def test_nest_level():
assert (nest_level(0) == 0)
assert (nest_level([]) == 1)
assert (nest_level(['a']) == 1)
assert (nest_level(['a', 'b']) == 1)
assert (nest_level([['a'], 'b']) == 2)
assert (nest_level(['a', ['b']]) == 2)
assert (nest_level([['a'], ['b']]) == 2)
def make_2d_axes(params, **kwargs):
"""Create a set of axes for plotting 2D marginalised posteriors.
Parameters
----------
params: lists of parameters
Can be either:
* list(str) if the x and y axes are the same
* [list(str),list(str)] if the x and y axes are different
Strings indicate the names of the parameters
tex: dict(str:str), optional
Dictionary mapping params to tex plot labels.
Default: params
upper, lower, diagonal: logical, optional
Whether to create 2D marginalised plots above or below the
diagonal, or to create a 1D marginalised plot on the diagonal.
Default: True
fig: matplotlib.figure.Figure, optional
Figure to plot on.
Default: matplotlib.pyplot.figure()
subplot_spec: matplotlib.gridspec.GridSpec, optional
gridspec to plot array as part of a subfigure.
Default: None
Returns
-------
fig: matplotlib.figure.Figure
New or original (if supplied) figure object
axes: pandas.DataFrame(matplotlib.axes.Axes)
Pandas array of axes objects
"""
if nest_level(params) == 2:
xparams, yparams = params
else:
xparams = yparams = params
upper = kwargs.pop('upper', True)
lower = kwargs.pop('lower', True)
diagonal = kwargs.pop('diagonal', True)
axes = pandas.DataFrame(index=numpy.atleast_1d(yparams),
columns=numpy.atleast_1d(xparams),
dtype=object)
axes[:][:] = None
all_params = list(axes.columns) + list(axes.index)
for j, y in enumerate(axes.index):
for i, x in enumerate(axes.columns):
if all_params.index(x) < all_params.index(y):
if lower:
axes[x][y] = -1
elif all_params.index(x) > all_params.index(y):
if upper:
axes[x][y] = +1
elif diagonal:
axes[x][y] = 0
axes.dropna(axis=0, how='all', inplace=True)
axes.dropna(axis=1, how='all', inplace=True)
tex = kwargs.pop('tex', {})
tex = {p: tex[p] if p in tex else p for p in all_params}
fig = kwargs.pop('fig') if 'fig' in kwargs else plt.figure()
if 'subplot_spec' in kwargs:
grid = SGS(*axes.shape,
hspace=0,
wspace=0,
subplot_spec=kwargs.pop('subplot_spec'))
else:
grid = GS(*axes.shape, hspace=0, wspace=0)
if kwargs:
raise TypeError('Unexpected **kwargs: %r' % kwargs)
if axes.size == 0:
return fig, axes
position = axes.copy()
axes[:][:] = None
for j, y in enumerate(axes.index):
for i, x in enumerate(axes.columns):
if position[x][y] is not None:
sx = list(axes[x].dropna())
sx = sx[0] if sx else None
sy = list(axes.T[y].dropna())
sy = sy[0] if sy else None
axes[x][y] = fig.add_subplot(grid[j, i], sharex=sx, sharey=sy)
if position[x][y] == 0:
axes[x][y].twin = axes[x][y].twinx()
axes[x][y].twin.set_yticks([])
axes[x][y].twin.set_ylim(0, 1.1)
axes[x][y].set_zorder(axes[x][y].twin.get_zorder() + 1)
axes[x][y].lines = axes[x][y].twin.lines
axes[x][y].patches = axes[x][y].twin.patches
axes[x][y].collections = axes[x][y].twin.collections
axes[x][y].containers = axes[x][y].twin.containers
make_diagonal(axes[x][y])
axes[x][y].position = 'diagonal'
elif position[x][y] == 1:
axes[x][y].position = 'upper'
elif position[x][y] == -1:
axes[x][y].position = 'lower'
for y, ax in axes.bfill(axis=1).iloc[:, 0].dropna().iteritems():
ax.set_ylabel(tex[y])
for x, ax in axes.ffill(axis=0).iloc[-1, :].dropna().iteritems():
ax.set_xlabel(tex[x])
for y, ax in axes.iterrows():
ax_ = ax.dropna()
if len(ax_):
for a in ax_[1:]:
a.tick_params('y', left=False, labelleft=False)
for x, ax in axes.iteritems():
ax_ = ax.dropna()
if len(ax_):
for a in ax_[:-1]:
a.tick_params('x', bottom=False, labelbottom=False)
for y, ax in axes.bfill(axis=1).iloc[:, 0].dropna().iteritems():
ax.yaxis.set_major_locator(MaxNLocator(3, prune='both'))
for x, ax in axes.ffill(axis=0).iloc[-1, :].dropna().iteritems():
ax.xaxis.set_major_locator(MaxNLocator(3, prune='both'))
return fig, axes
def make_2d_axes(params, **kwargs):
"""Create a set of axes for plotting 2D marginalised posteriors.
Parameters
----------
params: lists of parameters
Can be either:
* list(str) if the x and y axes are the same
* [list(str),list(str)] if the x and y axes are different
Strings indicate the names of the parameters
tex: dict(str:str), optional
Dictionary mapping params to tex plot labels.
Default: params
upper, lower, diagonal: logical, optional
Whether to create 2D marginalised plots above or below the
diagonal, or to create a 1D marginalised plot on the diagonal.
Default: True
fig: matplotlib.figure.Figure, optional
Figure to plot on.
Default: matplotlib.pyplot.figure()
ticks: str
If 'outer', plot ticks only on the very left and very bottom.
If 'inner', plot ticks also in inner subplots.
If None, plot no ticks at all.
Default: 'outer'
subplot_spec: matplotlib.gridspec.GridSpec, optional
gridspec to plot array as part of a subfigure.
Default: None
Returns
-------
fig: matplotlib.figure.Figure
New or original (if supplied) figure object
axes: pandas.DataFrame(matplotlib.axes.Axes)
Pandas array of axes objects
"""
if nest_level(params) == 2:
xparams, yparams = params
else:
xparams = yparams = params
ticks = kwargs.pop('ticks', 'outer')
upper = kwargs.pop('upper', True)
lower = kwargs.pop('lower', True)
diagonal = kwargs.pop('diagonal', True)
axes = AxesDataFrame(index=np.atleast_1d(yparams),
columns=np.atleast_1d(xparams),
dtype=object)
axes[:][:] = None
all_params = list(axes.columns) + list(axes.index)
for j, y in enumerate(axes.index):
for i, x in enumerate(axes.columns):
if all_params.index(x) < all_params.index(y):
if lower:
axes[x][y] = -1
elif all_params.index(x) > all_params.index(y):
if upper:
axes[x][y] = +1
elif diagonal:
axes[x][y] = 0
axes.dropna(axis=0, how='all', inplace=True)
axes.dropna(axis=1, how='all', inplace=True)
tex = kwargs.pop('tex', {})
tex = {p: tex[p] if p in tex else p for p in all_params}
fig = kwargs.pop('fig') if 'fig' in kwargs else plt.figure()
spec = kwargs.pop('subplot_spec', None)
if axes.shape[0] != 0 and axes.shape[1] != 0:
if spec is not None:
grid = SGS(*axes.shape, hspace=0, wspace=0, subplot_spec=spec)
else:
grid = GS(*axes.shape, hspace=0, wspace=0)
if kwargs:
raise TypeError('Unexpected **kwargs: %r' % kwargs)
if axes.size == 0:
return fig, axes
position = axes.copy()
axes[:][:] = None
for j, y in enumerate(axes.index[::-1]):
for i, x in enumerate(axes.columns):
if position[x][y] is not None:
sx = list(axes[x].dropna())
sx = sx[0] if sx else None
sy = list(axes.T[y].dropna())
sy = sy[0] if sy else None
axes[x][y] = fig.add_subplot(grid[axes.index.size-1-j, i],
sharex=sx, sharey=sy)
if position[x][y] == 0:
axes[x][y].twin = axes[x][y].twinx()
axes[x][y].twin.set_yticks([])
axes[x][y].twin.set_ylim(0, 1.1)
axes[x][y].set_zorder(axes[x][y].twin.get_zorder() + 1)
axes[x][y].lines = axes[x][y].twin.lines
axes[x][y].patches = axes[x][y].twin.patches
axes[x][y].collections = axes[x][y].twin.collections
axes[x][y].containers = axes[x][y].twin.containers
make_diagonal(axes[x][y])
axes[x][y].position = 'diagonal'
axes[x][y].twin.xaxis.set_major_locator(
MaxNLocator(3, prune='both'))
else:
if position[x][y] == 1:
axes[x][y].position = 'upper'
elif position[x][y] == -1:
axes[x][y].position = 'lower'
axes[x][y].yaxis.set_major_locator(
MaxNLocator(3, prune='both'))
axes[x][y].xaxis.set_major_locator(
MaxNLocator(3, prune='both'))
for y, ax in axes.bfill(axis=1).iloc[:, 0].dropna().iteritems():
ax.set_ylabel(tex[y])
for x, ax in axes.ffill(axis=0).iloc[-1, :].dropna().iteritems():
ax.set_xlabel(tex[x])
# left and right ticks and labels
for y, ax in axes.iterrows():
ax_ = ax.dropna()
if len(ax_) and ticks == 'inner':
for i, a in enumerate(ax_):
if i == 0: # first column
if a.position == 'diagonal' and len(ax_) == 1:
a.tick_params('y', left=False, labelleft=False)
else:
a.tick_params('y', left=True, labelleft=True)
elif a.position == 'diagonal': # not first column
tl = a.yaxis.majorTicks[0].tick1line.get_markersize()
a.tick_params('y', direction='out', length=tl/2,
left=True, labelleft=False)
else: # not diagonal and not first column
a.tick_params('y', direction='inout',
left=True, labelleft=False)
elif len(ax_) and ticks == 'outer': # no inner ticks
for a in ax_[1:]:
a.tick_params('y', left=False, labelleft=False)
elif len(ax_) and ticks is None: # no ticks at all
for a in ax_:
a.tick_params('y', left=False, right=False,
labelleft=False, labelright=False)
else:
raise ValueError(
"ticks=%s was requested, but ticks can only be one of "
"['outer', 'inner', None]." % ticks)
# bottom and top ticks and labels
for x, ax in axes.iteritems():
ax_ = ax.dropna()
if len(ax_):
if ticks == 'inner':
for i, a in enumerate(ax_):
if i == len(ax_) - 1: # bottom row
a.tick_params('x', bottom=True, labelbottom=True)
else: # not bottom row
a.tick_params('x', direction='inout',
bottom=True, labelbottom=False)
if a.position == 'diagonal':
a.twin.tick_params('x', direction='inout',
bottom=True, labelbottom=False)
elif ticks == 'outer': # no inner ticks
for a in ax_[:-1]:
a.tick_params('x', bottom=False, labelbottom=False)
elif ticks is None: # no ticks at all
for a in ax_:
a.tick_params('x', bottom=False, top=False,
labelbottom=False, labeltop=False)
else:
raise ValueError(
"ticks=%s was requested, but ticks can only be one of "
"['outer', 'inner', None]." % ticks)
return fig, axes