def test_plot_helpers(self):
from pygsti.report import plothelpers as ph
self.assertEqual(ph._eformat(0.1, "compacthp"),".10")
self.assertEqual(ph._eformat(1.0, "compacthp"),"1.0")
self.assertEqual(ph._eformat(5.2, "compacthp"),"5.2")
self.assertEqual(ph._eformat(63.2, "compacthp"),"63")
self.assertEqual(ph._eformat(2.1e-4, "compacthp"),"2m4")
self.assertEqual(ph._eformat(2.1e+4, "compacthp"),"2e4")
self.assertEqual(ph._eformat(-3.2e-4, "compacthp"),"-3m4")
self.assertEqual(ph._eformat(-3.2e+4, "compacthp"),"-3e4")
self.assertEqual(ph._eformat(4e+40, "compacthp"),"*40")
self.assertEqual(ph._eformat(6e+102, "compacthp"),"B")
self.assertEqual(ph._eformat(10, "compacthp"),"10")
self.assertEqual(ph._eformat(1.234, 2),"1.23")
self.assertEqual(ph._eformat(-1.234, 2),"-1.23")
self.assertEqual(ph._eformat(-1.234, "foobar"), "-1.234") #just prints in general format
subMxs = np.nan * np.ones((3,3,2,2),'d') # a 3x3 grid of 2x2 matrices
nBoxes, dof_per_box = ph._compute_num_boxes_dof(subMxs, sumUp=True, element_dof=1)
self.assertEqual(nBoxes, 0)
self.assertEqual(dof_per_box, None)
subMxs[0,0,1,1] = 1.0 # matrix [0,0] has a single non-Nan element
subMxs[0,2,0,1] = 1.0
subMxs[0,2,1,1] = 1.0 # matrix [0,2] has a two non-Nan elements
# now the mxs that aren't all-NaNs don't all have the same # of Nans => warning
#self.assertWarns(ph._compute_num_boxes_dof, subMxs, sumUp=True, element_dof=1)
ph._compute_num_boxes_dof( subMxs, sumUp=True, element_dof=1) # Python2.7 doesn't always warn...
def plotly_to_matplotlib(pygsti_fig,
save_to=None,
fontsize=12,
prec='compacthp',
box_labels_font_size=6):
"""
Convert a pygsti (plotly) figure to a matplotlib figure.
Parameters
----------
pygsti_fig : ReportFigure
A pyGSTi figure.
save_to : str
Output filename. Extension determines type. If None, then the
matplotlib figure is returned instead of saved.
fontsize : int, optional
Base fontsize to use for converted figure.
prec : int or {"compact","compacth"}
Digits of precision to include in labels.
box_labels_font_size : int, optional
The size for labels on the boxes. If 0 then no labels are
put on the boxes
Returns
-------
matplotlib.Figure
Matplotlib figure, unless save_to is not None, in which case
the figure is closed and None is returned.
"""
numMPLFigs = len(_plt.get_fignums())
fig = pygsti_fig.plotlyfig
data_trace_list = fig['data']
if 'special' in pygsti_fig.metadata:
if pygsti_fig.metadata['special'] == "keyplot":
return special_keyplot(pygsti_fig, save_to, fontsize)
else:
raise ValueError("Invalid `special` label: %s" %
pygsti_fig.metadata['special'])
#if axes is None:
mpl_fig, axes = _plt.subplots() # create a new figure if no axes are given
layout = fig['layout']
h, w = layout['height'], layout['width']
# todo: get margins and subtract from h,w
if mpl_fig is not None and w is not None and h is not None:
mpl_size = w / 100.0, h / 100.0 # heusistic
mpl_fig.set_size_inches(*mpl_size) # was 12,8 for "super" color plot
pygsti_fig.metadata[
'mpl_fig_size'] = mpl_size # record for later use by rendering commands
def get(obj, x, default):
""" Needed b/c in plotly v3 layout no longer is a dict """
try:
ret = obj[x]
return ret if (ret is not None) else default
except KeyError:
return default
raise ValueError(
"Non-KeyError raised when trying to access a plotly hierarchy object."
)
xaxis, yaxis = layout['xaxis'], layout['yaxis']
#annotations = get(layout,'annotations',[])
title = get(layout, 'title', None)
shapes = get(layout, 'shapes', []) # assume only shapes are grid lines
bargap = get(layout, 'bargap', 0)
xlabel = get(xaxis, 'title', None)
ylabel = get(yaxis, 'title', None)
xlabels = get(xaxis, 'ticktext', None)
ylabels = get(yaxis, 'ticktext', None)
xtickvals = get(xaxis, 'tickvals', None)
ytickvals = get(yaxis, 'tickvals', None)
xaxistype = get(xaxis, 'type', None)
yaxistype = get(yaxis, 'type', None)
xaxisside = get(xaxis, 'side', 'bottom')
yaxisside = get(yaxis, 'side', 'left')
xtickangle = get(xaxis, 'tickangle', 0)
xlim = get(xaxis, 'range', None)
ylim = get(yaxis, 'range', None)
if xaxisside == "top":
axes.xaxis.set_label_position('top')
axes.xaxis.tick_top()
#axes.yaxis.set_ticks_position('both')
if yaxisside == "right":
axes.yaxis.set_label_position('right')
axes.yaxis.tick_right()
#axes.yaxis.set_ticks_position('both')
if title is not None:
# Sometimes Title object still is nested
title_text = title if isinstance(title, str) else get(
title, 'text', '')
if xaxisside == "top":
axes.set_title(mpl_process_lbl(title_text), fontsize=fontsize,
y=4) # push title up higher
axes.set_title(mpl_process_lbl(title_text), fontsize=fontsize)
if xlabel is not None:
xlabel_text = xlabel if isinstance(xlabel, str) else get(
xlabel, 'text', '')
axes.set_xlabel(mpl_process_lbl(xlabel_text), fontsize=fontsize)
if ylabel is not None:
ylabel_text = ylabel if isinstance(ylabel, str) else get(
ylabel, 'text', '')
axes.set_ylabel(mpl_process_lbl(ylabel_text), fontsize=fontsize)
if xtickvals is not None:
axes.set_xticks(xtickvals, minor=False)
if ytickvals is not None:
axes.set_yticks(ytickvals, minor=False)
if xlabels is not None:
axes.set_xticklabels(mpl_process_lbls(xlabels),
rotation=0,
fontsize=(fontsize - 2))
if ylabels is not None:
axes.set_yticklabels(mpl_process_lbls(ylabels),
fontsize=(fontsize - 2))
if xtickangle != 0:
_plt.xticks(
rotation=-xtickangle
) # minus b/c ploty & matplotlib have different sign conventions
if xaxistype == 'log':
axes.set_xscale("log")
if yaxistype == 'log':
axes.set_yscale("log")
if xlim is not None:
if xaxistype == 'log': # plotly's limits are already log10'd in this case
xlim = 10.0**xlim[0], 10.0**xlim[1] # but matplotlib's aren't
axes.set_xlim(xlim)
if ylim is not None:
if yaxistype == 'log': # plotly's limits are already log10'd in this case
ylim = 10.0**ylim[0], 10.0**ylim[1] # but matplotlib's aren't
axes.set_ylim(ylim)
#figure out barwidth and offsets for bar plots
num_bars = sum([get(d, 'type', '') == 'bar' for d in data_trace_list])
currentBarOffset = 0
barWidth = (1.0 - bargap) / num_bars if num_bars > 0 else 1.0
#process traces
handles = []
labels = [] # for the legend
boxes = [] # for violins
for traceDict in data_trace_list:
typ = get(traceDict, 'type', 'unknown')
name = get(traceDict, 'name', None)
showlegend = get(traceDict, 'showlegend', True)
if typ == "heatmap":
#colorscale = get(traceDict,'colorscale','unknown')
# traceDict['z'] is *normalized* already - maybe would work here but not for box value labels
plt_data = pygsti_fig.metadata['plt_data']
show_colorscale = get(traceDict, 'showscale', True)
mpl_size = (plt_data.shape[1] * 0.5, plt_data.shape[0] * 0.5)
mpl_fig.set_size_inches(*mpl_size)
#pygsti_fig.metadata['mpl_fig_size'] = mpl_size #record for later use by rendering commands
colormap = pygsti_fig.colormap
assert (colormap
is not None), 'Must separately specify a colormap...'
norm, cmap = colormap.create_matplotlib_norm_and_cmap()
masked_data = _np.ma.array(plt_data, mask=_np.isnan(plt_data))
heatmap = axes.pcolormesh(masked_data, cmap=cmap, norm=norm)
axes.set_xlim(0, plt_data.shape[1])
axes.set_ylim(0, plt_data.shape[0])
if xtickvals is not None:
xtics = _np.array(
xtickvals) + 0.5 # _np.arange(plt_data.shape[1])+0.5
axes.set_xticks(xtics, minor=False)
if ytickvals is not None:
ytics = _np.array(
ytickvals) + 0.5 # _np.arange(plt_data.shape[0])+0.5
axes.set_yticks(ytics, minor=False)
grid = bool(len(shapes) > 1)
if grid:
def _get_minor_tics(t):
return [(t[i] + t[i + 1]) / 2.0 for i in range(len(t) - 1)]
axes.set_xticks(_get_minor_tics(xtics), minor=True)
axes.set_yticks(_get_minor_tics(ytics), minor=True)
axes.grid(which='minor',
axis='both',
linestyle='-',
linewidth=2)
off = False # Matplotlib used to allow 'off', but now False should be used
if xlabels is None and ylabels is None:
axes.tick_params(labelcolor='w',
top=off,
bottom=off,
left=off,
right=off) # white tics
else:
axes.tick_params(top=off, bottom=off, left=off, right=off)
#print("DB ann = ", len(annotations))
#boxLabels = bool( len(annotations) >= 1 ) #TODO: why not plt_data.size instead of 1?
#boxLabels = True # maybe should always be true?
if box_labels_font_size > 0:
# Write values on colored squares
for y in range(plt_data.shape[0]):
for x in range(plt_data.shape[1]):
if _np.isnan(plt_data[y, x]): continue
assert (_np.isfinite(plt_data[y, x])
), "%s is not finite!" % str(plt_data[y, x])
axes.text(
x + 0.5,
y + 0.5,
mpl_process_lbl(_eformat(plt_data[y, x], prec),
math=True),
horizontalalignment='center',
verticalalignment='center',
color=mpl_besttxtcolor(plt_data[y, x], cmap, norm),
fontsize=box_labels_font_size)
if show_colorscale:
cbar = _plt.colorbar(heatmap)
cbar.ax.tick_params(labelsize=(fontsize - 2))
elif typ == "scatter":
mode = get(traceDict, 'mode', 'lines')
marker = get(traceDict, 'marker', None)
line = get(traceDict, 'line', None)
if marker and (line is None):
line = marker['line'] # 2nd attempt to get line props
if marker:
color = get(marker, 'color', None)
if line and (color is None):
color = get(line, 'color', None)
if color is None:
color = 'rgb(0,0,0)'
if isinstance(color, tuple):
color = [mpl_color(c) for c in color]
else:
color = mpl_color(color)
linewidth = float(line['width']) if (
line and get(line, 'width', None) is not None) else 1.0
x = y = None
if 'x' in traceDict and 'y' in traceDict:
x = traceDict['x']
y = traceDict['y']
elif 'r' in traceDict and 't' in traceDict:
x = traceDict['r']
y = traceDict['t']
assert (x is not None and y
is not None), "x and y both None in trace: %s" % traceDict
if mode == 'lines':
if isinstance(color, list):
raise ValueError(
'List of colors incompatible with lines mode')
lines = _plt.plot(x,
y,
linestyle='-',
marker=None,
color=color,
linewidth=linewidth)
elif mode == 'markers':
lines = _plt.scatter(x, y, marker=".", color=color)
elif mode == 'lines+markers':
if isinstance(color, list):
# List of colors only works for markers with scatter, have default black line
lines = _plt.plot(x,
y,
linestyle='-',
color=(0, 0, 0),
linewidth=linewidth)
_plt.scatter(x, y, marker='.', color=color)
else:
lines = _plt.plot(x,
y,
linestyle='-',
marker='.',
color=color,
linewidth=linewidth)
else:
raise ValueError("Unknown mode: %s" % mode)
if showlegend and name:
handles.append(lines[0])
labels.append(name)
elif typ == "scattergl": # currently used only for colored points...
x = traceDict['x']
y = traceDict['y']
assert (x is not None and y
is not None), "x and y both None in trace: %s" % traceDict
colormap = pygsti_fig.colormap
if colormap:
norm, cmap = colormap.create_matplotlib_norm_and_cmap()
s = _plt.scatter(x, y, c=y, s=50, cmap=cmap, norm=norm)
else:
s = _plt.scatter(x, y, c=y, s=50, cmap='gray')
if showlegend and name:
handles.append(s)
labels.append(name)
elif typ == "bar":
xlabels = [str(xl) for xl in traceDict['x']
] # x "values" are actually bar labels in plotly
#always grey=pos, red=neg type of bar plot for now (since that's all pygsti uses)
y = _np.asarray(traceDict['y'])
if 'plt_yerr' in pygsti_fig.metadata:
yerr = pygsti_fig.metadata['plt_yerr']
else:
yerr = None
# actual x values are just the integers + offset
x = _np.arange(y.size) + currentBarOffset
currentBarOffset += barWidth # so next bar trace will be offset correctly
marker = get(traceDict, 'marker', None)
if marker and ('color' in marker):
if isinstance(marker['color'], str):
color = mpl_color(marker['color'])
elif isinstance(marker['color'], list):
color = [mpl_color(c) for c in marker['color']
] # b/c axes.bar can take a list of colors
else:
color = "gray"
if yerr is None:
axes.bar(x, y, barWidth, color=color)
else:
axes.bar(x, y, barWidth, color=color, yerr=yerr.flatten().real)
if xtickvals is not None:
xtics = _np.array(
xtickvals) + 0.5 # _np.arange(plt_data.shape[1])+0.5
else:
xtics = x
axes.set_xticks(xtics, minor=False)
axes.set_xticklabels(mpl_process_lbls(xlabels),
rotation=0,
fontsize=(fontsize - 4))
elif typ == "histogram":
#histnorm = get(traceDict,'histnorm',None)
marker = get(traceDict, 'marker', None)
color = mpl_color(marker['color'] if marker
and isinstance(marker['color'], str) else "gray")
xbins = traceDict['xbins']
histdata = traceDict['x']
if abs(xbins['size']) < 1e-6:
histBins = 1
else:
histBins = int(
round((xbins['end'] - xbins['start']) / xbins['size']))
histdata_finite = _np.take(
histdata, _np.where(_np.isfinite(histdata)))[
0] # take gives back (1,N) shaped array (why?)
if yaxistype == 'log':
if len(histdata_finite) == 0:
axes.set_yscale(
"linear"
) # no data, and will get an error with log-scale, so switch to linear
#histMin = min( histdata_finite ) if cmapFactory.vmin is None else cmapFactory.vmin
#histMax = max( histdata_finite ) if cmapFactory.vmax is None else cmapFactory.vmax
#_plt.hist(_np.clip(histdata_finite,histMin,histMax), histBins,
# range=[histMin, histMax], facecolor='gray', align='mid')
_, _, patches = _plt.hist(histdata_finite,
histBins,
facecolor=color,
align='mid')
#If we've been given an array of colors
if marker and ('color' in marker) and isinstance(
marker['color'], list):
for p, c in zip(patches, marker['color']):
_plt.setp(p, 'facecolor', mpl_color(c))
elif typ == "box":
boxes.append(traceDict)
if len(boxes) > 0:
_plt.violinplot([box['y'] for box in boxes],
[box['x0'] for box in boxes],
points=10,
widths=1.,
showmeans=False,
showextrema=False,
showmedians=False)
# above kwargs taken from Tim's original RB plot - we could set some of
# these from boxes[0]'s properties like 'boxmean' (a boolean) FUTURE?
extraartists = [axes]
if len(handles) > 0:
lgd = _plt.legend(handles,
labels,
bbox_to_anchor=(1.01, 1.0),
borderaxespad=0.,
loc="upper left")
extraartists.append(lgd)
if save_to:
_gc.collect(
) # too many open files (b/c matplotlib doesn't close everything) can cause the below to fail
_plt.savefig(save_to,
bbox_extra_artists=extraartists,
bbox_inches='tight') # need extra artists otherwise
#axis labels get clipped
_plt.cla()
_plt.close(mpl_fig)
del mpl_fig
_gc.collect() # again, to be safe...
if len(_plt.get_fignums()) != numMPLFigs:
raise ValueError(
"WARNING: MORE FIGURES OPEN NOW (%d) THAN WHEN WE STARTED %d)!!"
% (len(_plt.get_fignums()), numMPLFigs))
return None # figure is closed!
else:
return mpl_fig