate())
|
|
|
625
|
xmin = self.min_time
|
|
625
|
xmin = self.min_time
|
|
|
626
|
xmax = xmin+self.xrange*60*60
|
|
626
|
xmax = xmin+self.xrange*60*60
|
|
|
627
|
self.zmin = self.zmin if self.zmin else np.min(self.z)
|
|
627
|
self.zmin = self.zmin if self.zmin else np.min(self.z)
|
|
|
628
|
self.zmax = self.zmax if self.zmax else np.max(self.z)
|
|
628
|
self.zmax = self.zmax if self.zmax else np.max(self.z)
|
|
|
629
|
if ax.firsttime:
|
|
629
|
if ax.firsttime:
|
|
|
630
|
self.ymin = self.ymin if self.ymin else np.nanmin(self.y)
|
|
630
|
self.ymin = self.ymin if self.ymin else np.nanmin(self.y)
|
|
|
631
|
self.ymax = self.ymax if self.ymax else np.nanmax(self.y)
|
|
631
|
self.ymax = self.ymax if self.ymax else np.nanmax(self.y)
|
|
|
632
|
plot = ax.pcolormesh(x, y, z[n].T,
|
|
632
|
plot = ax.pcolormesh(x, y, z[n].T,
|
|
|
633
|
vmin=self.zmin,
|
|
633
|
vmin=self.zmin,
|
|
|
634
|
vmax=self.zmax,
|
|
634
|
vmax=self.zmax,
|
|
|
635
|
cmap=plt.get_cmap(self.colormap)
|
|
635
|
cmap=plt.get_cmap(self.colormap)
|
|
|
636
|
)
|
|
636
|
)
|
|
|
637
|
divider = make_axes_locatable(ax)
|
|
637
|
divider = make_axes_locatable(ax)
|
|
|
638
|
cax = divider.new_horizontal(size='2%', pad=0.05)
|
|
638
|
cax = divider.new_horizontal(size='2%', pad=0.05)
|
|
|
639
|
self.figure.add_axes(cax)
|
|
639
|
self.figure.add_axes(cax)
|
|
|
640
|
plt.colorbar(plot, cax)
|
|
640
|
plt.colorbar(plot, cax)
|
|
|
641
|
ax.set_ylim(self.ymin, self.ymax)
|
|
641
|
ax.set_ylim(self.ymin, self.ymax)
|
|
|
642
|
ax.xaxis.set_major_formatter(FuncFormatter(func))
|
|
642
|
ax.xaxis.set_major_formatter(FuncFormatter(func))
|
|
|
643
|
ax.xaxis.set_major_locator(LinearLocator(6))
|
|
643
|
ax.xaxis.set_major_locator(LinearLocator(6))
|
|
|
644
|
ax.set_ylabel(self.ylabel)
|
|
644
|
ax.set_ylabel(self.ylabel)
|
|
|
645
|
if self.xmin is None:
|
|
645
|
if self.xmin is None:
|
|
|
646
|
xmin = self.min_time
|
|
646
|
xmin = self.min_time
|
|
|
647
|
else:
|
|
647
|
else:
|
|
|
648
|
xmin = (datetime.datetime.combine(self.dataOut.datatime.date(),
|
|
648
|
xmin = (datetime.datetime.combine(self.dataOut.datatime.date(),
|
|
|
649
|
datetime.time(self.xmin, 0, 0))-d1970).total_seconds()
|
|
649
|
datetime.time(self.xmin, 0, 0))-d1970).total_seconds()
|
|
|
650
|
ax.set_xlim(xmin, xmax)
|
|
650
|
ax.set_xlim(xmin, xmax)
|
|
|
651
|
ax.firsttime = False
|
|
651
|
ax.firsttime = False
|
|
|
652
|
else:
|
|
652
|
else:
|
|
|
653
|
ax.collections.remove(ax.collections[0])
|
|
653
|
ax.collections.remove(ax.collections[0])
|
|
|
654
|
ax.set_xlim(xmin, xmax)
|
|
654
|
ax.set_xlim(xmin, xmax)
|
|
|
655
|
plot = ax.pcolormesh(x, y, z[n].T,
|
|
655
|
plot = ax.pcolormesh(x, y, z[n].T,
|
|
|
656
|
vmin=self.zmin,
|
|
656
|
vmin=self.zmin,
|
|
|
657
|
vmax=self.zmax,
|
|
657
|
vmax=self.zmax,
|
|
|
658
|
cmap=plt.get_cmap(self.colormap)
|
|
658
|
cmap=plt.get_cmap(self.colormap)
|
|
|
659
|
)
|
|
659
|
)
|
|
|
660
|
ax.set_title('{} {}'.format(self.titles[n],
|
|
660
|
ax.set_title('{} {}'.format(self.titles[n],
|
|
|
661
|
datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')),
|
|
661
|
datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')),
|
|
|
662
|
size=8)
|
|
662
|
size=8)
|
|
|
663
|
|
|
663
|
|
|
|
664
|
self.saveTime = self.min_time
|
|
664
|
self.saveTime = self.min_time
|
|
|
665
|
else :
|
|
665
|
else :
|
|
|
666
|
self.x = np.array(self.times)
|
|
666
|
self.x = np.array(self.times)
|
|
|
667
|
self.y = self.dataOut.getHeiRange()
|
|
667
|
self.y = self.dataOut.getHeiRange()
|
|
|
668
|
self.z = []
|
|
668
|
self.z = []
|
|
|
669
|
|
|
669
|
|
|
|
670
|
for ch in range(self.nrows):
|
|
670
|
for ch in range(self.nrows):
|
|
|
671
|
self.z.append([self.data[self.CODE][t][ch] for t in self.times])
|
|
671
|
self.z.append([self.data[self.CODE][t][ch] for t in self.times])
|
|
|
672
|
|
|
672
|
|
|
|
673
|
self.z = np.array(self.z)
|
|
673
|
self.z = np.array(self.z)
|
|
|
674
|
for n, eachfigure in enumerate(self.figurelist): #estaba ax in axes
|
|
674
|
for n, eachfigure in enumerate(self.figurelist): #estaba ax in axes
|
|
|
675
|
|
|
675
|
|
|
|
676
|
x, y, z = self.fill_gaps(*self.decimate())
|
|
676
|
x, y, z = self.fill_gaps(*self.decimate())
|
|
|
677
|
xmin = self.min_time
|
|
677
|
xmin = self.min_time
|
|
|
678
|
xmax = xmin+self.xrange*60*60
|
|
678
|
xmax = xmin+self.xrange*60*60
|
|
|
679
|
self.zmin = self.zmin if self.zmin else np.min(self.z)
|
|
679
|
self.zmin = self.zmin if self.zmin else np.min(self.z)
|
|
|
680
|
self.zmax = self.zmax if self.zmax else np.max(self.z)
|
|
680
|
self.zmax = self.zmax if self.zmax else np.max(self.z)
|
|
|
681
|
if self.axes[n].firsttime:
|
|
681
|
if self.axes[n].firsttime:
|
|
|
682
|
self.ymin = self.ymin if self.ymin else np.nanmin(self.y)
|
|
682
|
self.ymin = self.ymin if self.ymin else np.nanmin(self.y)
|
|
|
683
|
self.ymax = self.ymax if self.ymax else np.nanmax(self.y)
|
|
683
|
self.ymax = self.ymax if self.ymax else np.nanmax(self.y)
|
|
|
684
|
plot = self.axes[n].pcolormesh(x, y, z[n].T,
|
|
684
|
plot = self.axes[n].pcolormesh(x, y, z[n].T,
|
|
|
685
|
vmin=self.zmin,
|
|
685
|
vmin=self.zmin,
|
|
|
686
|
vmax=self.zmax,
|
|
686
|
vmax=self.zmax,
|
|
|
687
|
cmap=plt.get_cmap(self.colormap)
|
|
687
|
cmap=plt.get_cmap(self.colormap)
|
|
|
688
|
)
|
|
688
|
)
|
|
|
689
|
divider = make_axes_locatable(self.axes[n])
|
|
689
|
divider = make_axes_locatable(self.axes[n])
|
|
|
690
|
cax = divider.new_horizontal(size='2%', pad=0.05)
|
|
690
|
cax = divider.new_horizontal(size='2%', pad=0.05)
|
|
|
691
|
eachfigure.add_axes(cax)
|
|
691
|
eachfigure.add_axes(cax)
|
|
|
692
|
#self.figure2.add_axes(cax)
|
|
692
|
#self.figure2.add_axes(cax)
|
|
|
693
|
plt.colorbar(plot, cax)
|
|
693
|
plt.colorbar(plot, cax)
|
|
|
694
|
self.axes[n].set_ylim(self.ymin, self.ymax)
|
|
694
|
self.axes[n].set_ylim(self.ymin, self.ymax)
|
|
|
695
|
|
|
695
|
|
|
|
696
|
self.axes[n].xaxis.set_major_formatter(FuncFormatter(func))
|
|
696
|
self.axes[n].xaxis.set_major_formatter(FuncFormatter(func))
|
|
|
697
|
self.axes[n].xaxis.set_major_locator(LinearLocator(6))
|
|
697
|
self.axes[n].xaxis.set_major_locator(LinearLocator(6))
|
|
|
698
|
|
|
698
|
|
|
|
699
|
self.axes[n].set_ylabel(self.ylabel)
|
|
699
|
self.axes[n].set_ylabel(self.ylabel)
|
|
|
700
|
|
|
700
|
|
|
|
701
|
if self.xmin is None:
|
|
701
|
if self.xmin is None:
|
|
|
702
|
xmin = self.min_time
|
|
702
|
xmin = self.min_time
|
|
|
703
|
else:
|
|
703
|
else:
|
|
|
704
|
xmin = (datetime.datetime.combine(self.dataOut.datatime.date(),
|
|
704
|
xmin = (datetime.datetime.combine(self.dataOut.datatime.date(),
|
|
|
705
|
datetime.time(self.xmin, 0, 0))-d1970).total_seconds()
|
|
705
|
datetime.time(self.xmin, 0, 0))-d1970).total_seconds()
|
|
|
706
|
|
|
706
|
|
|
|
707
|
self.axes[n].set_xlim(xmin, xmax)
|
|
707
|
self.axes[n].set_xlim(xmin, xmax)
|
|
|
708
|
self.axes[n].firsttime = False
|
|
708
|
self.axes[n].firsttime = False
|
|
|
709
|
else:
|
|
709
|
else:
|
|
|
710
|
self.axes[n].collections.remove(self.axes[n].collections[0])
|
|
710
|
self.axes[n].collections.remove(self.axes[n].collections[0])
|
|
|
711
|
self.axes[n].set_xlim(xmin, xmax)
|
|
711
|
self.axes[n].set_xlim(xmin, xmax)
|
|
|
712
|
plot = self.axes[n].pcolormesh(x, y, z[n].T,
|
|
712
|
plot = self.axes[n].pcolormesh(x, y, z[n].T,
|
|
|
713
|
vmin=self.zmin,
|
|
713
|
vmin=self.zmin,
|
|
|
714
|
vmax=self.zmax,
|
|
714
|
vmax=self.zmax,
|
|
|
715
|
cmap=plt.get_cmap(self.colormap)
|
|
715
|
cmap=plt.get_cmap(self.colormap)
|
|
|
716
|
)
|
|
716
|
)
|
|
|
717
|
self.axes[n].set_title('{} {}'.format(self.titles[n],
|
|
717
|
self.axes[n].set_title('{} {}'.format(self.titles[n],
|
|
|
718
|
datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')),
|
|
718
|
datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')),
|
|
|
719
|
size=8)
|
|
719
|
size=8)
|
|
|
720
|
|
|
720
|
|
|
|
721
|
self.saveTime = self.min_time
|
|
721
|
self.saveTime = self.min_time
|
|
|
722
|
|
|
722
|
|
|
|
723
|
|
|
723
|
|
|
|
724
|
class PlotCOHData(PlotRTIData):
|
|
724
|
class PlotCOHData(PlotRTIData):
|
|
|
725
|
|
|
725
|
|
|
|
726
|
CODE = 'coh'
|
|
726
|
CODE = 'coh'
|
|
|
727
|
|
|
727
|
|
|
|
728
|
def setup(self):
|
|
728
|
def setup(self):
|
|
|
729
|
|
|
729
|
|
|
|
730
|
self.ncols = 1
|
|
730
|
self.ncols = 1
|
|
|
731
|
self.nrows = self.dataOut.nPairs
|
|
731
|
self.nrows = self.dataOut.nPairs
|
|
|
732
|
self.width = 10
|
|
732
|
self.width = 10
|
|
|
733
|
self.height = 2.2*self.nrows if self.nrows<6 else 12
|
|
733
|
self.height = 2.2*self.nrows if self.nrows<6 else 12
|
|
|
|
|
|
734
|
self.ind_plt_ch = False #just for coherence and phase
|
|
|
734
|
if self.nrows==1:
|
|
735
|
if self.nrows==1:
|
|
|
735
|
self.height += 1
|
|
736
|
self.height += 1
|
|
|
736
|
self.ylabel = 'Range [Km]'
|
|
737
|
self.ylabel = 'Range [Km]'
|
|
|
737
|
self.titles = ['{} Ch{} * Ch{}'.format(self.CODE.upper(), x[0], x[1]) for x in self.dataOut.pairsList]
|
|
738
|
self.titles = ['{} Ch{} * Ch{}'.format(self.CODE.upper(), x[0], x[1]) for x in self.dataOut.pairsList]
|
|
|
738
|
|
|
739
|
|
|
|
739
|
if self.figure is None:
|
|
740
|
if self.figure is None:
|
|
|
740
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
741
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
|
741
|
edgecolor='k',
|
|
742
|
edgecolor='k',
|
|
|
742
|
facecolor='w')
|
|
743
|
facecolor='w')
|
|
|
743
|
else:
|
|
744
|
else:
|
|
|
744
|
self.figure.clf()
|
|
745
|
self.figure.clf()
|
|
|
745
|
self.axes = []
|
|
746
|
self.axes = []
|
|
|
746
|
|
|
747
|
|
|
|
747
|
for n in range(self.nrows):
|
|
748
|
for n in range(self.nrows):
|
|
|
748
|
ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
|
|
749
|
ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
|
|
|
749
|
ax.firsttime = True
|
|
750
|
ax.firsttime = True
|
|
|
750
|
self.axes.append(ax)
|
|
751
|
self.axes.append(ax)
|
|
|
751
|
|
|
752
|
|
|
|
752
|
|
|
753
|
|
|
|
753
|
class PlotNoiseData(PlotData):
|
|
754
|
class PlotNoiseData(PlotData):
|
|
|
754
|
CODE = 'noise'
|
|
755
|
CODE = 'noise'
|
|
|
755
|
|
|
756
|
|
|
|
756
|
def setup(self):
|
|
757
|
def setup(self):
|
|
|
757
|
|
|
758
|
|
|
|
758
|
self.ncols = 1
|
|
759
|
self.ncols = 1
|
|
|
759
|
self.nrows = 1
|
|
760
|
self.nrows = 1
|
|
|
760
|
self.width = 10
|
|
761
|
self.width = 10
|
|
|
761
|
self.height = 3.2
|
|
762
|
self.height = 3.2
|
|
|
762
|
self.ylabel = 'Intensity [dB]'
|
|
763
|
self.ylabel = 'Intensity [dB]'
|
|
|
763
|
self.titles = ['Noise']
|
|
764
|
self.titles = ['Noise']
|
|
|
764
|
|
|
765
|
|
|
|
765
|
if self.figure is None:
|
|
766
|
if self.figure is None:
|
|
|
766
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
767
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
|
767
|
edgecolor='k',
|
|
768
|
edgecolor='k',
|
|
|
768
|
facecolor='w')
|
|
769
|
facecolor='w')
|
|
|
769
|
else:
|
|
770
|
else:
|
|
|
770
|
self.figure.clf()
|
|
771
|
self.figure.clf()
|
|
|
771
|
self.axes = []
|
|
772
|
self.axes = []
|
|
|
772
|
|
|
773
|
|
|
|
773
|
self.ax = self.figure.add_subplot(self.nrows, self.ncols, 1)
|
|
774
|
self.ax = self.figure.add_subplot(self.nrows, self.ncols, 1)
|
|
|
774
|
self.ax.firsttime = True
|
|
775
|
self.ax.firsttime = True
|
|
|
775
|
|
|
776
|
|
|
|
776
|
def plot(self):
|
|
777
|
def plot(self):
|
|
|
777
|
|
|
778
|
|
|
|
778
|
x = self.times
|
|
779
|
x = self.times
|
|
|
779
|
xmin = self.min_time
|
|
780
|
xmin = self.min_time
|
|
|
780
|
xmax = xmin+self.xrange*60*60
|
|
781
|
xmax = xmin+self.xrange*60*60
|
|
|
781
|
if self.ax.firsttime:
|
|
782
|
if self.ax.firsttime:
|
|
|
782
|
for ch in self.dataOut.channelList:
|
|
783
|
for ch in self.dataOut.channelList:
|
|
|
783
|
y = [self.data[self.CODE][t][ch] for t in self.times]
|
|
784
|
y = [self.data[self.CODE][t][ch] for t in self.times]
|
|
|
784
|
self.ax.plot(x, y, lw=1, label='Ch{}'.format(ch))
|
|
785
|
self.ax.plot(x, y, lw=1, label='Ch{}'.format(ch))
|
|
|
785
|
self.ax.firsttime = False
|
|
786
|
self.ax.firsttime = False
|
|
|
786
|
self.ax.xaxis.set_major_formatter(FuncFormatter(func))
|
|
787
|
self.ax.xaxis.set_major_formatter(FuncFormatter(func))
|
|
|
787
|
self.ax.xaxis.set_major_locator(LinearLocator(6))
|
|
788
|
self.ax.xaxis.set_major_locator(LinearLocator(6))
|
|
|
788
|
self.ax.set_ylabel(self.ylabel)
|
|
789
|
self.ax.set_ylabel(self.ylabel)
|
|
|
789
|
plt.legend()
|
|
790
|
plt.legend()
|
|
|
790
|
else:
|
|
791
|
else:
|
|
|
791
|
for ch in self.dataOut.channelList:
|
|
792
|
for ch in self.dataOut.channelList:
|
|
|
792
|
y = [self.data[self.CODE][t][ch] for t in self.times]
|
|
793
|
y = [self.data[self.CODE][t][ch] for t in self.times]
|
|
|
793
|
self.ax.lines[ch].set_data(x, y)
|
|
794
|
self.ax.lines[ch].set_data(x, y)
|
|
|
794
|
|
|
795
|
|
|
|
795
|
self.ax.set_xlim(xmin, xmax)
|
|
796
|
self.ax.set_xlim(xmin, xmax)
|
|
|
796
|
self.ax.set_ylim(min(y)-5, max(y)+5)
|
|
797
|
self.ax.set_ylim(min(y)-5, max(y)+5)
|
|
|
797
|
self.saveTime = self.min_time
|
|
798
|
self.saveTime = self.min_time
|
|
|
798
|
|
|
799
|
|
|
|
799
|
|
|
800
|
|
|
|
800
|
class PlotWindProfilerData(PlotRTIData):
|
|
801
|
class PlotWindProfilerData(PlotRTIData):
|
|
|
801
|
|
|
802
|
|
|
|
802
|
CODE = 'wind'
|
|
803
|
CODE = 'wind'
|
|
|
803
|
colormap = 'seismic'
|
|
804
|
colormap = 'seismic'
|
|
|
804
|
|
|
805
|
|
|
|
805
|
def setup(self):
|
|
806
|
def setup(self):
|
|
|
806
|
self.ncols = 1
|
|
807
|
self.ncols = 1
|
|
|
807
|
self.nrows = self.dataOut.data_output.shape[0]
|
|
808
|
self.nrows = self.dataOut.data_output.shape[0]
|
|
|
808
|
self.width = 10
|
|
809
|
self.width = 10
|
|
|
809
|
self.height = 2.2*self.nrows
|
|
810
|
self.height = 2.2*self.nrows
|
|
|
810
|
self.ylabel = 'Height [Km]'
|
|
811
|
self.ylabel = 'Height [Km]'
|
|
|
811
|
self.titles = ['Zonal Wind' ,'Meridional Wind', 'Vertical Wind']
|
|
812
|
self.titles = ['Zonal Wind' ,'Meridional Wind', 'Vertical Wind']
|
|
|
812
|
self.clabels = ['Velocity (m/s)','Velocity (m/s)','Velocity (cm/s)']
|
|
813
|
self.clabels = ['Velocity (m/s)','Velocity (m/s)','Velocity (cm/s)']
|
|
|
813
|
self.windFactor = [1, 1, 100]
|
|
814
|
self.windFactor = [1, 1, 100]
|
|
|
814
|
|
|
815
|
|
|
|
815
|
if self.figure is None:
|
|
816
|
if self.figure is None:
|
|
|
816
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
817
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
|
817
|
edgecolor='k',
|
|
818
|
edgecolor='k',
|
|
|
818
|
facecolor='w')
|
|
819
|
facecolor='w')
|
|
|
819
|
else:
|
|
820
|
else:
|
|
|
820
|
self.figure.clf()
|
|
821
|
self.figure.clf()
|
|
|
821
|
self.axes = []
|
|
822
|
self.axes = []
|
|
|
822
|
|
|
823
|
|
|
|
823
|
for n in range(self.nrows):
|
|
824
|
for n in range(self.nrows):
|
|
|
824
|
ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
|
|
825
|
ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
|
|
|
825
|
ax.firsttime = True
|
|
826
|
ax.firsttime = True
|
|
|
826
|
self.axes.append(ax)
|
|
827
|
self.axes.append(ax)
|
|
|
827
|
|
|
828
|
|
|
|
828
|
def plot(self):
|
|
829
|
def plot(self):
|
|
|
829
|
|
|
830
|
|
|
|
830
|
self.x = np.array(self.times)
|
|
831
|
self.x = np.array(self.times)
|
|
|
831
|
self.y = self.dataOut.heightList
|
|
832
|
self.y = self.dataOut.heightList
|
|
|
832
|
self.z = []
|
|
833
|
self.z = []
|
|
|
833
|
|
|
834
|
|
|
|
834
|
for ch in range(self.nrows):
|
|
835
|
for ch in range(self.nrows):
|
|
|
835
|
self.z.append([self.data['output'][t][ch] for t in self.times])
|
|
836
|
self.z.append([self.data['output'][t][ch] for t in self.times])
|
|
|
836
|
|
|
837
|
|
|
|
837
|
self.z = np.array(self.z)
|
|
838
|
self.z = np.array(self.z)
|
|
|
838
|
self.z = numpy.ma.masked_invalid(self.z)
|
|
839
|
self.z = numpy.ma.masked_invalid(self.z)
|
|
|
839
|
|
|
840
|
|
|
|
840
|
cmap=plt.get_cmap(self.colormap)
|
|
841
|
cmap=plt.get_cmap(self.colormap)
|
|
|
841
|
cmap.set_bad('black', 1.)
|
|
842
|
cmap.set_bad('black', 1.)
|
|
|
842
|
|
|
843
|
|
|
|
843
|
for n, ax in enumerate(self.axes):
|
|
844
|
for n, ax in enumerate(self.axes):
|
|
|
844
|
x, y, z = self.fill_gaps(*self.decimate())
|
|
845
|
x, y, z = self.fill_gaps(*self.decimate())
|
|
|
845
|
xmin = self.min_time
|
|
846
|
xmin = self.min_time
|
|
|
846
|
xmax = xmin+self.xrange*60*60
|
|
847
|
xmax = xmin+self.xrange*60*60
|
|
|
847
|
if ax.firsttime:
|
|
848
|
if ax.firsttime:
|
|
|
848
|
self.ymin = self.ymin if self.ymin else np.nanmin(self.y)
|
|
849
|
self.ymin = self.ymin if self.ymin else np.nanmin(self.y)
|
|
|
849
|
self.ymax = self.ymax if self.ymax else np.nanmax(self.y)
|
|
850
|
self.ymax = self.ymax if self.ymax else np.nanmax(self.y)
|
|
|
850
|
self.zmax = self.zmax if self.zmax else numpy.nanmax(abs(self.z[:-1, :]))
|
|
851
|
self.zmax = self.zmax if self.zmax else numpy.nanmax(abs(self.z[:-1, :]))
|
|
|
851
|
self.zmin = self.zmin if self.zmin else -self.zmax
|
|
852
|
self.zmin = self.zmin if self.zmin else -self.zmax
|
|
|
852
|
|
|
853
|
|
|
|
853
|
plot = ax.pcolormesh(x, y, z[n].T*self.windFactor[n],
|
|
854
|
plot = ax.pcolormesh(x, y, z[n].T*self.windFactor[n],
|
|
|
854
|
vmin=self.zmin,
|
|
855
|
vmin=self.zmin,
|
|
|
855
|
vmax=self.zmax,
|
|
856
|
vmax=self.zmax,
|
|
|
856
|
cmap=cmap
|
|
857
|
cmap=cmap
|
|
|
857
|
)
|
|
858
|
)
|
|
|
858
|
divider = make_axes_locatable(ax)
|
|
859
|
divider = make_axes_locatable(ax)
|
|
|
859
|
cax = divider.new_horizontal(size='2%', pad=0.05)
|
|
860
|
cax = divider.new_horizontal(size='2%', pad=0.05)
|
|
|
860
|
self.figure.add_axes(cax)
|
|
861
|
self.figure.add_axes(cax)
|
|
|
861
|
cb = plt.colorbar(plot, cax)
|
|
862
|
cb = plt.colorbar(plot, cax)
|
|
|
862
|
cb.set_label(self.clabels[n])
|
|
863
|
cb.set_label(self.clabels[n])
|
|
|
863
|
ax.set_ylim(self.ymin, self.ymax)
|
|
864
|
ax.set_ylim(self.ymin, self.ymax)
|
|
|
864
|
|
|
865
|
|
|
|
865
|
ax.xaxis.set_major_formatter(FuncFormatter(func))
|
|
866
|
ax.xaxis.set_major_formatter(FuncFormatter(func))
|
|
|
866
|
ax.xaxis.set_major_locator(LinearLocator(6))
|
|
867
|
ax.xaxis.set_major_locator(LinearLocator(6))
|
|
|
867
|
|
|
868
|
|
|
|
868
|
ax.set_ylabel(self.ylabel)
|
|
869
|
ax.set_ylabel(self.ylabel)
|
|
|
869
|
|
|
870
|
|
|
|
870
|
ax.set_xlim(xmin, xmax)
|
|
871
|
ax.set_xlim(xmin, xmax)
|
|
|
871
|
ax.firsttime = False
|
|
872
|
ax.firsttime = False
|
|
|
872
|
else:
|
|
873
|
else:
|
|
|
873
|
ax.collections.remove(ax.collections[0])
|
|
874
|
ax.collections.remove(ax.collections[0])
|
|
|
874
|
ax.set_xlim(xmin, xmax)
|
|
875
|
ax.set_xlim(xmin, xmax)
|
|
|
875
|
plot = ax.pcolormesh(x, y, z[n].T*self.windFactor[n],
|
|
876
|
plot = ax.pcolormesh(x, y, z[n].T*self.windFactor[n],
|
|
|
876
|
vmin=self.zmin,
|
|
877
|
vmin=self.zmin,
|
|
|
877
|
vmax=self.zmax,
|
|
878
|
vmax=self.zmax,
|
|
|
878
|
cmap=plt.get_cmap(self.colormap)
|
|
879
|
cmap=plt.get_cmap(self.colormap)
|
|
|
879
|
)
|
|
880
|
)
|
|
|
880
|
ax.set_title('{} {}'.format(self.titles[n],
|
|
881
|
ax.set_title('{} {}'.format(self.titles[n],
|
|
|
881
|
datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')),
|
|
882
|
datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')),
|
|
|
882
|
size=8)
|
|
883
|
size=8)
|
|
|
883
|
|
|
884
|
|
|
|
884
|
self.saveTime = self.min_time
|
|
885
|
self.saveTime = self.min_time
|
|
|
885
|
|
|
886
|
|
|
|
886
|
|
|
887
|
|
|
|
887
|
class PlotSNRData(PlotRTIData):
|
|
888
|
class PlotSNRData(PlotRTIData):
|
|
|
888
|
CODE = 'snr'
|
|
889
|
CODE = 'snr'
|
|
|
889
|
colormap = 'jet'
|
|
890
|
colormap = 'jet'
|
|
|
890
|
|
|
891
|
|
|
|
891
|
class PlotDOPData(PlotRTIData):
|
|
892
|
class PlotDOPData(PlotRTIData):
|
|
|
892
|
CODE = 'dop'
|
|
893
|
CODE = 'dop'
|
|
|
893
|
colormap = 'jet'
|
|
894
|
colormap = 'jet'
|
|
|
894
|
|
|
895
|
|
|
|
895
|
|
|
896
|
|
|
|
896
|
class PlotPHASEData(PlotCOHData):
|
|
897
|
class PlotPHASEData(PlotCOHData):
|
|
|
897
|
CODE = 'phase'
|
|
898
|
CODE = 'phase'
|
|
|
898
|
colormap = 'seismic'
|
|
899
|
colormap = 'seismic'
|
|
|
899
|
|
|
900
|
|
|
|
900
|
|
|
901
|
|
|
|
901
|
class PlotSkyMapData(PlotData):
|
|
902
|
class PlotSkyMapData(PlotData):
|
|
|
902
|
|
|
903
|
|
|
|
903
|
CODE = 'met'
|
|
904
|
CODE = 'met'
|
|
|
904
|
|
|
905
|
|
|
|
905
|
def setup(self):
|
|
906
|
def setup(self):
|
|
|
906
|
|
|
907
|
|
|
|
907
|
self.ncols = 1
|
|
908
|
self.ncols = 1
|
|
|
908
|
self.nrows = 1
|
|
909
|
self.nrows = 1
|
|
|
909
|
self.width = 7.2
|
|
910
|
self.width = 7.2
|
|
|
910
|
self.height = 7.2
|
|
911
|
self.height = 7.2
|
|
|
911
|
|
|
912
|
|
|
|
912
|
self.xlabel = 'Zonal Zenith Angle (deg)'
|
|
913
|
self.xlabel = 'Zonal Zenith Angle (deg)'
|
|
|
913
|
self.ylabel = 'Meridional Zenith Angle (deg)'
|
|
914
|
self.ylabel = 'Meridional Zenith Angle (deg)'
|
|
|
914
|
|
|
915
|
|
|
|
915
|
if self.figure is None:
|
|
916
|
if self.figure is None:
|
|
|
916
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
917
|
self.figure = plt.figure(figsize=(self.width, self.height),
|
|
|
917
|
edgecolor='k',
|
|
918
|
edgecolor='k',
|
|
|
918
|
facecolor='w')
|
|
919
|
facecolor='w')
|
|
|
919
|
else:
|
|
920
|
else:
|
|
|
920
|
self.figure.clf()
|
|
921
|
self.figure.clf()
|
|
|
921
|
|
|
922
|
|
|
|
922
|
self.ax = plt.subplot2grid((self.nrows, self.ncols), (0, 0), 1, 1, polar=True)
|
|
923
|
self.ax = plt.subplot2grid((self.nrows, self.ncols), (0, 0), 1, 1, polar=True)
|
|
|
923
|
self.ax.firsttime = True
|
|
924
|
self.ax.firsttime = True
|
|
|
924
|
|
|
925
|
|
|
|
925
|
|
|
926
|
|
|
|
926
|
def plot(self):
|
|
927
|
def plot(self):
|
|
|
927
|
|
|
928
|
|
|
|
928
|
arrayParameters = np.concatenate([self.data['param'][t] for t in self.times])
|
|
929
|
arrayParameters = np.concatenate([self.data['param'][t] for t in self.times])
|
|
|
929
|
error = arrayParameters[:,-1]
|
|
930
|
error = arrayParameters[:,-1]
|
|
|
930
|
indValid = numpy.where(error == 0)[0]
|
|
931
|
indValid = numpy.where(error == 0)[0]
|
|
|
931
|
finalMeteor = arrayParameters[indValid,:]
|
|
932
|
finalMeteor = arrayParameters[indValid,:]
|
|
|
932
|
finalAzimuth = finalMeteor[:,3]
|
|
933
|
finalAzimuth = finalMeteor[:,3]
|
|
|
933
|
finalZenith = finalMeteor[:,4]
|
|
934
|
finalZenith = finalMeteor[:,4]
|
|
|
934
|
|
|
935
|
|
|
|
935
|
x = finalAzimuth*numpy.pi/180
|
|
936
|
x = finalAzimuth*numpy.pi/180
|
|
|
936
|
y = finalZenith
|
|
937
|
y = finalZenith
|
|
|
937
|
|
|
938
|
|
|
|
938
|
if self.ax.firsttime:
|
|
939
|
if self.ax.firsttime:
|
|
|
939
|
self.ax.plot = self.ax.plot(x, y, 'bo', markersize=5)[0]
|
|
940
|
self.ax.plot = self.ax.plot(x, y, 'bo', markersize=5)[0]
|
|
|
940
|
self.ax.set_ylim(0,90)
|
|
941
|
self.ax.set_ylim(0,90)
|
|
|
941
|
self.ax.set_yticks(numpy.arange(0,90,20))
|
|
942
|
self.ax.set_yticks(numpy.arange(0,90,20))
|
|
|
942
|
self.ax.set_xlabel(self.xlabel)
|
|
943
|
self.ax.set_xlabel(self.xlabel)
|
|
|
943
|
self.ax.set_ylabel(self.ylabel)
|
|
944
|
self.ax.set_ylabel(self.ylabel)
|
|
|
944
|
self.ax.yaxis.labelpad = 40
|
|
945
|
self.ax.yaxis.labelpad = 40
|
|
|
945
|
self.ax.firsttime = False
|
|
946
|
self.ax.firsttime = False
|
|
|
946
|
else:
|
|
947
|
else:
|
|
|
947
|
self.ax.plot.set_data(x, y)
|
|
948
|
self.ax.plot.set_data(x, y)
|
|
|
948
|
|
|
949
|
|
|
|
949
|
|
|
950
|
|
|
|
950
|
dt1 = datetime.datetime.fromtimestamp(self.min_time).strftime('%y/%m/%d %H:%M:%S')
|
|
951
|
dt1 = datetime.datetime.fromtimestamp(self.min_time).strftime('%y/%m/%d %H:%M:%S')
|
|
|
951
|
dt2 = datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')
|
|
952
|
dt2 = datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')
|
|
|
952
|
title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1,
|
|
953
|
title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1,
|
|
|
953
|
dt2,
|
|
954
|
dt2,
|
|
|
954
|
len(x))
|
|
955
|
len(x))
|
|
|
955
|
self.ax.set_title(title, size=8)
|
|
956
|
self.ax.set_title(title, size=8)
|
|
|
956
|
|
|
957
|
|
|
|
957
|
self.saveTime = self.max_time
|
|
958
|
self.saveTime = self.max_time
|
