/usr/lib/python3/dist-packages/dtcwt/plotting.py is in python3-dtcwt 0.11.0-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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Convenience functions for plotting DTCWT-related objects.
"""
from __future__ import absolute_import
import numpy as np
from matplotlib.pyplot import *
__all__ = (
'overlay_quiver',
)
def overlay_quiver(image, vectorField, level, offset):
"""Overlays nicely coloured quiver plot of complex coefficients over original full-size image,
providing a useful phase visualisation.
:param image: array holding grayscale values on the interval [0, 255] to display
:param vectorField: a single [MxNx6] numpy array of DTCWT coefficients
:param level: the transform level (1-indexed) of *vectorField*.
:param offset: Offset for DTCWT coefficients (typically 0.5)
.. note::
The *level* parameter is 1-indexed meaning that the third level has
index "3". This is unusual in Python but is kept for compatibility
with similar MATLAB routines.
Should also work with other types of complex arrays (e.g., SLP
coefficients), as long as the format is the same.
Usage example:
.. plot::
:include-source: true
import dtcwt
import dtcwt.plotting as plotting
mandrill = datasets.mandrill()
transform2d = dtcwt.Transform2d()
mandrill_t = transform2d.forward(mandrill, nlevels=5)
plotting.overlay_quiver(mandrill*255, mandrill_t.highpasses[-1], 5, 0.5)
.. codeauthor:: R. Anderson, 2005 (MATLAB)
.. codeauthor:: S. C. Forshaw, 2014 (Python)
"""
# Make sure imshow() uses the full range of greyscale values
imshow(image, cmap=cm.gray, clim=(0,255))
hold(True)
# Set up the grid for the quiver plot
g1 = np.kron(np.arange(0, vectorField[:,:,0].shape[0]).T, np.ones((1,vectorField[:,:,0].shape[1])))
g2 = np.kron(np.ones((vectorField[:,:,0].shape[0], 1)), np.arange(0, vectorField[:,:,0].shape[1]))
# Choose a coloUrmap
cmap = cm.spectral
scalefactor = np.max(np.max(np.max(np.max(np.abs(vectorField)))))
vectorField[-1,-1,:] = scalefactor
for sb in range(0, vectorField.shape[2]):
hold(True)
thiscolour = cmap(sb / float(vectorField.shape[2])) # Select colour for this subband
hq = quiver(g2*(2**level) + offset*(2**level), g1*(2**level) + offset*(2**level), np.real(vectorField[:,:,sb]), \
np.imag(vectorField[:,:,sb]), color=thiscolour, scale=scalefactor*2**level)
quiverkey(hq, 1.05, 1.00-0.035*sb, 0, "subband " + np.str(sb), coordinates='axes', color=thiscolour, labelcolor=thiscolour, labelpos='E')
hold(False)
return hq
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