def reset_matplotlib():
"""
Reset matplotlib to a common default.
"""
# Set all default values.
mpl.rcdefaults()
# Force agg backend.
plt.switch_backend('agg')
# These settings must be hardcoded for running the comparision tests and
# are not necessarily the default values.
mpl.rcParams['font.family'] = 'Bitstream Vera Sans'
mpl.rcParams['text.hinting'] = False
# Not available for all matplotlib versions.
try:
mpl.rcParams['text.hinting_factor'] = 8
except KeyError:
pass
import locale
locale.setlocale(locale.LC_ALL, str('en_US.UTF-8'))
# Most generic way to get the data folder path.
python类rcdefaults()的实例源码
def _setup():
# The baseline images are created in this locale, so we should use
# it during all of the tests.
try:
locale.setlocale(locale.LC_ALL, str('en_US.UTF-8'))
except locale.Error:
try:
locale.setlocale(locale.LC_ALL, str('English_United States.1252'))
except locale.Error:
warnings.warn(
"Could not set locale to English/United States. "
"Some date-related tests may fail")
plt.switch_backend('Agg') # use Agg backend for these test
if mpl.get_backend().lower() != "agg":
msg = ("Using a wrong matplotlib backend ({0}), "
"which will not produce proper images")
raise Exception(msg.format(mpl.get_backend()))
# These settings *must* be hardcoded for running the comparison
# tests
mpl.rcdefaults() # Start with all defaults
mpl.rcParams['text.hinting'] = True
mpl.rcParams['text.antialiased'] = True
mpl.rcParams['text.hinting_factor'] = 8
# make sure we don't carry over bad plots from former tests
msg = ("no of open figs: {} -> find the last test with ' "
"python tests.py -v' and add a '@cleanup' decorator.")
assert len(plt.get_fignums()) == 0, msg.format(plt.get_fignums())
def reset_matplotlib():
"""
Reset matplotlib to a common default.
"""
# Set all default values.
mpl.rcdefaults()
# Force agg backend.
plt.switch_backend('agg')
test_graphics_others.py 文件源码
项目:PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda
作者: SignalMedia
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def setUp(self):
TestPlotBase.setUp(self)
import matplotlib as mpl
mpl.rcdefaults()
self.ts = tm.makeTimeSeries()
self.ts.name = 'ts'
self.series = tm.makeStringSeries()
self.series.name = 'series'
self.iseries = tm.makePeriodSeries()
self.iseries.name = 'iseries'
test_graphics_others.py 文件源码
项目:PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda
作者: SignalMedia
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def setUp(self):
TestPlotBase.setUp(self)
import matplotlib as mpl
mpl.rcdefaults()
self.tdf = tm.makeTimeDataFrame()
self.hexbin_df = DataFrame({
"A": np.random.uniform(size=20),
"B": np.random.uniform(size=20),
"C": np.arange(20) + np.random.uniform(size=20)})
from pandas import read_csv
path = os.path.join(curpath(), 'data', 'iris.csv')
self.iris = read_csv(path)
test_graphics.py 文件源码
项目:PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda
作者: SignalMedia
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def setUp(self):
import matplotlib as mpl
mpl.rcdefaults()
n = 100
with tm.RNGContext(42):
gender = np.random.choice(['Male', 'Female'], size=n)
classroom = np.random.choice(['A', 'B', 'C'], size=n)
self.hist_df = DataFrame({'gender': gender,
'classroom': classroom,
'height': random.normal(66, 4, size=n),
'weight': random.normal(161, 32, size=n),
'category': random.randint(4, size=n)})
self.mpl_le_1_2_1 = plotting._mpl_le_1_2_1()
self.mpl_ge_1_3_1 = plotting._mpl_ge_1_3_1()
self.mpl_ge_1_4_0 = plotting._mpl_ge_1_4_0()
self.mpl_ge_1_5_0 = plotting._mpl_ge_1_5_0()
if self.mpl_ge_1_4_0:
self.bp_n_objects = 7
else:
self.bp_n_objects = 8
if self.mpl_ge_1_5_0:
# 1.5 added PolyCollections to legend handler
# so we have twice as many items.
self.polycollection_factor = 2
else:
self.polycollection_factor = 1
test_graphics.py 文件源码
项目:PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda
作者: SignalMedia
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def setUp(self):
TestPlotBase.setUp(self)
import matplotlib as mpl
mpl.rcdefaults()
self.ts = tm.makeTimeSeries()
self.ts.name = 'ts'
self.series = tm.makeStringSeries()
self.series.name = 'series'
self.iseries = tm.makePeriodSeries()
self.iseries.name = 'iseries'
test_graphics.py 文件源码
项目:PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda
作者: SignalMedia
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def setUp(self):
TestPlotBase.setUp(self)
import matplotlib as mpl
mpl.rcdefaults()
self.tdf = tm.makeTimeDataFrame()
self.hexbin_df = DataFrame({"A": np.random.uniform(size=20),
"B": np.random.uniform(size=20),
"C": np.arange(20) + np.random.uniform(
size=20)})
from pandas import read_csv
path = os.path.join(curpath(), 'data', 'iris.csv')
self.iris = read_csv(path)
def mfista_plots(fdfin, ptable, filename=None,
plotargs={'ms': 1., }):
isinteractive = plt.isinteractive()
backend = matplotlib.rcParams["backend"]
if isinteractive:
plt.ioff()
matplotlib.use('Agg')
nullfmt = NullFormatter()
# Get model data
modelptable = ptable.copy()
modelptable.observe(fdfin)
# Save fdf
if filename is not None:
util.matplotlibrc(nrows=4, ncols=2, width=400, height=150)
else:
matplotlib.rcdefaults()
fig, axs = plt.subplots(nrows=4, ncols=2, sharex=False)
fdfin.plot(axs=axs[:,0],color="red")
ptable.plot(axs=axs[:,1],color="black", ploterror=True)
modelptable.plot(axs=axs[:,1], color="red")
if filename is not None:
plt.savefig(filename)
plt.close()
else:
plt.show()
if isinteractive:
plt.ion()
matplotlib.use(backend)