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Replace mlab functions #9177

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b4e339a
Replace path_length in contour
dstansby Sep 16, 2017
c1fbf27
Deprecate is_closed_polygon
dstansby Sep 21, 2017
0138524
Replace bivariate normal in testing methods
dstansby Sep 21, 2017
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23 changes: 17 additions & 6 deletions lib/matplotlib/contour.py
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Original file line number Diff line number Diff line change
Expand Up @@ -376,7 +376,7 @@ def calc_label_rot_and_inline(self, slc, ind, lw, lc=None, spacing=5):
not empty (lc defaults to the empty list if None). *spacing*
is the space around the label in pixels to leave empty.

Do both of these tasks at once to avoid calling mlab.path_length
Do both of these tasks at once to avoid calculating path lengths
multiple times, which is relatively costly.

The method used here involves calculating the path length
Expand All @@ -391,7 +391,7 @@ def calc_label_rot_and_inline(self, slc, ind, lw, lc=None, spacing=5):
hlw = lw / 2.0

# Check if closed and, if so, rotate contour so label is at edge
closed = mlab.is_closed_polygon(slc)
closed = _is_closed_polygon(slc)
if closed:
slc = np.r_[slc[ind:-1], slc[:ind + 1]]

Expand All @@ -400,8 +400,10 @@ def calc_label_rot_and_inline(self, slc, ind, lw, lc=None, spacing=5):

ind = 0

# Path length in pixel space
pl = mlab.path_length(slc)
# Calculate path lengths
pl = np.zeros(slc.shape[0], dtype=float)
dx = np.diff(slc, axis=0)
pl[1:] = np.cumsum(np.hypot(dx[:, 0], dx[:, 1]))
pl = pl - pl[ind]

# Use linear interpolation to get points around label
Expand Down Expand Up @@ -644,7 +646,7 @@ def labels(self, inline, inline_spacing):
# zero in print_label and locate_label. Other than these
# functions, this is not necessary and should probably be
# eventually removed.
if mlab.is_closed_polygon(lc):
if _is_closed_polygon(lc):
slc = np.r_[slc0, slc0[1:2, :]]
else:
slc = slc0
Expand Down Expand Up @@ -705,6 +707,15 @@ def _find_closest_point_on_leg(p1, p2, p0):
return d, pc


def _is_closed_polygon(X):
"""
Tests whether first and last object in a sequence are the same. These are
presumably coordinates on a polygonal curve, in which case this function
tests if that curve is closed.
"""
return np.all(X[0] == X[-1])


def _find_closest_point_on_path(lc, point):
"""
lc: coordinates of vertices
Expand All @@ -719,7 +730,7 @@ def _find_closest_point_on_path(lc, point):
xcmin = None
legmin = (None, None)

closed = mlab.is_closed_polygon(lc)
closed = _is_closed_polygon(lc)

# build list of legs before and after this vertex
legs = []
Expand Down
5 changes: 5 additions & 0 deletions lib/matplotlib/mlab.py
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Expand Up @@ -1868,6 +1868,7 @@ def derivs(x,t):
return yout


@cbook.deprecated('2.2')
def bivariate_normal(X, Y, sigmax=1.0, sigmay=1.0,
mux=0.0, muy=0.0, sigmaxy=0.0):
"""
Expand Down Expand Up @@ -3812,6 +3813,7 @@ def poly_between(x, ylower, yupper):
return x, y


@cbook.deprecated('2.2')
def is_closed_polygon(X):
"""
Tests whether first and last object in a sequence are the same. These are
Expand Down Expand Up @@ -3911,6 +3913,7 @@ def cross_from_above(x, threshold):
##################################################
# Vector and path length geometry calculations
##################################################
@cbook.deprecated('2.2')
def vector_lengths(X, P=2., axis=None):
"""
Finds the length of a set of vectors in *n* dimensions. This is
Expand All @@ -3925,6 +3928,7 @@ def vector_lengths(X, P=2., axis=None):
return (np.sum(X**(P), axis=axis))**(1./P)


@cbook.deprecated('2.2')
def distances_along_curve(X):
"""
Computes the distance between a set of successive points in *N* dimensions.
Expand All @@ -3937,6 +3941,7 @@ def distances_along_curve(X):
return vector_lengths(X, axis=1)


@cbook.deprecated('2.2')
def path_length(X):
"""
Computes the distance travelled along a polygonal curve in *N* dimensions.
Expand Down
7 changes: 4 additions & 3 deletions lib/matplotlib/tests/test_contour.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,6 @@
import datetime

import numpy as np
from matplotlib import mlab
from matplotlib.testing.decorators import image_comparison
from matplotlib import pyplot as plt
from numpy.testing import assert_array_almost_equal
Expand Down Expand Up @@ -243,8 +242,10 @@ def test_labels():
x = np.arange(-3.0, 3.0, delta)
y = np.arange(-2.0, 2.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z1 = np.exp(-(X**2 + Y**2) / 2) / (2 * np.pi)
Z2 = (np.exp(-(((X - 1) / 1.5)**2 + ((Y - 1) / 0.5)**2) / 2) /
(2 * np.pi * 0.5 * 1.5))

# difference of Gaussians
Z = 10.0 * (Z2 - Z1)

Expand Down
11 changes: 6 additions & 5 deletions lib/matplotlib/tests/test_image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,6 @@
from matplotlib import patches
import matplotlib.pyplot as plt

from matplotlib import mlab
import pytest

from copy import copy
Expand Down Expand Up @@ -611,8 +610,9 @@ def test_rotate_image():
delta = 0.25
x = y = np.arange(-3.0, 3.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z1 = np.exp(-(X**2 + Y**2) / 2) / (2 * np.pi)
Z2 = (np.exp(-(((X - 1) / 1.5)**2 + ((Y - 1) / 0.5)**2) / 2) /
(2 * np.pi * 0.5 * 1.5))
Z = Z2 - Z1 # difference of Gaussians

fig, ax1 = plt.subplots(1, 1)
Expand Down Expand Up @@ -673,8 +673,9 @@ def test_mask_image_over_under():
delta = 0.025
x = y = np.arange(-3.0, 3.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z1 = np.exp(-(X**2 + Y**2) / 2) / (2 * np.pi)
Z2 = (np.exp(-(((X - 1) / 1.5)**2 + ((Y - 1) / 0.5)**2) / 2) /
(2 * np.pi * 0.5 * 1.5))
Z = 10*(Z2 - Z1) # difference of Gaussians

palette = copy(plt.cm.gray)
Expand Down