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SF.net SVN: matplotlib:[6393] trunk/matplotlib
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From: <ry...@us...> - 2008-11-11 19:28:41
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Revision: 6393
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=6393&view=rev
Author: ryanmay
Date: 2008-11-11 19:28:38 +0000 (Tue, 11 Nov 2008)
Log Message:
-----------
Update the axes.csd() to match the new options added to mlab.csd(). Move some of the docs from axes.psd() to the common place in mlab.
Modified Paths:
--------------
trunk/matplotlib/CHANGELOG
trunk/matplotlib/lib/matplotlib/axes.py
trunk/matplotlib/lib/matplotlib/mlab.py
Modified: trunk/matplotlib/CHANGELOG
===================================================================
--- trunk/matplotlib/CHANGELOG 2008-11-11 18:42:11 UTC (rev 6392)
+++ trunk/matplotlib/CHANGELOG 2008-11-11 19:28:38 UTC (rev 6393)
@@ -1,3 +1,7 @@
+2008-11-11 Update the axes.csd() to match the new options added to
+ mlab.csd(). Move some of the docs from axes.psd() to
+ the common place in mlab. - RM
+
2008-11-11 Update the mlab.csd() to match the new options added to
mlab.psd(). Factor out the keyword argument docs so that
they can be shared between the two functions. - RM
Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py 2008-11-11 18:42:11 UTC (rev 6392)
+++ trunk/matplotlib/lib/matplotlib/axes.py 2008-11-11 19:28:38 UTC (rev 6393)
@@ -6531,9 +6531,10 @@
call signature::
psd(x, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
- window=mlab.window_hanning, noverlap=0, **kwargs)
+ window=mlab.window_hanning, noverlap=0, pad_to=None,
+ sides='default', **kwargs)
- The power spectral density by Welches average periodogram
+ The power spectral density by Welch's average periodogram
method. The vector *x* is divided into *NFFT* length
segments. Each segment is detrended by function *detrend* and
windowed by function *window*. *noverlap* gives the length of
@@ -6542,41 +6543,14 @@
scaling to correct for power loss due to windowing. *Fs* is the
sampling frequency.
- Keyword arguments:
+ %(PSD)s
- *NFFT*: integer
- The length of the fft segment, must be a power of 2
-
- *Fs*: integer
- The sampling frequency.
-
*Fc*: integer
The center frequency of *x* (defaults to 0), which offsets
the x extents of the plot to reflect the frequency range used
when a signal is acquired and then filtered and downsampled to
baseband.
- *detrend*:
- The function applied to each segment before fft-ing,
- designed to remove the mean or linear trend. Unlike in
- matlab, where the *detrend* parameter is a vector, in
- matplotlib is it a function. The :mod:`~matplotlib.pylab`
- module defines :func:`~matplotlib.pylab.detrend_none`,
- :func:`~matplotlib.pylab.detrend_mean`, and
- :func:`~matplotlib.pylab.detrend_linear`, but you can use
- a custom function as well.
-
- *window*:
- The function used to window the segments. *window* is a
- function, unlike in matlab where it is a vector.
- :mod:`~matplotlib.pylab` defines
- :func:`~matplotlib.pylab.window_none`, and
- :func:`~matplotlib.pylab.window_hanning`, but you can use
- a custom function as well.
-
- *noverlap*: integer
- Gives the length of the overlap between segments.
-
Returns the tuple (*Pxx*, *freqs*).
For plotting, the power is plotted as
@@ -6615,17 +6589,24 @@
self.set_yticks(ticks)
return pxx, freqs
- psd.__doc__ = cbook.dedent(psd.__doc__) % martist.kwdocd
+ psd_doc_dict = dict()
+ psd_doc_dict.update(martist.kwdocd)
+ psd_doc_dict.update(mlab.kwdocd)
+ psd_doc_dict['PSD'] = cbook.dedent(psd_doc_dict['PSD'])
+ psd.__doc__ = cbook.dedent(psd.__doc__) % psd_doc_dict
+
def csd(self, x, y, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
- window=mlab.window_hanning, noverlap=0, **kwargs):
+ window=mlab.window_hanning, noverlap=0, pad_to=None,
+ sides='default', **kwargs):
"""
call signature::
csd(x, y, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
- window=window_hanning, noverlap=0, **kwargs)
+ window=mlab.window_hanning, noverlap=0, pad_to=None,
+ sides='default', **kwargs)
- The cross spectral density :math:`P_{xy}` by Welches average
+ The cross spectral density :math:`P_{xy}` by Welch's average
periodogram method. The vectors *x* and *y* are divided into
*NFFT* length segments. Each segment is detrended by function
*detrend* and windowed by function *window*. The product of
@@ -6637,6 +6618,14 @@
(complex valued), and :math:`10\log_{10}|P_{xy}|` is
plotted.
+ %(PSD)s
+
+ *Fc*: integer
+ The center frequency of *x* (defaults to 0), which offsets
+ the x extents of the plot to reflect the frequency range used
+ when a signal is acquired and then filtered and downsampled to
+ baseband.
+
References:
Bendat & Piersol -- Random Data: Analysis and Measurement
Procedures, John Wiley & Sons (1986)
@@ -6654,7 +6643,8 @@
For a description of the optional parameters.
"""
if not self._hold: self.cla()
- pxy, freqs = mlab.csd(x, y, NFFT, Fs, detrend, window, noverlap)
+ pxy, freqs = mlab.csd(x, y, NFFT, Fs, detrend, window, noverlap,
+ pad_to, sides)
pxy.shape = len(freqs),
# pxy is complex
freqs += Fc
@@ -6672,7 +6662,8 @@
self.set_yticks(ticks)
return pxy, freqs
- csd.__doc__ = cbook.dedent(csd.__doc__) % martist.kwdocd
+ csd.__doc__ = cbook.dedent(csd.__doc__) % psd_doc_dict
+ del psd_doc_dict #So that this does not become an Axes attribute
def cohere(self, x, y, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
window=mlab.window_hanning, noverlap=0, **kwargs):
Modified: trunk/matplotlib/lib/matplotlib/mlab.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/mlab.py 2008-11-11 18:42:11 UTC (rev 6392)
+++ trunk/matplotlib/lib/matplotlib/mlab.py 2008-11-11 19:28:38 UTC (rev 6393)
@@ -310,48 +310,55 @@
#Split out these keyword docs so that they can be used elsewhere
kwdocd = dict()
kwdocd['PSD'] ="""
- *NFFT*
- The number of data points used in each block for the FFT.
- Must be even; a power 2 is most efficient. The default value is 256.
+ Keyword arguments:
- *Fs*
- The sampling frequency (samples per time unit). It is used
- to calculate the Fourier frequencies, freqs, in cycles per time
- unit. The default value is 2.
+ *NFFT*: integer
+ The number of data points used in each block for the FFT.
+ Must be even; a power 2 is most efficient. The default value is 256.
- *detrend*
- Any callable function (unlike in matlab where it is a vector).
- For examples, see :func:`detrend`, :func:`detrend_none`, and
- :func:`detrend_mean`. The default is :func:`detrend_none`.
+ *Fs*: scalar
+ The sampling frequency (samples per time unit). It is used
+ to calculate the Fourier frequencies, freqs, in cycles per time
+ unit. The default value is 2.
- *window*
- A function or a vector of length *NFFT*. To create window
- vectors see :func:`window_hanning`, :func:`window_none`,
- :func:`numpy.blackman`, :func:`numpy.hamming`,
- :func:`numpy.bartlett`, :func:`scipy.signal`,
- :func:`scipy.signal.get_window`, etc. The default is
- :func:`window_hanning`. If a function is passed as the
- argument, it must take a data segment as an argument and
- return the windowed version of the segment.
+ *detrend*: callable
+ The function applied to each segment before fft-ing,
+ designed to remove the mean or linear trend. Unlike in
+ matlab, where the *detrend* parameter is a vector, in
+ matplotlib is it a function. The :mod:`~matplotlib.pylab`
+ module defines :func:`~matplotlib.pylab.detrend_none`,
+ :func:`~matplotlib.pylab.detrend_mean`, and
+ :func:`~matplotlib.pylab.detrend_linear`, but you can use
+ a custom function as well.
- *noverlap*
- The number of points of overlap between blocks. The default value
- is 0 (no overlap).
+ *window*: callable or ndarray
+ A function or a vector of length *NFFT*. To create window
+ vectors see :func:`window_hanning`, :func:`window_none`,
+ :func:`numpy.blackman`, :func:`numpy.hamming`,
+ :func:`numpy.bartlett`, :func:`scipy.signal`,
+ :func:`scipy.signal.get_window`, etc. The default is
+ :func:`window_hanning`. If a function is passed as the
+ argument, it must take a data segment as an argument and
+ return the windowed version of the segment.
- *pad_to*
- The number of points to which the data segment is padd when
- performing the FFT. This can be different from *NFFT*, which
- specifies the number of data points used. While not increasing
- the actual resolution of the psd (the minimum distance between
- resolvable peaks), this can give more points in the plot,
- allowing for more detail. This corresponds to the *n* parameter
- in the call to fft(). The default is None, which sets *pad_to*
- equal to *NFFT*
+ *noverlap*: integer
+ The number of points of overlap between blocks. The default value
+ is 0 (no overlap).
- *sides* [ 'default' | 'onesided' | 'twosided' ]
- Specifies which sides of the PSD to return. Default gives the
- default behavior, which returns one-sided for real data and both
- for complex data. 'one' forces the return of a one-sided PSD, while
+ *pad_to*: integer
+ The number of points to which the data segment is padd when
+ performing the FFT. This can be different from *NFFT*, which
+ specifies the number of data points used. While not increasing
+ the actual resolution of the psd (the minimum distance between
+ resolvable peaks), this can give more points in the plot,
+ allowing for more detail. This corresponds to the *n* parameter
+ in the call to fft(). The default is None, which sets *pad_to*
+ equal to *NFFT*
+
+ *sides*: [ 'default' | 'onesided' | 'twosided' ]
+ Specifies which sides of the PSD to return. Default gives the
+ default behavior, which returns one-sided for real data and both
+ for complex data. 'one' forces the return of a one-sided PSD, while
'both' forces two-sided.
"""
psd.__doc__ = psd.__doc__ % kwdocd
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