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Commit9a84637

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Merge pull request#2 from matplotlib/master
doc
2 parents539d8b8 +2208665 commit9a84637

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3 files changed

+50
-94
lines changed

3 files changed

+50
-94
lines changed

‎examples/animation/random_walk.py

Lines changed: 11 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -7,31 +7,29 @@
77

88
importnumpyasnp
99
importmatplotlib.pyplotasplt
10-
importmpl_toolkits.mplot3d.axes3dasp3
1110
importmatplotlib.animationasanimation
1211

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

1615

17-
defGen_RandLine(length,dims=2):
16+
defgen_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
forindexinrange(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-
returnlineData
30+
step= (np.random.rand(dims)-0.5)*0.1
31+
line_data[:,index]=line_data[:,index-1]+step
32+
returnline_data
3533

3634

3735
defupdate_lines(num,dataLines,lines):
@@ -41,12 +39,13 @@ def update_lines(num, dataLines, lines):
4139
line.set_3d_properties(data[2, :num])
4240
returnlines
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)forindexinrange(50)]
48+
data= [gen_rand_line(25,3)forindexinrange(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

Lines changed: 30 additions & 70 deletions
Original file line numberDiff line numberDiff line change
@@ -55,9 +55,10 @@ class ConversionError(TypeError):
5555

5656
classAxisInfo(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
defaxisinfo(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
returnNone
103103

@@ -112,19 +112,19 @@ def default_units(x, axis):
112112
defconvert(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 bea sequence of scalars that can be used by the numpy
117-
array layer.
115+
116+
If *obj* isa sequence, return the converted sequence. The output must
117+
be a sequence of scalars that can be used by the numpyarray layer.
118118
"""
119119
returnobj
120120

121121
@staticmethod
122122
defis_numlike(x):
123123
"""
124-
The Matplotlib datalim, autoscaling, locators etc work with
125-
scalarswhich are the units converted to floats given the
126-
current unit. Theconverter may be passed these floats, or
127-
arrays of them, even whenunits 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
ifnp.iterable(x):
130130
forthisxinx:
@@ -134,73 +134,33 @@ def is_numlike(x):
134134

135135

136136
classRegistry(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
defget_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-
ifnotlen(self):
151-
returnNone# 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-
ifclassxisnotNone:
160-
converter=self.get(classx)
161-
162-
ifconverterisNoneandhasattr(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+
ifhasattr(x,"values"):
142+
x=x.values# Unpack pandas Series and DataFrames.
167143
ifisinstance(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
ifnotx.size:
170150
returnself.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-
ifnotnp.all(xravel.mask):
176-
# Get first non-masked item
177-
converter=self.get_converter(
178-
xravel[np.argmin(xravel.mask)])
179-
returnconverter
180-
exceptAttributeError:
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 (notisinstance(next_item,np.ndarray)or
187-
next_item.shape!=x.shape):
188-
converter=self.get_converter(next_item)
189-
returnconverter
190-
191-
# If we haven't found a converter yet, try to get the first element
192-
ifconverterisNone:
193-
try:
194-
thisx=cbook.safe_first_element(x)
151+
try:# Look up in the cache.
152+
returnself[type(x)]
153+
exceptKeyError:
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-
ifclassxandclassx!=getattr(thisx,'__class__',None):
199-
converter=self.get_converter(thisx)
200-
returnconverter
201-
202-
# DISABLED self._cached[idx] = converter
203-
returnconverter
159+
# ... and avoid infinite recursion for pathological iterables
160+
# where indexing returns instances of the same iterable class.
161+
iftype(first)isnottype(x):
162+
returnself.get_converter(first)
163+
returnNone
204164

205165

206166
registry=Registry()

‎tutorials/toolkits/mplot3d.py

Lines 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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