def peek(self, title="RHESSI Observing Summary Count Rate", **kwargs):
"""Plots RHESSI Count Rate light curve. An example is shown below.
.. plot::
from sunpy import lightcurve as lc
from sunpy.data.sample import RHESSI_LIGHTCURVE
rhessi = lc.RHESSISummaryLightCurve.create(RHESSI_LIGHTCURVE)
rhessi.peek()
Parameters
----------
title : str
The title of the plot.
**kwargs : dict
Any additional plot arguments that should be used
when plotting.
Returns
-------
fig : `~matplotlib.Figure`
A plot figure.
"""
figure = plt.figure()
axes = plt.gca()
#dates = matplotlib.dates.date2num(self.data.index)
lc_linecolors = rhessi.hsi_linecolors()
for lc_color, (item, frame) in zip(lc_linecolors,
self.data.iteritems()):
axes.plot_date(self.data.index,
frame.values,
'-',
label=item,
lw=2,
color=lc_color)
axes.set_yscale("log")
axes.set_xlabel(datetime.datetime.isoformat(self.data.index[0])[0:10])
axes.set_title('RHESSI Observing Summary Count Rates')
axes.set_ylabel('Count Rate s$^{-1}$ detector$^{-1}$')
axes.yaxis.grid(True, 'major')
axes.xaxis.grid(False, 'major')
axes.legend()
# @todo: display better tick labels for date range (e.g. 06/01 - 06/05)
formatter = matplotlib.dates.DateFormatter('%H:%M')
axes.xaxis.set_major_formatter(formatter)
axes.fmt_xdata = matplotlib.dates.DateFormatter('%H:%M')
figure.autofmt_xdate()
figure.show()
def peek(self, title="RHESSI Observing Summary Count Rate", **kwargs):
"""
Plots RHESSI Count Rate light curve. An example is shown below:
.. plot::
import sunpy.data.sample
import sunpy.timeseries
rhessi = sunpy.timeseries.TimeSeries(sunpy.data.sample.RHESSI_TIMESERIES, source='RHESSI')
rhessi.peek()
Parameters
----------
title : `str`
The title of the plot.
**kwargs : `dict`
Additional plot keyword arguments that are handed to `axes.plot` functions
"""
# Check we have a timeseries valid for plotting
self._validate_data_for_plotting()
figure = plt.figure()
axes = plt.gca()
lc_linecolors = rhessi.hsi_linecolors()
for lc_color, (item, frame) in zip(lc_linecolors,
self.to_dataframe().items()):
axes.plot_date(self.to_dataframe().index,
frame.values,
'-',
label=item,
lw=2,
color=lc_color,
**kwargs)
axes.set_yscale("log")
axes.set_xlabel(
datetime.datetime.isoformat(self.to_dataframe().index[0])[0:10])
axes.set_title(title)
axes.set_ylabel('Count Rate s$^{-1}$ detector$^{-1}$')
axes.yaxis.grid(True, 'major')
axes.xaxis.grid(False, 'major')
axes.legend()
# TODO: display better tick labels for date range (e.g. 06/01 - 06/05)
formatter = matplotlib.dates.DateFormatter('%H:%M')
axes.xaxis.set_major_formatter(formatter)
axes.fmt_xdata = matplotlib.dates.DateFormatter('%H:%M')
figure.autofmt_xdate()
return figure
def peek(self, title="RHESSI Observing Summary Count Rate", **kwargs):
"""Plots RHESSI Count Rate light curve. An example is shown below.
.. plot::
import sunpy.data.sample
import sunpy.timeseries
rhessi = sunpy.timeseries.TimeSeries(sunpy.data.sample.RHESSI_LIGHTCURVE, source='RHESSI')
rhessi.peek()
Parameters
----------
title : `str`
The title of the plot.
**kwargs : `dict`
Any additional plot arguments that should be used
when plotting.
Returns
-------
fig : `~matplotlib.Figure`
A plot figure.
"""
# Check we have a timeseries valid for plotting
self._validate_data_for_ploting()
figure = plt.figure()
axes = plt.gca()
#dates = matplotlib.dates.date2num(self.data.index)
lc_linecolors = rhessi.hsi_linecolors()
for lc_color, (item, frame) in zip(lc_linecolors, self.data.iteritems()):
axes.plot_date(self.data.index, frame.values, '-', label=item, lw=2, color=lc_color)
axes.set_yscale("log")
axes.set_xlabel(datetime.datetime.isoformat(self.data.index[0])[0:10])
axes.set_title('RHESSI Observing Summary Count Rates')
axes.set_ylabel('Count Rate s$^{-1}$ detector$^{-1}$')
axes.yaxis.grid(True, 'major')
axes.xaxis.grid(False, 'major')
axes.legend()
# @todo: display better tick labels for date range (e.g. 06/01 - 06/05)
formatter = matplotlib.dates.DateFormatter('%H:%M')
axes.xaxis.set_major_formatter(formatter)
axes.fmt_xdata = matplotlib.dates.DateFormatter('%H:%M')
figure.autofmt_xdate()
figure.show()
def peek(self, title="RHESSI Observing Summary Count Rate", **kwargs):
"""Plots RHESSI Count Rate light curve. An example is shown below.
.. plot::
from sunpy import lightcurve as lc
rhessi = lc.RHESSISummaryLightCurve.create('2012/06/01 01:30', '2012/06/01 03:35')
rhessi.peek()
Parameters
----------
title : str
The title of the plot.
**kwargs : dict
Any additional plot arguments that should be used
when plotting.
Returns
-------
fig : `~matplotlib.Figure`
A plot figure.
"""
figure = plt.figure()
axes = plt.gca()
#dates = matplotlib.dates.date2num(self.data.index)
lc_linecolors = rhessi.hsi_linecolors()
for lc_color, (item, frame) in zip(lc_linecolors, self.data.iteritems()):
axes.plot_date(self.data.index, frame.values, '-', label=item, lw=2, color=lc_color)
axes.set_yscale("log")
axes.set_xlabel(datetime.datetime.isoformat(self.data.index[0])[0:10])
axes.set_title('RHESSI Observing Summary Count Rates')
axes.set_ylabel('Count Rate s$^{-1}$ detector$^{-1}$')
axes.yaxis.grid(True, 'major')
axes.xaxis.grid(False, 'major')
axes.legend()
# @todo: display better tick labels for date range (e.g. 06/01 - 06/05)
formatter = matplotlib.dates.DateFormatter('%H:%M')
axes.xaxis.set_major_formatter(formatter)
axes.fmt_xdata = matplotlib.dates.DateFormatter('%H:%M')
figure.autofmt_xdate()
figure.show()
def peek(self):
"""Plots RHESSI Count Rate light curve. An example is shown below.
.. plot::
from sunpy import lightcurve as lc
from sunpy.data.sample import RHESSI_TIMESERIES
rhessi = lc.RHESSISummaryLightCurve.create(RHESSI_TIMESERIES)
rhessi.peek()
Returns
-------
fig : `~matplotlib.Figure`
A plot figure.
"""
figure = plt.figure()
axes = plt.gca()
lc_linecolors = rhessi.hsi_linecolors()
for lc_color, (item, frame) in zip(lc_linecolors,
self.data.iteritems()):
axes.plot_date(self.data.index,
frame.values,
'-',
label=item,
lw=2,
color=lc_color)
axes.set_yscale("log")
axes.set_xlabel(datetime.datetime.isoformat(self.data.index[0])[0:10])
axes.set_title('RHESSI Observing Summary Count Rates')
axes.set_ylabel('Count Rate s$^{-1}$ detector$^{-1}$')
axes.yaxis.grid(True, 'major')
axes.xaxis.grid(False, 'major')
axes.legend()
# @todo: display better tick labels for date range (e.g. 06/01 - 06/05)
formatter = matplotlib.dates.DateFormatter('%H:%M')
axes.xaxis.set_major_formatter(formatter)
axes.fmt_xdata = matplotlib.dates.DateFormatter('%H:%M')
figure.autofmt_xdate()
figure.show()
def peek(self, title="RHESSI Observing Summary Count Rate"):
"""
Plots RHESSI Count Rate light curve. An example is shown below:
.. plot::
import sunpy.data.sample
import sunpy.timeseries
rhessi = sunpy.timeseries.TimeSeries(sunpy.data.sample.RHESSI_TIMESERIES, source='RHESSI')
rhessi.peek()
Parameters
----------
title : `str`
The title of the plot.
"""
# Check we have a timeseries valid for plotting
self._validate_data_for_ploting()
figure = plt.figure()
axes = plt.gca()
lc_linecolors = rhessi.hsi_linecolors()
for lc_color, (item, frame) in zip(lc_linecolors, self.data.items()):
axes.plot_date(self.data.index, frame.values, '-', label=item, lw=2, color=lc_color)
axes.set_yscale("log")
axes.set_xlabel(datetime.datetime.isoformat(self.data.index[0])[0:10])
axes.set_title(title)
axes.set_ylabel('Count Rate s$^{-1}$ detector$^{-1}$')
axes.yaxis.grid(True, 'major')
axes.xaxis.grid(False, 'major')
axes.legend()
# TODO: display better tick labels for date range (e.g. 06/01 - 06/05)
formatter = matplotlib.dates.DateFormatter('%H:%M')
axes.xaxis.set_major_formatter(formatter)
axes.fmt_xdata = matplotlib.dates.DateFormatter('%H:%M')
figure.autofmt_xdate()
return figure
def peek(self):
"""Plots RHESSI Count Rate light curve. An example is shown below.
.. plot::
from sunpy import lightcurve as lc
from sunpy.data.sample import RHESSI_TIMESERIES
rhessi = lc.RHESSISummaryLightCurve.create(RHESSI_TIMESERIES)
rhessi.peek()
Returns
-------
fig : `~matplotlib.Figure`
A plot figure.
"""
figure = plt.figure()
axes = plt.gca()
lc_linecolors = rhessi.hsi_linecolors()
for lc_color, (item, frame) in zip(lc_linecolors, self.data.iteritems()):
axes.plot_date(self.data.index, frame.values, '-', label=item, lw=2, color=lc_color)
axes.set_yscale("log")
axes.set_xlabel(datetime.datetime.isoformat(self.data.index[0])[0:10])
axes.set_title('RHESSI Observing Summary Count Rates')
axes.set_ylabel('Count Rate s$^{-1}$ detector$^{-1}$')
axes.yaxis.grid(True, 'major')
axes.xaxis.grid(False, 'major')
axes.legend()
# @todo: display better tick labels for date range (e.g. 06/01 - 06/05)
formatter = matplotlib.dates.DateFormatter('%H:%M')
axes.xaxis.set_major_formatter(formatter)
axes.fmt_xdata = matplotlib.dates.DateFormatter('%H:%M')
figure.autofmt_xdate()
figure.show()
