Integrate psi wavelet function from -Inf to x using the rectangle integration method.
Parameters: | wavelet : Wavelet instance or str
precision : int, optional
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Returns: | [int_psi, x] : :
[int_psi_d, int_psi_r, x] : :
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Examples
>>> from pywt import Wavelet, integrate_wavelet
>>> wavelet1 = Wavelet('db2')
>>> [int_psi, x] = integrate_wavelet(wavelet1, precision=5)
>>> wavelet2 = Wavelet('bior1.3')
>>> [int_psi_d, int_psi_r, x] = integrate_wavelet(wavelet2, precision=5)
The result of the call depends on the wavelet argument:
for orthogonal and continuous wavelets - an integral of the wavelet function specified on an x-grid:
[int_psi, x_grid] = integrate_wavelet(wavelet, precision)
for other wavelets - integrals of decomposition and reconstruction wavelet functions and a corresponding x-grid:
[int_psi_d, int_psi_r, x_grid] = integrate_wavelet(wavelet, precision)
Computes the central frequency of the psi wavelet function.
Parameters: | wavelet : Wavelet instance, str or tuple
precision : int, optional
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Returns: | scalar : |
Parameters: | wavelet : Wavelet instance or str
scale : scalar precision : int, optional
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Returns: | freq : scalar |
Returns the Quadrature Mirror Filter(QMF).
The magnitude response of QMF is mirror image about pi/2 of that of the input filter.
Parameters: | filter : array_like
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Returns: | qm_filter : ndarray
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Returns the orthogonal filter bank.
The orthogonal filter bank consists of the HPFs and LPFs at decomposition and reconstruction stage for the input scaling filter.
Parameters: | scaling_filter : array_like
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Returns: | orth_filt_bank : tuple of 4 ndarrays
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The following example datasets are available in the module pywt.data:
name description ecg ECG waveform (1024 samples) aero grayscale image (512x512) ascent grayscale image (512x512) camera grayscale image (512x512)
Each can be loaded via a function of the same name.
Example: .. sourcecode:: python
>>> import pywt
>>> camera = pywt.data.camera()