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mdboommdboom
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Merge pull request #1247 from pelson/log_axvline
Log axvline
2 parents 384e492 + 237e6d0 commit 73e3131

7 files changed

Lines changed: 786 additions & 49 deletions

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‎lib/matplotlib/__init__.py‎

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1075,6 +1075,7 @@ def tk_window_focus():
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'matplotlib.tests.test_patches',
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'matplotlib.tests.test_pickle',
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'matplotlib.tests.test_rcparams',
1078+
'matplotlib.tests.test_scale',
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'matplotlib.tests.test_simplification',
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'matplotlib.tests.test_spines',
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'matplotlib.tests.test_text',

‎lib/matplotlib/scale.py‎

Lines changed: 47 additions & 32 deletions
Original file line numberDiff line numberDiff line change
@@ -1,16 +1,17 @@
11
from __future__ import print_function
2-
import textwrap
2+
33
import numpy as np
44
from numpy import ma
5-
MaskedArray = ma.MaskedArray
65

7-
from cbook import dedent
8-
from ticker import NullFormatter, ScalarFormatter, LogFormatterMathtext, Formatter
9-
from ticker import NullLocator, LogLocator, AutoLocator, SymmetricalLogLocator, FixedLocator
10-
from ticker import is_decade
11-
from transforms import Transform, IdentityTransform
6+
from matplotlib.cbook import dedent
7+
from matplotlib.ticker import (NullFormatter, ScalarFormatter,
8+
LogFormatterMathtext)
9+
from matplotlib.ticker import (NullLocator, LogLocator, AutoLocator,
10+
SymmetricalLogLocator)
11+
from matplotlib.transforms import Transform, IdentityTransform
1212
from matplotlib import docstring
1313

14+
1415
class ScaleBase(object):
1516
"""
1617
The base class for all scales.
@@ -31,15 +32,15 @@ def get_transform(self):
3132
Return the :class:`~matplotlib.transforms.Transform` object
3233
associated with this scale.
3334
"""
34-
raise NotImplementedError
35+
raise NotImplementedError()
3536

3637
def set_default_locators_and_formatters(self, axis):
3738
"""
3839
Set the :class:`~matplotlib.ticker.Locator` and
3940
:class:`~matplotlib.ticker.Formatter` objects on the given
4041
axis to match this scale.
4142
"""
42-
raise NotImplementedError
43+
raise NotImplementedError()
4344

4445
def limit_range_for_scale(self, vmin, vmax, minpos):
4546
"""
@@ -51,6 +52,7 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
5152
"""
5253
return vmin, vmax
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55+
5456
class LinearScale(ScaleBase):
5557
"""
5658
The default linear scale.
@@ -90,10 +92,12 @@ def _mask_non_positives(a):
9092
return ma.MaskedArray(a, mask=mask)
9193
return a
9294

95+
9396
def _clip_non_positives(a):
9497
a[a <= 0.0] = 1e-300
9598
return a
9699

100+
97101
class LogScale(ScaleBase):
98102
"""
99103
A standard logarithmic scale. Care is taken so non-positive
@@ -115,21 +119,21 @@ class LogTransformBase(Transform):
115119
input_dims = 1
116120
output_dims = 1
117121
is_separable = True
118-
122+
has_inverse = True
123+
119124
def __init__(self, nonpos):
120125
Transform.__init__(self)
121126
if nonpos == 'mask':
122127
self._handle_nonpos = _mask_non_positives
123128
else:
124129
self._handle_nonpos = _clip_non_positives
125130

126-
127131
class Log10Transform(LogTransformBase):
128132
base = 10.0
129133

130-
def transform(self, a):
134+
def transform_non_affine(self, a):
131135
a = self._handle_nonpos(a * 10.0)
132-
if isinstance(a, MaskedArray):
136+
if isinstance(a, ma.MaskedArray):
133137
return ma.log10(a)
134138
return np.log10(a)
135139

@@ -140,9 +144,10 @@ class InvertedLog10Transform(Transform):
140144
input_dims = 1
141145
output_dims = 1
142146
is_separable = True
147+
has_inverse = True
143148
base = 10.0
144149

145-
def transform(self, a):
150+
def transform_non_affine(self, a):
146151
return ma.power(10.0, a) / 10.0
147152

148153
def inverted(self):
@@ -151,9 +156,9 @@ def inverted(self):
151156
class Log2Transform(LogTransformBase):
152157
base = 2.0
153158

154-
def transform(self, a):
159+
def transform_non_affine(self, a):
155160
a = self._handle_nonpos(a * 2.0)
156-
if isinstance(a, MaskedArray):
161+
if isinstance(a, ma.MaskedArray):
157162
return ma.log(a) / np.log(2)
158163
return np.log2(a)
159164

@@ -164,9 +169,10 @@ class InvertedLog2Transform(Transform):
164169
input_dims = 1
165170
output_dims = 1
166171
is_separable = True
172+
has_inverse = True
167173
base = 2.0
168174

169-
def transform(self, a):
175+
def transform_non_affine(self, a):
170176
return ma.power(2.0, a) / 2.0
171177

172178
def inverted(self):
@@ -175,9 +181,9 @@ def inverted(self):
175181
class NaturalLogTransform(LogTransformBase):
176182
base = np.e
177183

178-
def transform(self, a):
184+
def transform_non_affine(self, a):
179185
a = self._handle_nonpos(a * np.e)
180-
if isinstance(a, MaskedArray):
186+
if isinstance(a, ma.MaskedArray):
181187
return ma.log(a)
182188
return np.log(a)
183189

@@ -188,9 +194,10 @@ class InvertedNaturalLogTransform(Transform):
188194
input_dims = 1
189195
output_dims = 1
190196
is_separable = True
197+
has_inverse = True
191198
base = np.e
192199

193-
def transform(self, a):
200+
def transform_non_affine(self, a):
194201
return ma.power(np.e, a) / np.e
195202

196203
def inverted(self):
@@ -200,7 +207,8 @@ class LogTransform(Transform):
200207
input_dims = 1
201208
output_dims = 1
202209
is_separable = True
203-
210+
has_inverse = True
211+
204212
def __init__(self, base, nonpos):
205213
Transform.__init__(self)
206214
self.base = base
@@ -209,9 +217,9 @@ def __init__(self, base, nonpos):
209217
else:
210218
self._handle_nonpos = _clip_non_positives
211219

212-
def transform(self, a):
220+
def transform_non_affine(self, a):
213221
a = self._handle_nonpos(a * self.base)
214-
if isinstance(a, MaskedArray):
222+
if isinstance(a, ma.MaskedArray):
215223
return ma.log(a) / np.log(self.base)
216224
return np.log(a) / np.log(self.base)
217225

@@ -222,18 +230,18 @@ class InvertedLogTransform(Transform):
222230
input_dims = 1
223231
output_dims = 1
224232
is_separable = True
225-
233+
has_inverse = True
234+
226235
def __init__(self, base):
227236
Transform.__init__(self)
228237
self.base = base
229238

230-
def transform(self, a):
239+
def transform_non_affine(self, a):
231240
return ma.power(self.base, a) / self.base
232241

233242
def inverted(self):
234243
return LogScale.LogTransform(self.base)
235-
236-
244+
237245
def __init__(self, axis, **kwargs):
238246
"""
239247
*basex*/*basey*:
@@ -316,7 +324,8 @@ class SymmetricalLogTransform(Transform):
316324
input_dims = 1
317325
output_dims = 1
318326
is_separable = True
319-
327+
has_inverse = True
328+
320329
def __init__(self, base, linthresh, linscale):
321330
Transform.__init__(self)
322331
self.base = base
@@ -325,7 +334,7 @@ def __init__(self, base, linthresh, linscale):
325334
self._linscale_adj = (linscale / (1.0 - self.base ** -1))
326335
self._log_base = np.log(base)
327336

328-
def transform(self, a):
337+
def transform_non_affine(self, a):
329338
sign = np.sign(a)
330339
masked = ma.masked_inside(a, -self.linthresh, self.linthresh, copy=False)
331340
log = sign * self.linthresh * (
@@ -344,7 +353,8 @@ class InvertedSymmetricalLogTransform(Transform):
344353
input_dims = 1
345354
output_dims = 1
346355
is_separable = True
347-
356+
has_inverse = True
357+
348358
def __init__(self, base, linthresh, linscale):
349359
Transform.__init__(self)
350360
symlog = SymmetricalLogScale.SymmetricalLogTransform(base, linthresh, linscale)
@@ -354,7 +364,7 @@ def __init__(self, base, linthresh, linscale):
354364
self.linscale = linscale
355365
self._linscale_adj = (linscale / (1.0 - self.base ** -1))
356366

357-
def transform(self, a):
367+
def transform_non_affine(self, a):
358368
sign = np.sign(a)
359369
masked = ma.masked_inside(a, -self.invlinthresh, self.invlinthresh, copy=False)
360370
exp = sign * self.linthresh * (
@@ -434,17 +444,19 @@ def get_transform(self):
434444
return self._transform
435445

436446

437-
438447
_scale_mapping = {
439448
'linear' : LinearScale,
440449
'log' : LogScale,
441450
'symlog' : SymmetricalLogScale
442451
}
452+
453+
443454
def get_scale_names():
444455
names = _scale_mapping.keys()
445456
names.sort()
446457
return names
447458

459+
448460
def scale_factory(scale, axis, **kwargs):
449461
"""
450462
Return a scale class by name.
@@ -462,6 +474,7 @@ def scale_factory(scale, axis, **kwargs):
462474
scale_factory.__doc__ = dedent(scale_factory.__doc__) % \
463475
{'names': " | ".join(get_scale_names())}
464476

477+
465478
def register_scale(scale_class):
466479
"""
467480
Register a new kind of scale.
@@ -470,6 +483,7 @@ def register_scale(scale_class):
470483
"""
471484
_scale_mapping[scale_class.name] = scale_class
472485

486+
473487
def get_scale_docs():
474488
"""
475489
Helper function for generating docstrings related to scales.
@@ -486,6 +500,7 @@ def get_scale_docs():
486500
docs.append("")
487501
return "\n".join(docs)
488502

503+
489504
docstring.interpd.update(
490505
scale = ' | '.join([repr(x) for x in get_scale_names()]),
491506
scale_docs = get_scale_docs().strip(),

‎lib/matplotlib/tests/baseline_images/test_scale/log_scales.pdf‎

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‎lib/matplotlib/tests/baseline_images/test_scale/log_scales.png‎

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