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Commit 9a84637

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high-in-entropyhigh-in-entropy
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Merge pull request #2 from matplotlib/master
doc
2 parents 539d8b8 + 2208665 commit 9a84637
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‎examples/animation/random_walk.py

Copy file name to clipboardExpand all lines: examples/animation/random_walk.py
+11-12Lines changed: 11 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -7,31 +7,29 @@
77

88
import numpy as np
99
import matplotlib.pyplot as plt
10-
import mpl_toolkits.mplot3d.axes3d as p3
1110
import matplotlib.animation as animation
1211

1312
# Fixing random state for reproducibility
1413
np.random.seed(19680801)
1514

1615

17-
def Gen_RandLine(length, dims=2):
16+
def gen_rand_line(length, dims=2):
1817
"""
1918
Create a line using a random walk algorithm
2019
2120
length is the number of points for the line.
2221
dims is the number of dimensions the line has.
2322
"""
24-
lineData = np.empty((dims, length))
25-
lineData[:, 0] = np.random.rand(dims)
23+
line_data = np.empty((dims, length))
24+
line_data[:, 0] = np.random.rand(dims)
2625
for index in range(1, length):
2726
# scaling the random numbers by 0.1 so
2827
# movement is small compared to position.
2928
# subtraction by 0.5 is to change the range to [-0.5, 0.5]
3029
# to allow a line to move backwards.
31-
step = ((np.random.rand(dims) - 0.5) * 0.1)
32-
lineData[:, index] = lineData[:, index - 1] + step
33-
34-
return lineData
30+
step = (np.random.rand(dims) - 0.5) * 0.1
31+
line_data[:, index] = line_data[:, index - 1] + step
32+
return line_data
3533

3634

3735
def update_lines(num, dataLines, lines):
@@ -41,12 +39,13 @@ def update_lines(num, dataLines, lines):
4139
line.set_3d_properties(data[2, :num])
4240
return lines
4341

42+
4443
# Attaching 3D axis to the figure
4544
fig = plt.figure()
46-
ax = p3.Axes3D(fig)
45+
ax = fig.add_subplot(projection="3d")
4746

4847
# Fifty lines of random 3-D lines
49-
data = [Gen_RandLine(25, 3) for index in range(50)]
48+
data = [gen_rand_line(25, 3) for index in range(50)]
5049

5150
# Creating fifty line objects.
5251
# NOTE: Can't pass empty arrays into 3d version of plot()
@@ -65,7 +64,7 @@ def update_lines(num, dataLines, lines):
6564
ax.set_title('3D Test')
6665

6766
# Creating the Animation object
68-
line_ani = animation.FuncAnimation(fig, update_lines, 25, fargs=(data, lines),
69-
interval=50, blit=False)
67+
line_ani = animation.FuncAnimation(
68+
fig, update_lines, 25, fargs=(data, lines), interval=50)
7069

7170
plt.show()

‎lib/matplotlib/units.py

Copy file name to clipboardExpand all lines: lib/matplotlib/units.py
+30-70Lines changed: 30 additions & 70 deletions
Original file line numberDiff line numberDiff line change
@@ -55,9 +55,10 @@ class ConversionError(TypeError):
5555

5656
class AxisInfo(object):
5757
"""
58-
Information to support default axis labeling, tick labeling, and
59-
default limits. An instance of this class must be returned by
60-
:meth:`ConversionInterface.axisinfo`.
58+
Information to support default axis labeling, tick labeling, and limits.
59+
60+
An instance of this class must be returned by
61+
`ConversionInterface.axisinfo`.
6162
"""
6263
def __init__(self, majloc=None, minloc=None,
6364
majfmt=None, minfmt=None, label=None,
@@ -96,8 +97,7 @@ class ConversionInterface(object):
9697
@staticmethod
9798
def axisinfo(unit, axis):
9899
"""
99-
Return an `~units.AxisInfo` instance for the axis with the
100-
specified units.
100+
Return an `~units.AxisInfo` for the axis with the specified units.
101101
"""
102102
return None
103103

@@ -112,19 +112,19 @@ def default_units(x, axis):
112112
def convert(obj, unit, axis):
113113
"""
114114
Convert *obj* using *unit* for the specified *axis*.
115-
If *obj* is a sequence, return the converted sequence.
116-
The output must be a sequence of scalars that can be used by the numpy
117-
array layer.
115+
116+
If *obj* is a sequence, return the converted sequence. The output must
117+
be a sequence of scalars that can be used by the numpy array layer.
118118
"""
119119
return obj
120120

121121
@staticmethod
122122
def is_numlike(x):
123123
"""
124-
The Matplotlib datalim, autoscaling, locators etc work with
125-
scalars which are the units converted to floats given the
126-
current unit. The converter may be passed these floats, or
127-
arrays of them, even when units are set.
124+
The Matplotlib datalim, autoscaling, locators etc work with scalars
125+
which are the units converted to floats given the current unit. The
126+
converter may be passed these floats, or arrays of them, even when
127+
units are set.
128128
"""
129129
if np.iterable(x):
130130
for thisx in x:
@@ -134,73 +134,33 @@ def is_numlike(x):
134134

135135

136136
class Registry(dict):
137-
"""
138-
A register that maps types to conversion interfaces.
139-
"""
140-
def __init__(self):
141-
dict.__init__(self)
142-
self._cached = {}
137+
"""Register types with conversion interface."""
143138

144139
def get_converter(self, x):
145-
"""
146-
Get the converter for data that has the same type as *x*. If no
147-
converters are registered for *x*, returns ``None``.
148-
"""
149-
150-
if not len(self):
151-
return None # nothing registered
152-
# DISABLED idx = id(x)
153-
# DISABLED cached = self._cached.get(idx)
154-
# DISABLED if cached is not None: return cached
155-
156-
converter = None
157-
classx = getattr(x, '__class__', None)
158-
159-
if classx is not None:
160-
converter = self.get(classx)
161-
162-
if converter is None and hasattr(x, "values"):
163-
# this unpacks pandas series or dataframes...
164-
x = x.values
165-
166-
# If x is an array, look inside the array for data with units
140+
"""Get the converter interface instance for *x*, or None."""
141+
if hasattr(x, "values"):
142+
x = x.values # Unpack pandas Series and DataFrames.
167143
if isinstance(x, np.ndarray):
144+
# In case x in a masked array, access the underlying data (only its
145+
# type matters). If x is a regular ndarray, getdata() just returns
146+
# the array itself.
147+
x = np.ma.getdata(x).ravel()
168148
# If there are no elements in x, infer the units from its dtype
169149
if not x.size:
170150
return self.get_converter(np.array([0], dtype=x.dtype))
171-
xravel = x.ravel()
172-
try:
173-
# pass the first value of x that is not masked back to
174-
# get_converter
175-
if not np.all(xravel.mask):
176-
# Get first non-masked item
177-
converter = self.get_converter(
178-
xravel[np.argmin(xravel.mask)])
179-
return converter
180-
except AttributeError:
181-
# not a masked_array
182-
# Make sure we don't recurse forever -- it's possible for
183-
# ndarray subclasses to continue to return subclasses and
184-
# not ever return a non-subclass for a single element.
185-
next_item = xravel[0]
186-
if (not isinstance(next_item, np.ndarray) or
187-
next_item.shape != x.shape):
188-
converter = self.get_converter(next_item)
189-
return converter
190-
191-
# If we haven't found a converter yet, try to get the first element
192-
if converter is None:
193-
try:
194-
thisx = cbook.safe_first_element(x)
151+
try: # Look up in the cache.
152+
return self[type(x)]
153+
except KeyError:
154+
try: # If cache lookup fails, look up based on first element...
155+
first = cbook.safe_first_element(x)
195156
except (TypeError, StopIteration):
196157
pass
197158
else:
198-
if classx and classx != getattr(thisx, '__class__', None):
199-
converter = self.get_converter(thisx)
200-
return converter
201-
202-
# DISABLED self._cached[idx] = converter
203-
return converter
159+
# ... and avoid infinite recursion for pathological iterables
160+
# where indexing returns instances of the same iterable class.
161+
if type(first) is not type(x):
162+
return self.get_converter(first)
163+
return None
204164

205165

206166
registry = Registry()

‎tutorials/toolkits/mplot3d.py

Copy file name to clipboardExpand all lines: tutorials/toolkits/mplot3d.py
+9-12Lines changed: 9 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -14,24 +14,21 @@
1414
1515
Getting started
1616
---------------
17-
An Axes3D object is created just like any other axes using
18-
the projection='3d' keyword.
19-
Create a new :class:`matplotlib.figure.Figure` and
20-
add a new axes to it of type :class:`~mpl_toolkits.mplot3d.Axes3D`::
17+
3D Axes (of class `Axes3D`) are created by passing the ``projection="3d"``
18+
keyword argument to `Figure.add_subplot`::
2119
2220
import matplotlib.pyplot as plt
23-
from mpl_toolkits.mplot3d import Axes3D
2421
fig = plt.figure()
2522
ax = fig.add_subplot(111, projection='3d')
2623
27-
.. versionadded:: 1.0.0
28-
This approach is the preferred method of creating a 3D axes.
24+
.. versionchanged:: 1.0.0
25+
Prior to Matplotlib 1.0.0, `Axes3D` needed to be directly instantiated with
26+
``from mpl_toolkits.mplot3d import Axes3D; ax = Axes3D(fig)``.
2927
30-
.. note::
31-
Prior to version 1.0.0, the method of creating a 3D axes was
32-
different. For those using older versions of matplotlib, change
33-
``ax = fig.add_subplot(111, projection='3d')``
34-
to ``ax = Axes3D(fig)``.
28+
.. versionchanged:: 3.2.0
29+
Prior to Matplotlib 3.2.0, it was necessary to explicitly import the
30+
:mod:`mpl_toolkits.mplot3d` module to make the '3d' projection to
31+
`Figure.add_subplot`.
3532
3633
See the :ref:`toolkit_mplot3d-faq` for more information about the mplot3d
3734
toolkit.

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