def test_1d_density_kwarg(plot_1d, s):
try:
np.random.seed(0)
x = np.random.normal(scale=s, size=2000)
fig, ax = plt.subplots()
# hist density = False:
h = hist_plot_1d(ax, x, density=False, bins=np.linspace(-5.5, 5.5, 12))
bar_height = h.get_children()[len(h.get_children()) // 2].get_height()
assert (bar_height == pytest.approx(1, rel=0.1))
# kde density = False:
k = plot_1d(ax, x, density=False)[0]
f = interp1d(k.get_xdata(), k.get_ydata(), 'cubic', assume_sorted=True)
kde_height = f(0)
assert (kde_height == pytest.approx(1, rel=0.1))
# hist density = True:
h = hist_plot_1d(ax, x, density=True, bins=np.linspace(-5.5, 5.5, 12))
bar_height = h.get_children()[len(h.get_children()) // 2].get_height()
assert (bar_height == pytest.approx(erf(0.5 / np.sqrt(2) / s),
rel=0.1))
# kde density = True:
k = plot_1d(ax, x, density=True)[0]
f = interp1d(k.get_xdata(), k.get_ydata(), 'cubic', assume_sorted=True)
kde_height = f(0)
gauss_norm = 1 / np.sqrt(2 * np.pi * s**2)
assert (kde_height == pytest.approx(gauss_norm, rel=0.1))
plt.close("all")
except ImportError:
if 'fastkde' not in sys.modules:
pass
def test_hist_plot_1d():
fig, ax = plt.subplots()
numpy.random.seed(0)
data = numpy.random.randn(1000)
for p in ['', 'astropyhist']:
try:
# Check heights for histtype 'bar'
bars = hist_plot_1d(ax, data, histtype='bar', plotter=p)
assert(numpy.all([isinstance(b, Patch) for b in bars]))
assert(max([b.get_height() for b in bars]) == 1.)
assert(numpy.all(numpy.array([b.get_height() for b in bars])
<= 1.))
# Check heights for histtype 'step'
polygon, = hist_plot_1d(ax, data, histtype='step', plotter=p)
assert(isinstance(polygon, Polygon))
trans = polygon.get_transform() - ax.transData
assert(numpy.isclose(trans.transform(polygon.xy)[:, -1].max(), 1.,
rtol=1e-10, atol=1e-10))
assert(numpy.all(trans.transform(polygon.xy)[:, -1] <= 1.))
# Check heights for histtype 'stepfilled'
polygon, = hist_plot_1d(ax, data, histtype='stepfilled', plotter=p)
assert(isinstance(polygon, Polygon))
trans = polygon.get_transform() - ax.transData
assert(numpy.isclose(trans.transform(polygon.xy)[:, -1].max(), 1.,
rtol=1e-10, atol=1e-10))
assert(numpy.all(trans.transform(polygon.xy)[:, -1] <= 1.))
# Check arguments are passed onward to underlying function
bars = hist_plot_1d(ax, data, histtype='bar',
color='r', alpha=0.5, plotter=p)
cc = ColorConverter.to_rgba('r', alpha=0.5)
assert(numpy.all([b.get_fc() == cc for b in bars]))
polygon, = hist_plot_1d(ax, data, histtype='step',
color='r', alpha=0.5, plotter=p)
assert(polygon.get_ec() == ColorConverter.to_rgba('r', alpha=0.5))
# Check xmin
xmin = -0.5
bars = hist_plot_1d(ax, data, histtype='bar', xmin=xmin, plotter=p)
assert((numpy.array([b.xy[0] for b in bars]) >= -0.5).all())
polygon, = hist_plot_1d(ax, data, histtype='step', xmin=xmin)
assert((polygon.xy[:, 0] >= -0.5).all())
# Check xmax
xmax = 0.5
bars = hist_plot_1d(ax, data, histtype='bar', xmax=xmax, plotter=p)
assert((numpy.array([b.xy[-1] for b in bars]) <= 0.5).all())
polygon, = hist_plot_1d(ax, data, histtype='step',
xmax=xmax, plotter=p)
assert((polygon.xy[:, 0] <= 0.5).all())
# Check xmin and xmax
bars = hist_plot_1d(ax, data, histtype='bar',
xmin=xmin, xmax=xmax, plotter=p)
assert((numpy.array([b.xy[0] for b in bars]) >= -0.5).all())
assert((numpy.array([b.xy[-1] for b in bars]) <= 0.5).all())
polygon, = hist_plot_1d(ax, data, histtype='step',
xmin=xmin, xmax=xmax, plotter=p)
assert((polygon.xy[:, 0] >= -0.5).all())
assert((polygon.xy[:, 0] <= 0.5).all())
plt.close("all")
except ImportError:
if p == 'astropyhist' and 'astropy' not in sys.modules:
pass
def plot(self, ax, paramname_x, paramname_y=None, *args, **kwargs):
"""Interface for 2D and 1D plotting routines.
Produces a single 1D or 2D plot on an axis.
Parameters
----------
ax: matplotlib.axes.Axes
Axes to plot on
paramname_x: str
Choice of parameter to plot on x-coordinate from self.columns.
paramname_y: str
Choice of parameter to plot on y-coordinate from self.columns.
optional, if not provided, or the same as paramname_x, then 1D plot
produced.
plot_type: str
Must be in {'kde', 'scatter', 'hist', 'fastkde'} for 2D plots and
in {'kde', 'hist', 'fastkde', 'astropyhist'} for 1D plots.
optional, (Default: 'kde')
ncompress: int
Number of samples to use in plotting routines.
optional, Default dynamically chosen
q: str, float, (float, float)
Plot the `q` inner posterior quantiles in 1d 'kde' plots. To plot
the full range, set `q=0` or `q=1`.
* if str: any of {'1sigma', '2sigma', '3sigma', '4sigma', '5sigma'}
Plot within mean +/- #sigma of posterior.
* if float: Plot within the symmetric confidence interval
`(1-q, q)` or `(q, 1-q)`.
* if tuple: Plot within the (possibly asymmetric) confidence
interval `q`.
optional, (Default: '5sigma')
Returns
-------
fig: matplotlib.figure.Figure
New or original (if supplied) figure object
axes: pandas.DataFrame or pandas.Series of matplotlib.axes.Axes
Pandas array of axes objects
"""
self._set_automatic_limits()
plot_type = kwargs.pop('plot_type', 'kde')
do_1d_plot = paramname_y is None or paramname_x == paramname_y
kwargs['label'] = kwargs.get('label', self.label)
ncompress = kwargs.pop('ncompress', None)
if do_1d_plot:
if paramname_x in self and plot_type is not None:
xmin, xmax = self._limits(paramname_x)
kwargs['xmin'] = kwargs.get('xmin', xmin)
kwargs['xmax'] = kwargs.get('xmax', xmax)
if plot_type == 'kde':
if ncompress is None:
ncompress = 1000
return kde_plot_1d(ax,
self[paramname_x],
weights=self.weights,
ncompress=ncompress,
*args,
**kwargs)
elif plot_type == 'fastkde':
x = self[paramname_x].compress(ncompress)
return fastkde_plot_1d(ax, x, *args, **kwargs)
elif plot_type == 'hist':
return hist_plot_1d(ax,
self[paramname_x],
weights=self.weights,
*args,
**kwargs)
elif plot_type == 'astropyhist':
x = self[paramname_x].compress(ncompress)
return hist_plot_1d(ax,
x,
plotter='astropyhist',
*args,
**kwargs)
else:
raise NotImplementedError("plot_type is '%s', but must be"
" one of {'kde', 'fastkde', "
"'hist', 'astropyhist'}." %
plot_type)
else:
ax.plot([], [])
else:
if (paramname_x in self and paramname_y in self
and plot_type is not None):
xmin, xmax = self._limits(paramname_x)
kwargs['xmin'] = kwargs.get('xmin', xmin)
kwargs['xmax'] = kwargs.get('xmax', xmax)
ymin, ymax = self._limits(paramname_y)
kwargs['ymin'] = kwargs.get('ymin', ymin)
kwargs['ymax'] = kwargs.get('ymax', ymax)
if plot_type == 'kde':
if ncompress is None:
ncompress = 1000
x = self[paramname_x]
y = self[paramname_y]
return kde_contour_plot_2d(ax,
x,
y,
weights=self.weights,
ncompress=ncompress,
*args,
**kwargs)
elif plot_type == 'fastkde':
x = self[paramname_x].compress(ncompress)
y = self[paramname_y].compress(ncompress)
return fastkde_contour_plot_2d(ax, x, y, *args, **kwargs)
elif plot_type == 'scatter':
if ncompress is None:
ncompress = 500
x = self[paramname_x].compress(ncompress)
y = self[paramname_y].compress(ncompress)
return scatter_plot_2d(ax, x, y, *args, **kwargs)
elif plot_type == 'hist':
x = self[paramname_x]
y = self[paramname_y]
return hist_plot_2d(ax,
x,
y,
weights=self.weights,
*args,
**kwargs)
else:
raise NotImplementedError("plot_type is '%s', but must be"
"in {'kde', 'fastkde',"
"'scatter', 'hist'}." %
plot_type)
else:
ax.plot([], [])
def plot(self, ax, paramname_x, paramname_y=None, *args, **kwargs):
"""Interface for 2D and 1D plotting routines.
Produces a single 1D or 2D plot on an axis.
Parameters
----------
ax: matplotlib.axes.Axes
Axes to plot on
paramname_x: str
Choice of parameter to plot on x-coordinate from self.columns.
paramname_y: str
Choice of parameter to plot on y-coordinate from self.columns.
optional, if not provided, or the same as paramname_x, then 1D plot
produced.
plot_type: str
Must be in {'kde', 'scatter', 'hist', 'fastkde'} for 2D plots and
in {'kde', 'hist', 'fastkde', 'astropyhist'} for 1D plots.
optional, (Default: 'kde')
ncompress: int
Number of samples to use in plotting routines.
optional, Default dynamically chosen
Returns
-------
fig: matplotlib.figure.Figure
New or original (if supplied) figure object
axes: pandas.DataFrame or pandas.Series of matplotlib.axes.Axes
Pandas array of axes objects
"""
plot_type = kwargs.pop('plot_type', 'kde')
do_1d_plot = paramname_y is None or paramname_x == paramname_y
kwargs['label'] = kwargs.get('label', self.label)
ncompress = kwargs.pop('ncompress', None)
if do_1d_plot:
if paramname_x in self and plot_type is not None:
xmin, xmax = self._limits(paramname_x)
if plot_type == 'kde':
if ncompress is None:
ncompress = 1000
return kde_plot_1d(ax,
self[paramname_x],
weights=self.weight,
ncompress=ncompress,
xmin=xmin,
xmax=xmax,
*args,
**kwargs)
elif plot_type == 'fastkde':
x = self[paramname_x].compress(ncompress)
return fastkde_plot_1d(ax,
x,
xmin=xmin,
xmax=xmax,
*args,
**kwargs)
elif plot_type == 'hist':
return hist_plot_1d(ax,
self[paramname_x],
weights=self.weight,
xmin=xmin,
xmax=xmax,
*args,
**kwargs)
elif plot_type == 'astropyhist':
x = self[paramname_x].compress(ncompress)
return hist_plot_1d(ax,
x,
plotter='astropyhist',
xmin=xmin,
xmax=xmax,
*args,
**kwargs)
else:
raise NotImplementedError("plot_type is '%s', but must be"
" one of {'kde', 'fastkde', "
"'hist', 'astropyhist'}." %
plot_type)
else:
ax.plot([], [])
else:
if (paramname_x in self and paramname_y in self
and plot_type is not None):
xmin, xmax = self._limits(paramname_x)
ymin, ymax = self._limits(paramname_y)
if plot_type == 'kde':
if ncompress is None:
ncompress = 1000
x = self[paramname_x]
y = self[paramname_y]
return kde_contour_plot_2d(ax,
x,
y,
weights=self.weight,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
ncompress=ncompress,
*args,
**kwargs)
elif plot_type == 'fastkde':
x = self[paramname_x].compress(ncompress)
y = self[paramname_y].compress(ncompress)
return fastkde_contour_plot_2d(ax,
x,
y,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
*args,
**kwargs)
elif plot_type == 'scatter':
if ncompress is None:
ncompress = 500
x = self[paramname_x].compress(ncompress)
y = self[paramname_y].compress(ncompress)
return scatter_plot_2d(ax,
x,
y,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
*args,
**kwargs)
elif plot_type == 'hist':
x = self[paramname_x]
y = self[paramname_y]
return hist_plot_2d(ax,
x,
y,
weights=self.weight,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
*args,
**kwargs)
else:
raise NotImplementedError("plot_type is '%s', but must be"
"in {'kde', 'fastkde',"
"'scatter', 'hist'}." %
plot_type)
else:
ax.plot([], [])