jroplot_parameters.py
436 lines
| 13.3 KiB
| text/x-python
|
PythonLexer
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r502 | import os | |
import datetime | |||
import numpy | |||
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r1001 | ||
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r1285 | from schainpy.model.graphics.jroplot_base import Plot, plt | |
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r1358 | from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot | |
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r1285 | from schainpy.utils import log | |
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r1001 | ||
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r1285 | EARTH_RADIUS = 6.3710e3 | |
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r1001 | ||
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r1285 | def ll2xy(lat1, lon1, lat2, lon2): | |
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r1001 | ||
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r1285 | p = 0.017453292519943295 | |
a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \ | |||
numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2 | |||
r = 12742 * numpy.arcsin(numpy.sqrt(a)) | |||
theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p) | |||
* numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p)) | |||
theta = -theta + numpy.pi/2 | |||
return r*numpy.cos(theta), r*numpy.sin(theta) | |||
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r897 | ||
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r1285 | def km2deg(km): | |
''' | |||
Convert distance in km to degrees | |||
''' | |||
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r897 | ||
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r1285 | return numpy.rad2deg(km/EARTH_RADIUS) | |
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r897 | ||
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r1285 | class SpectralMomentsPlot(SpectraPlot): | |
''' | |||
Plot for Spectral Moments | |||
''' | |||
CODE = 'spc_moments' | |||
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r1358 | # colormap = 'jet' | |
# plot_type = 'pcolor' | |||
class DobleGaussianPlot(SpectraPlot): | |||
''' | |||
Plot for Double Gaussian Plot | |||
''' | |||
CODE = 'gaussian_fit' | |||
# colormap = 'jet' | |||
# plot_type = 'pcolor' | |||
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r897 | ||
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r1358 | class DoubleGaussianSpectraCutPlot(SpectraCutPlot): | |
''' | |||
Plot SpectraCut with Double Gaussian Fit | |||
''' | |||
CODE = 'cut_gaussian_fit' | |||
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r897 | ||
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r1669 | ||
class SpectralFitObliquePlot(SpectraPlot): | |||
''' | |||
Plot for Spectral Oblique | |||
''' | |||
CODE = 'spc_moments' | |||
colormap = 'jet' | |||
plot_type = 'pcolor' | |||
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r1285 | class SnrPlot(RTIPlot): | |
''' | |||
Plot for SNR Data | |||
''' | |||
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r897 | ||
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r1285 | CODE = 'snr' | |
colormap = 'jet' | |||
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r897 | ||
r1343 | def update(self, dataOut): | ||
r1738 | if len(self.channelList) == 0: | ||
self.update_list(dataOut) | |||
r1343 | |||
r1738 | meta = {} | ||
r1343 | data = { | ||
r1738 | 'snr': 10 * numpy.log10(dataOut.data_snr) | ||
r1343 | } | ||
r1738 | return data, meta | ||
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r897 | ||
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r1285 | class DopplerPlot(RTIPlot): | |
''' | |||
Plot for DOPPLER Data (1st moment) | |||
''' | |||
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r897 | ||
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r1285 | CODE = 'dop' | |
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r1669 | colormap = 'RdBu_r' | |
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r897 | ||
r1343 | def update(self, dataOut): | ||
r1738 | self.update_list(dataOut) | ||
r1343 | data = { | ||
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r1669 | 'dop': dataOut.data_dop | |
r1343 | } | ||
return data, {} | |||
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r897 | ||
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r1285 | class PowerPlot(RTIPlot): | |
''' | |||
Plot for Power Data (0 moment) | |||
''' | |||
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r897 | ||
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r1285 | CODE = 'pow' | |
colormap = 'jet' | |||
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r897 | ||
r1343 | def update(self, dataOut): | ||
r1738 | self.update_list(dataOut) | ||
r1343 | data = { | ||
r1751 | 'pow': 10*numpy.log10(dataOut.data_pow) | ||
r1343 | } | ||
r1738 | try: | ||
data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | |||
except: | |||
pass | |||
r1343 | return data, {} | ||
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r897 | ||
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r1285 | class SpectralWidthPlot(RTIPlot): | |
''' | |||
Plot for Spectral Width Data (2nd moment) | |||
''' | |||
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r897 | ||
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r1285 | CODE = 'width' | |
colormap = 'jet' | |||
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r897 | ||
r1343 | def update(self, dataOut): | ||
r1738 | self.update_list(dataOut) | ||
r1343 | data = { | ||
'width': dataOut.data_width | |||
} | |||
r1738 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | ||
r1343 | return data, {} | ||
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r897 | ||
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r1285 | class SkyMapPlot(Plot): | |
''' | |||
Plot for meteors detection data | |||
''' | |||
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r897 | ||
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r1285 | CODE = 'param' | |
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r897 | ||
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r1285 | def setup(self): | |
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r502 | ||
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r1285 | self.ncols = 1 | |
self.nrows = 1 | |||
self.width = 7.2 | |||
self.height = 7.2 | |||
self.nplots = 1 | |||
self.xlabel = 'Zonal Zenith Angle (deg)' | |||
self.ylabel = 'Meridional Zenith Angle (deg)' | |||
self.polar = True | |||
self.ymin = -180 | |||
self.ymax = 180 | |||
self.colorbar = False | |||
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r897 | ||
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r1285 | def plot(self): | |
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r897 | ||
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r1285 | arrayParameters = numpy.concatenate(self.data['param']) | |
error = arrayParameters[:, -1] | |||
indValid = numpy.where(error == 0)[0] | |||
finalMeteor = arrayParameters[indValid, :] | |||
finalAzimuth = finalMeteor[:, 3] | |||
finalZenith = finalMeteor[:, 4] | |||
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r897 | ||
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r1285 | x = finalAzimuth * numpy.pi / 180 | |
y = finalZenith | |||
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r897 | ||
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r1285 | ax = self.axes[0] | |
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r897 | ||
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r1285 | if ax.firsttime: | |
ax.plot = ax.plot(x, y, 'bo', markersize=5)[0] | |||
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r832 | else: | |
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r1285 | ax.plot.set_data(x, y) | |
dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S') | |||
dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S') | |||
title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1, | |||
dt2, | |||
len(x)) | |||
self.titles[0] = title | |||
r1343 | class GenericRTIPlot(Plot): | ||
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r1285 | ''' | |
r1343 | Plot for data_xxxx object | ||
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r1285 | ''' | |
CODE = 'param' | |||
r1343 | colormap = 'viridis' | ||
plot_type = 'pcolorbuffer' | |||
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r1285 | ||
def setup(self): | |||
self.xaxis = 'time' | |||
self.ncols = 1 | |||
r1359 | self.nrows = self.data.shape('param')[0] | ||
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r1285 | self.nplots = self.nrows | |
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r1322 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95}) | |
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r1669 | ||
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r1322 | if not self.xlabel: | |
self.xlabel = 'Time' | |||
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r1285 | ||
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r1358 | self.ylabel = 'Range [km]' | |
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r1285 | if not self.titles: | |
r1360 | self.titles = ['Param {}'.format(x) for x in range(self.nrows)] | ||
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r1285 | ||
r1343 | def update(self, dataOut): | ||
data = { | |||
r1359 | 'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0) | ||
r1343 | } | ||
r1740 | |||
r1343 | meta = {} | ||
return data, meta | |||
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r1285 | def plot(self): | |
r1343 | # self.data.normalize_heights() | ||
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r1285 | self.x = self.data.times | |
r1343 | self.y = self.data.yrange | ||
r1359 | self.z = self.data['param'] | ||
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r897 | ||
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r1285 | self.z = numpy.ma.masked_invalid(self.z) | |
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r897 | ||
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r1285 | if self.decimation is None: | |
x, y, z = self.fill_gaps(self.x, self.y, self.z) | |||
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r511 | else: | |
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r1285 | x, y, z = self.fill_gaps(*self.decimate()) | |
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r897 | ||
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r1285 | for n, ax in enumerate(self.axes): | |
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r588 | ||
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r1285 | self.zmax = self.zmax if self.zmax is not None else numpy.max( | |
self.z[n]) | |||
self.zmin = self.zmin if self.zmin is not None else numpy.min( | |||
self.z[n]) | |||
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r897 | ||
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r1285 | if ax.firsttime: | |
if self.zlimits is not None: | |||
self.zmin, self.zmax = self.zlimits[n] | |||
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r897 | ||
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r1285 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], | |
vmin=self.zmin, | |||
vmax=self.zmax, | |||
cmap=self.cmaps[n] | |||
) | |||
else: | |||
if self.zlimits is not None: | |||
self.zmin, self.zmax = self.zlimits[n] | |||
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r1669 | try: | |
ax.collections.remove(ax.collections[0]) | |||
except: | |||
pass | |||
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r1285 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], | |
vmin=self.zmin, | |||
vmax=self.zmax, | |||
cmap=self.cmaps[n] | |||
) | |||
class PolarMapPlot(Plot): | |||
''' | |||
Plot for weather radar | |||
''' | |||
CODE = 'param' | |||
colormap = 'seismic' | |||
def setup(self): | |||
self.ncols = 1 | |||
self.nrows = 1 | |||
self.width = 9 | |||
self.height = 8 | |||
self.mode = self.data.meta['mode'] | |||
if self.channels is not None: | |||
self.nplots = len(self.channels) | |||
self.nrows = len(self.channels) | |||
r1065 | else: | ||
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r1285 | self.nplots = self.data.shape(self.CODE)[0] | |
self.nrows = self.nplots | |||
self.channels = list(range(self.nplots)) | |||
if self.mode == 'E': | |||
self.xlabel = 'Longitude' | |||
self.ylabel = 'Latitude' | |||
else: | |||
self.xlabel = 'Range (km)' | |||
self.ylabel = 'Height (km)' | |||
self.bgcolor = 'white' | |||
self.cb_labels = self.data.meta['units'] | |||
self.lat = self.data.meta['latitude'] | |||
self.lon = self.data.meta['longitude'] | |||
self.xmin, self.xmax = float( | |||
km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon) | |||
self.ymin, self.ymax = float( | |||
km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat) | |||
# self.polar = True | |||
def plot(self): | |||
for n, ax in enumerate(self.axes): | |||
data = self.data['param'][self.channels[n]] | |||
zeniths = numpy.linspace( | |||
0, self.data.meta['max_range'], data.shape[1]) | |||
if self.mode == 'E': | |||
r1343 | azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2 | ||
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r1285 | r, theta = numpy.meshgrid(zeniths, azimuths) | |
x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin( | |||
theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])) | |||
x = km2deg(x) + self.lon | |||
y = km2deg(y) + self.lat | |||
r1065 | else: | ||
r1343 | azimuths = numpy.radians(self.data.yrange) | ||
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r1285 | r, theta = numpy.meshgrid(zeniths, azimuths) | |
x, y = r*numpy.cos(theta), r*numpy.sin(theta) | |||
self.y = zeniths | |||
if ax.firsttime: | |||
if self.zlimits is not None: | |||
self.zmin, self.zmax = self.zlimits[n] | |||
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r1669 | ax.plt = ax.pcolormesh(# r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), | |
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r1285 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), | |
vmin=self.zmin, | |||
vmax=self.zmax, | |||
cmap=self.cmaps[n]) | |||
|
r513 | else: | |
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r1285 | if self.zlimits is not None: | |
self.zmin, self.zmax = self.zlimits[n] | |||
ax.collections.remove(ax.collections[0]) | |||
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r1669 | ax.plt = ax.pcolormesh(# r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), | |
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r1285 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), | |
vmin=self.zmin, | |||
vmax=self.zmax, | |||
cmap=self.cmaps[n]) | |||
if self.mode == 'A': | |||
continue | |||
# plot district names | |||
f = open('/data/workspace/schain_scripts/distrito.csv') | |||
for line in f: | |||
label, lon, lat = [s.strip() for s in line.split(',') if s] | |||
lat = float(lat) | |||
lon = float(lon) | |||
# ax.plot(lon, lat, '.b', ms=2) | |||
ax.text(lon, lat, label.decode('utf8'), ha='center', | |||
va='bottom', size='8', color='black') | |||
# plot limites | |||
limites = [] | |||
tmp = [] | |||
for line in open('/data/workspace/schain_scripts/lima.csv'): | |||
if '#' in line: | |||
if tmp: | |||
limites.append(tmp) | |||
tmp = [] | |||
continue | |||
values = line.strip().split(',') | |||
tmp.append((float(values[0]), float(values[1]))) | |||
for points in limites: | |||
ax.add_patch( | |||
Polygon(points, ec='k', fc='none', ls='--', lw=0.5)) | |||
# plot Cuencas | |||
for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'): | |||
f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca)) | |||
values = [line.strip().split(',') for line in f] | |||
points = [(float(s[0]), float(s[1])) for s in values] | |||
ax.add_patch(Polygon(points, ec='b', fc='none')) | |||
# plot grid | |||
for r in (15, 30, 45, 60): | |||
ax.add_artist(plt.Circle((self.lon, self.lat), | |||
km2deg(r), color='0.6', fill=False, lw=0.2)) | |||
ax.text( | |||
self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180), | |||
self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180), | |||
'{}km'.format(r), | |||
ha='center', va='bottom', size='8', color='0.6', weight='heavy') | |||
if self.mode == 'E': | |||
r1739 | title = 'El={}\N{DEGREE SIGN}'.format(self.data.meta['elevation']) | ||
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r1285 | label = 'E{:02d}'.format(int(self.data.meta['elevation'])) | |
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r608 | else: | |
r1739 | title = 'Az={}\N{DEGREE SIGN}'.format(self.data.meta['azimuth']) | ||
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r1285 | label = 'A{:02d}'.format(int(self.data.meta['azimuth'])) | |
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r897 | ||
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r1285 | self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels] | |
self.titles = ['{} {}'.format( | |||
self.data.parameters[x], title) for x in self.channels] | |||
r1738 | |||
class TxPowerPlot(Plot): | |||
''' | |||
Plot for TX Power from external file | |||
''' | |||
CODE = 'tx_power' | |||
plot_type = 'scatterbuffer' | |||
def setup(self): | |||
self.xaxis = 'time' | |||
self.ncols = 1 | |||
self.nrows = 1 | |||
self.nplots = 1 | |||
self.ylabel = 'Power [kW]' | |||
self.xlabel = 'Time' | |||
self.titles = ['TX power'] | |||
self.colorbar = False | |||
self.plots_adjust.update({'right': 0.85 }) | |||
#if not self.titles: | |||
self.titles = ['TX Power Plot'] | |||
def update(self, dataOut): | |||
data = {} | |||
meta = {} | |||
data['tx_power'] = dataOut.txPower/1000 | |||
meta['yrange'] = numpy.array([]) | |||
#print(dataOut.txPower/1000) | |||
return data, meta | |||
def plot(self): | |||
x = self.data.times | |||
xmin = self.data.min_time | |||
xmax = xmin + self.xrange * 60 * 60 | |||
Y = self.data['tx_power'] | |||
if self.axes[0].firsttime: | |||
if self.ymin is None: self.ymin = 0 | |||
if self.ymax is None: self.ymax = numpy.nanmax(Y) + 5 | |||
if self.ymax == 5: | |||
self.ymax = 250 | |||
self.ymin = 100 | |||
self.axes[0].plot(x, Y, lw=1, label='Power') | |||
plt.legend(bbox_to_anchor=(1.18, 1.0)) | |||
else: | |||
self.axes[0].lines[0].set_data(x, Y) |