def plot(self, filename=None, norm=False, ylim=None,
sides=None, **kargs):
"""a simple plotting routine to plot the PSD versus frequency.
:param str filename: save the figure into a file
:param norm: False by default. If True, the PSD is normalised.
:param ylim: readjust the y range .
:param sides: if not provided, :attr:`sides` is used. See :attr:`sides`
for details.
:param kargs: any optional argument accepted by :func:`pylab.plot`.
.. plot::
:width: 80%
:include-source:
from spectrum import *
p = Periodogram(marple_data)
p() # runs the psd estimate
p.plot(norm=True, marker='o')
"""
#First, check that psd attribute is up-to-date
if self.modified is True:
raise errors.SpectrumModifiedError
# and that it has been computed
if self.__psd is None:
raise errors.SpectrumPSDError
# check that the input sides parameter is correct if provided
if sides is not None:
if sides not in self._sides_choices:
raise errors.SpectrumChoiceError(sides, self._sides_choices)
# if sides is provided but identical to the current psd, nothing to do.
if sides is None or sides == self.sides:
frequencies = self.frequencies()
psd = self.psd
#sides = self.sides
elif sides is not None:
# if sides argument is different from the attribute, we need to
# create a new PSD/Freq but we do not want to touch the attributes
# if data is complex, one-sided is wrong in any case.
if self.datatype == 'complex':
assert sides != 'onesided'
frequencies = self.frequencies(sides=sides)
psd = self.get_converted_psd(sides)
if len(psd) != len(frequencies):
raise ValueError("PSD length is %s and freq length is %s" % (len(psd), len(frequencies)))
from pylab import ylim as plt_ylim
if 'ax' in list(kargs.keys()):
save_ax = plt.gca()
plt.sca(kargs['ax'])
rollback = True
del kargs['ax']
else:
rollback = False
if norm:
pylab.plot(frequencies, 10*pylab.log10(psd/max(psd)), **kargs)
else:
pylab.plot(frequencies, 10*pylab.log10(psd),**kargs)
plt.xlabel('Frequency')
plt.ylabel('Power (dB)')
pylab.grid(True)
if ylim:
plt_ylim(ylim)
if sides == 'onesided':
pylab.xlim(0,self.sampling/2.)
elif sides == 'twosided':
pylab.xlim(0, self.sampling)
elif sides == 'centerdc':
pylab.xlim(-self.sampling/2., self.sampling/2.)
if filename:
pylab.savefig(filename)
if rollback:
plt.sca(save_ax)
del psd, frequencies #is it needed?
def plot(self, filename=None, norm=False, ylim=None, sides=None, **kargs):
"""a simple plotting routine to plot the PSD versus frequency.
:param str filename: save the figure into a file
:param norm: False by default. If True, the PSD is normalised.
:param ylim: readjust the y range .
:param sides: if not provided, :attr:`sides` is used. See :attr:`sides`
for details.
:param kargs: any optional argument accepted by :func:`pylab.plot`.
.. plot::
:width: 80%
:include-source:
from spectrum import *
p = Periodogram(marple_data)
p() # runs the psd estimate
p.plot(norm=True, marker='o')
"""
#First, check that psd attribute is up-to-date
if self.modified is True:
raise errors.SpectrumModifiedError
# and that it has been computed
if self.__psd is None:
raise errors.SpectrumPSDError
# check that the input sides parameter is correct if provided
if sides is not None:
if sides not in self._sides_choices:
raise errors.SpectrumChoiceError(sides, self._sides_choices)
# if sides is provided but identical to the current psd, nothing to do.
if sides is None or sides == self.sides:
frequencies = self.frequencies()
psd = self.psd
#sides = self.sides
elif sides is not None:
# if sides argument is different from the attribute, we need to
# create a new PSD/Freq but we do not want to touch the attributes
# if data is complex, one-sided is wrong in any case.
if self.datatype == 'complex':
assert sides != 'onesided'
frequencies = self.frequencies(sides=sides)
psd = self.get_converted_psd(sides)
if len(psd) != len(frequencies):
raise ValueError("PSD length is %s and freq length is %s" %
(len(psd), len(frequencies)))
from pylab import ylim as plt_ylim
if 'ax' in list(kargs.keys()):
save_ax = plt.gca()
plt.sca(kargs['ax'])
rollback = True
del kargs['ax']
else:
rollback = False
if norm:
pylab.plot(frequencies, 10 * pylab.log10(psd / max(psd)), **kargs)
else:
pylab.plot(frequencies, 10 * pylab.log10(psd), **kargs)
plt.xlabel('Frequency')
plt.ylabel('Power (dB)')
pylab.grid(True)
if ylim:
plt_ylim(ylim)
if sides == 'onesided':
pylab.xlim(0, self.sampling / 2.)
elif sides == 'twosided':
pylab.xlim(0, self.sampling)
elif sides == 'centerdc':
pylab.xlim(-self.sampling / 2., self.sampling / 2.)
if filename:
pylab.savefig(filename)
if rollback:
plt.sca(save_ax)
del psd, frequencies #is it needed?