def plot_table(ax, data, float_format='{:.2f}', columns=None, bbox=None, cell_font_size=6):
if columns is not None:
if type(columns) is dict:
data = data[columns.keys()]
data = data.rename(columns)
else:
data = data[columns]
if bbox is None:
bbox = [0, 0, 1, 1]
ax.set_axis_off()
table = Table(ax, bbox=bbox)
num_rows, num_cols = data.shape
width = 1.0 / num_cols
#height = 1.0 / num_rows
height = table._approx_text_height()
# Add cells
for (i,j), val in np.ndenumerate(data):
val = float_format.format(val)
table.add_cell(i, j, width, height, text=val, loc='center')
cells = table.get_celld()
for index, val in np.ndenumerate(data):
cells[index].set_fontsize(cell_font_size)
# Row Labels...
for i, label in enumerate(data.index):
table.add_cell(i, -1, width, height, text=label, loc='right', edgecolor='none', facecolor='none')
# Column Labels...
for j, label in enumerate(data.columns):
table.add_cell(-1, j, width, height/2, text=label, loc='center', edgecolor='none', facecolor='none')
ax.add_table(table)
table.set_fontsize(cell_font_size)
return ax
def plot(self, experiment, **kwargs):
"""Plot a table"""
if not experiment:
raise util.CytoflowViewError("No experiment specified")
if not self.channel or self.channel not in experiment.data:
raise util.CytoflowViewError("Must set a channel")
if not (self.row_facet or self.column_facet):
raise util.CytoflowViewError("Must set at least one of row_facet "
"or column_facet")
if self.subrow_facet and not self.row_facet:
raise util.CytoflowViewError("Must set row_facet before using "
"subrow_facet")
if self.subcolumn_facet and not self.column_facet:
raise util.CytoflowViewError("Must set column_facet before using "
"subcolumn_facet")
if self.row_facet and self.row_facet not in experiment.conditions:
raise util.CytoflowViewError("Row facet {0} not in the experiment"
.format(self.row_facet))
if self.subrow_facet and self.subrow_facet not in experiment.conditions:
raise util.CytoflowViewError("Subrow facet {0} not in the experiment"
.format(self.subrow_facet))
if self.column_facet and self.column_facet not in experiment.conditions:
raise util.CytoflowViewError("Column facet {0} not in the experiment"
.format(self.column_facet))
if self.subcolumn_facet and self.subcolumn_facet not in experiment.conditions:
raise util.CytoflowViewError("Subcolumn facet {0} not in the experiment"
.format(self.subcolumn_facet))
if not self.function:
raise util.CytoflowViewError("Summary function isn't set")
row_groups = np.sort(pd.unique(experiment[self.row_facet])) \
if self.row_facet else [None]
subrow_groups = np.sort(pd.unique(experiment[self.subrow_facet])) \
if self.subrow_facet else [None]
col_groups = np.sort(pd.unique(experiment[self.column_facet])) \
if self.column_facet else [None]
subcol_groups = np.sort(pd.unique(experiment[self.subcolumn_facet])) \
if self.subcolumn_facet else [None]
if self.subset:
try:
data = experiment.query(self.subset).data.reset_index()
except:
raise util.CytoflowViewError("Subset string '{0}' isn't valid"
.format(self.subset))
if len(data.index) == 0:
raise util.CytoflowViewError("Subset string '{0}' returned no events"
.format(self.subset))
else:
data = experiment.data
group_vars = []
if self.row_facet: group_vars.append(self.row_facet)
if self.subrow_facet: group_vars.append(self.subrow_facet)
if self.column_facet: group_vars.append(self.column_facet)
if self.subcolumn_facet: group_vars.append(self.subcolumn_facet)
agg = data.groupby(by = group_vars)[self.channel].aggregate(self.function)
# agg is a multi-index series; we can get a particular value from it
# with get(idx1, idx2...)
row_offset = (self.column_facet != "") + (self.subcolumn_facet != "")
col_offset = (self.row_facet != "") + (self.subrow_facet != "")
num_cols = len(col_groups) * len(subcol_groups) + col_offset
fig = plt.figure()
ax = fig.add_subplot(111)
# hide the plot axes that matplotlib tries to make
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
for sp in ax.spines.itervalues():
sp.set_color('w')
sp.set_zorder(0)
loc = 'best'
bbox = None
t = Table(ax, loc, bbox, **kwargs)
width = [1.0 / num_cols] * num_cols
height = t._approx_text_height() * 1.8
# make the main table
for (ri, r) in enumerate(row_groups):
for (rri, rr) in enumerate(subrow_groups):
for (ci, c) in enumerate(col_groups):
for (cci, cc) in enumerate(subcol_groups):
row_idx = ri * len(subrow_groups) + rri + row_offset
col_idx = ci * len(subcol_groups) + cci + col_offset
agg_idx = [x for x in (r, rr, c, cc) if x is not None]
agg_idx = tuple(agg_idx)
if len(agg_idx) == 1:
agg_idx = agg_idx[0]
t.add_cell(row_idx,
col_idx,
width = width[col_idx],
height = height,
text = agg.get(agg_idx))
# row headers
if self.row_facet:
for (ri, r) in enumerate(row_groups):
row_idx = ri * len(subrow_groups) + row_offset
text = "{0} = {1}".format(self.row_facet, r)
t.add_cell(row_idx,
0,
width = width[0],
height = height,
text = text)
# subrow headers
if self.subrow_facet:
for (ri, r) in enumerate(row_groups):
for (rri, rr) in enumerate(subrow_groups):
row_idx = ri * len(subrow_groups) + rri + row_offset
text = "{0} = {1}".format(self.subrow_facet, rr)
t.add_cell(row_idx,
1,
width = width[1],
height = height,
text = text)
# column headers
if self.column_facet:
for (ci, c) in enumerate(col_groups):
col_idx = ci * len(subcol_groups) + col_offset
text = "{0} = {1}".format(self.column_facet, c)
t.add_cell(0,
col_idx,
width = width[col_idx],
height = height,
text = text)
# column headers
if self.subcolumn_facet:
for (ci, c) in enumerate(col_groups):
for (cci, cc) in enumerate(subcol_groups):
col_idx = ci * len(subcol_groups) + cci + col_offset
text = "{0} = {1}".format(self.subcolumn_facet, c)
t.add_cell(1,
col_idx,
width = width[col_idx],
height = height,
text = text)
ax.add_table(t)
def label_manual(self,
display_elems,
figsize=(15, 7.5),
title="Sleep Stages"):
"""
Displays dialog for manual stage labeling
args:
displa_elems: list of lists of parameters used for display in format
((data_struct,{'parname1':parval1,'parname2':parval2,...}),...)
where data_struct is of class containing plot method (such
as EEGSpectralData) and 'parname1':parval1,... are
name-value pairs supplied to the function.
figsize: Size of the figure
block: Blocks code execution until label dialog is closed
"""
self.saving = False
sleep_stage_labels = [
'NREM3', 'NREM2', 'REM', 'NREM1', 'WAKE', 'MASK OFF', '???'
]
height_ratios = np.ones(len(display_elems)) * 3
height_ratios = np.append(height_ratios, 1)
fig = plt.figure(figsize=figsize)
gs = gridspec.GridSpec(len(display_elems) + 1,
1,
height_ratios=height_ratios)
ax_transforms = {}
def format_time_period(val):
m, s = divmod(int(round(val)), 60)
h, m = divmod(m, 60)
return "%d:%02d:%02d" % (h, m, s)
def reset_labels(event=None):
self.stage_times = [0]
self.stage_labels = [5]
if event is not None:
redraw_labels(event)
def reload_labels(event=None):
self.stage_times = np.append([], self.loaded_stage_times)
self.stage_labels = np.append([], self.loaded_stage_labels)
if self.stage_times[0] is None or self.stage_labels[
0] is None or self.stage_times.size != self.stage_labels.size:
print("data is bad, resetting labels")
reset_labels(event)
else:
print("stage_times size is " + str(self.stage_times.size))
print("stage_labels size is " + str(self.stage_labels.size))
if event is not None:
redraw_labels(event)
def redraw_labels(event=None):
line1.set_xdata(
np.concatenate((self.stage_times, [self.sleep_length])))
line1.set_ydata(
np.concatenate((self.stage_labels, [self.stage_labels[-1]])))
data = [0, 0, 0, 0, 0, 0, 0, 0]
for x in range(0, len(self.stage_times)):
data_offset = int(
len(sleep_stage_labels) - (self.stage_labels[x] + 1))
thisval = self.stage_times[x]
nextval = self.sleep_length if x is len(
self.stage_times) - 1 else self.stage_times[x + 1]
diffval = nextval - thisval
data[data_offset] = data[data_offset] + diffval
data[len(data) - 1] = self.sleep_length
for x in range(0, len(data)):
table.get_celld()[x, 1].get_text().set_text(
format_time_period(data[x]))
fig.canvas.draw()
def on_pick(figure, mouseevent):
#print(ax_transforms)
#print(mouseevent)
#print(figure)
#print(figure.get_axes())
if not mouseevent.inaxes in ax_transforms:
return False, {}
eegdata = ax_transforms[mouseevent.inaxes]
xmouse, ymouse = mouseevent.xdata, mouseevent.ydata
xmouse = eegdata.index_to_time(xmouse)
#print('x, y of mouse: {:.2f},{:.2f}'.format(xmouse, ymouse))
larger = [
x[0] for x in enumerate(self.stage_times) if x[1] > xmouse
]
if len(larger) > 0:
idx = larger[0]
if self.stage_labels[idx - 1] != self.stage_label:
self.stage_times[idx] = xmouse
self.stage_labels[idx] = self.stage_label
else:
self.stage_times = np.delete(self.stage_times, idx)
self.stage_labels = np.delete(self.stage_labels, idx)
else:
if self.stage_labels[-1] != self.stage_label:
self.stage_times = np.append(self.stage_times, xmouse)
self.stage_labels = np.append(self.stage_labels,
self.stage_label)
#print(stage_times)
#print(stage_labels)
for i in range(1, len(self.stage_labels) - 1):
if self.stage_labels[i] == self.stage_labels[i - 1]:
self.stage_labels = np.delete(self.stage_labels, i)
self.stage_times = np.delete(self.stage_times, i)
redraw_labels()
return True, {}
for did in range(len(display_elems)):
delem = display_elems[did]
ax = plt.subplot(gs[did])
ax_transforms[ax] = delem[0]
params = delem[1]
params['axes'] = ax
delem[0].plot(**params)
if did == 0:
plt.title(title)
#TODO
ax.set_picker(True)
fig.canvas.mpl_connect('pick_event', on_pick)
fig.set_picker(on_pick)
xtickspacing = 300
if len(np.arange(0, self.sleep_length, 300)) > 20:
xtickspacing = 600
if len(np.arange(0, self.sleep_length, 600)) > 20:
xtickspacing = 1200
if len(np.arange(0, self.sleep_length, 1200)) > 20:
xtickspacing = 1800
if len(np.arange(0, self.sleep_length, 1800)) > 20:
xtickspacing = 3600
xticks = np.arange(0, self.sleep_length, xtickspacing)
xticklabels = [str(int(i / 60)) for i in xticks]
reload_labels()
ax1 = plt.subplot(gs[-1])
line1, = ax1.plot(np.concatenate(
(self.stage_times, [self.sleep_length])),
np.concatenate(
(self.stage_labels, [self.stage_labels[-1]])),
drawstyle="steps-post")
ax1.set_xlabel("Time (min)")
ax1.set_ylabel("Sleep Stage")
ax1.set_xlim(0, self.sleep_length)
ax1.set_yticks(np.arange(7))
ax1.set_yticklabels(sleep_stage_labels)
ax1.set_xticks(xticks)
ax1.set_xticklabels(xticklabels)
self.stage_label = 6
rax = plt.axes([0.0, 0.0, 0.2, 0.16], facecolor='lightgoldenrodyellow')
radio = RadioButtons(rax, sleep_stage_labels[::-1], active=0)
def stagepicker(label):
self.stage_label = sleep_stage_labels.index(label)
#print(plot_eeg_log_hist.stage_label)
#fig.canvas.draw_idle()
def done(event):
self.saving = True
plt.close()
if self.loaded_stage_labels is not None:
axreload = plt.axes([0.7, 0.0, 0.1, 0.075])
breload = Button(axreload, 'Reload')
breload.on_clicked(reload_labels)
axreset = plt.axes([0.8, 0.0, 0.1, 0.075])
breset = Button(axreset, 'Reset')
breset.on_clicked(reset_labels)
axdone = plt.axes([0.9, 0.0, 0.1, 0.075])
bdone = Button(axdone, 'Save &\n Quit')
bdone.on_clicked(done)
radio.on_clicked(stagepicker)
tableax = plt.axes([0.2, 0.0, 0.25, 0.16], facecolor='lightblue')
tableax.get_yaxis().set_visible(False)
table = Table(tableax, bbox=[0, 0, 1, 1])
height = table._approx_text_height()
lidx = 0
for label in sleep_stage_labels[::-1]:
table.add_cell(lidx, 0, width=0.6, height=height, text=label)
table.add_cell(lidx, 1, width=0.4, height=height, text='')
lidx = lidx + 1
table.add_cell(lidx,
0,
width=0.6,
height=height,
text='Total Sleep Time')
table.add_cell(lidx, 1, width=0.4, height=height, text='')
tableax.add_table(table)
fig.canvas.callbacks.connect('pick_event', on_pick)
fig.canvas.set_window_title('EEG Spectrogram Analysis')
plt.subplots_adjust(left=0.15 if figsize[0] < 10 else 0.075,
bottom=0.2,
right=0.99,
top=0.97)
redraw_labels()
plt.show()
self.stage_times = np.array(self.stage_times)
self.stage_times = np.concatenate(
(self.stage_times, [self.sleep_length]))
self.stage_labels = np.concatenate((self.stage_labels, [6]))
def plot(self, experiment, plot_name = None, **kwargs):
"""Plot a table"""
if experiment is None:
raise util.CytoflowViewError('experiment', "No experiment specified")
if self.statistic not in experiment.statistics:
raise util.CytoflowViewError('statistic',
"Can't find the statistic {} in the experiment"
.format(self.statistic))
else:
stat = experiment.statistics[self.statistic]
data = pd.DataFrame(index = stat.index)
data[stat.name] = stat
if self.subset:
try:
data = data.query(self.subset)
except Exception as e:
raise util.CytoflowViewError('subset',
"Subset string '{0}' isn't valid"
.format(self.subset)) from e
if len(data) == 0:
raise util.CytoflowViewError('subset',
"Subset string '{0}' returned no values"
.format(self.subset))
names = list(data.index.names)
for name in names:
unique_values = data.index.get_level_values(name).unique()
if len(unique_values) == 1:
warn("Only one value for level {}; dropping it.".format(name),
util.CytoflowViewWarning)
try:
data.index = data.index.droplevel(name)
except AttributeError as e:
raise util.CytoflowViewError(None,
"Must have more than one "
"value to plot.") from e
if not (self.row_facet or self.column_facet):
raise util.CytoflowViewError('row_facet',
"Must set at least one of row_facet "
"or column_facet")
if self.subrow_facet and not self.row_facet:
raise util.CytoflowViewError('subrow_facet',
"Must set row_facet before using "
"subrow_facet")
if self.subcolumn_facet and not self.column_facet:
raise util.CytoflowViewError('subcolumn_facet',
"Must set column_facet before using "
"subcolumn_facet")
if self.row_facet and self.row_facet not in experiment.conditions:
raise util.CytoflowViewError('row_facet',
"Row facet {} not in the experiment, "
"must be one of {}"
.format(self.row_facet, experiment.conditions))
if self.row_facet and self.row_facet not in data.index.names:
raise util.CytoflowViewError('row_facet',
"Row facet {} not a statistic index; "
"must be one of {}"
.format(self.row_facet, data.index.names))
if self.subrow_facet and self.subrow_facet not in experiment.conditions:
raise util.CytoflowViewError('subrow_facet',
"Subrow facet {} not in the experiment, "
"must be one of {}"
.format(self.subrow_facet, experiment.conditions))
if self.subrow_facet and self.subrow_facet not in data.index.names:
raise util.CytoflowViewError('subrow_facet',
"Subrow facet {} not a statistic index; "
"must be one of {}"
.format(self.subrow_facet, data.index.names))
if self.column_facet and self.column_facet not in experiment.conditions:
raise util.CytoflowViewError('column_facet',
"Column facet {} not in the experiment, "
"must be one of {}"
.format(self.column_facet, experiment.conditions))
if self.column_facet and self.column_facet not in data.index.names:
raise util.CytoflowViewError('column_facet',
"Column facet {} not a statistic index; "
"must be one of {}"
.format(self.column_facet, data.index.names))
if self.subcolumn_facet and self.subcolumn_facet not in experiment.conditions:
raise util.CytoflowViewError('subcolumn_facet',
"Subcolumn facet {} not in the experiment, "
"must be one of {}"
.format(self.subcolumn_facet, experiment.conditions))
if self.subcolumn_facet and self.subcolumn_facet not in data.index.names:
raise util.CytoflowViewError('subcolumn_facet',
"Subcolumn facet {} not a statistic index; "
"must be one of {}"
.format(self.subcolumn_facet, data.index.names))
facets = [x for x in [self.row_facet, self.subrow_facet,
self.column_facet, self.subcolumn_facet] if x]
if len(facets) != len(set(facets)):
raise util.CytoflowViewError(None,
"Can't reuse facets")
if set(facets) != set(data.index.names):
raise util.CytoflowViewError(None,
"Must use all the statistic indices as variables or facets: {}"
.format(data.index.names))
row_groups = data.index.get_level_values(self.row_facet).unique() \
if self.row_facet else [None]
subrow_groups = data.index.get_level_values(self.subrow_facet).unique() \
if self.subrow_facet else [None]
col_groups = data.index.get_level_values(self.column_facet).unique() \
if self.column_facet else [None]
subcol_groups = data.index.get_level_values(self.subcolumn_facet).unique() \
if self.subcolumn_facet else [None]
row_offset = (self.column_facet != "") + (self.subcolumn_facet != "")
col_offset = (self.row_facet != "") + (self.subrow_facet != "")
num_cols = len(col_groups) * len(subcol_groups) + col_offset
fig = plt.figure()
ax = fig.add_subplot(111)
# hide the plot axes that matplotlib tries to make
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
for sp in ax.spines.values():
sp.set_color('w')
sp.set_zorder(0)
loc = 'upper left'
bbox = None
t = Table(ax, loc, bbox, **kwargs)
t.auto_set_font_size(False)
for c in range(num_cols):
t.auto_set_column_width(c)
width = [0.2] * num_cols
height = t._approx_text_height() * 1.8
# make the main table
for (ri, r) in enumerate(row_groups):
for (rri, rr) in enumerate(subrow_groups):
for (ci, c) in enumerate(col_groups):
for (cci, cc) in enumerate(subcol_groups):
row_idx = ri * len(subrow_groups) + rri + row_offset
col_idx = ci * len(subcol_groups) + cci + col_offset
# this is not pythonic, but i'm tired
agg_idx = []
for data_idx in data.index.names:
if data_idx == self.row_facet:
agg_idx.append(r)
elif data_idx == self.subrow_facet:
agg_idx.append(rr)
elif data_idx == self.column_facet:
agg_idx.append(c)
elif data_idx == self.subcolumn_facet:
agg_idx.append(cc)
agg_idx = tuple(agg_idx)
if len(agg_idx) == 1:
agg_idx = agg_idx[0]
try:
text = "{:g}".format(data.loc[agg_idx][stat.name])
except ValueError:
text = data.loc[agg_idx][stat.name]
t.add_cell(row_idx,
col_idx,
width = width[col_idx],
height = height,
text = text)
# row headers
if self.row_facet:
for (ri, r) in enumerate(row_groups):
row_idx = ri * len(subrow_groups) + row_offset
try:
text = "{0} = {1:g}".format(self.row_facet, r)
except ValueError:
text = "{0} = {1}".format(self.row_facet, r)
t.add_cell(row_idx,
0,
width = width[0],
height = height,
text = text)
# subrow headers
if self.subrow_facet:
for (ri, r) in enumerate(row_groups):
for (rri, rr) in enumerate(subrow_groups):
row_idx = ri * len(subrow_groups) + rri + row_offset
try:
text = "{0} = {1:g}".format(self.subrow_facet, rr)
except ValueError:
text = "{0} = {1}".format(self.subrow_facet, rr)
t.add_cell(row_idx,
1,
width = width[1],
height = height,
text = text)
# column headers
if self.column_facet:
for (ci, c) in enumerate(col_groups):
col_idx = ci * len(subcol_groups) + col_offset
try:
text = "{0} = {1:g}".format(self.column_facet, c)
except ValueError:
text = "{0} = {1}".format(self.column_facet, c)
t.add_cell(0,
col_idx,
width = width[col_idx],
height = height,
text = text)
# subcolumn headers
if self.subcolumn_facet:
for (ci, c) in enumerate(col_groups):
for (cci, cc) in enumerate(subcol_groups):
col_idx = ci * len(subcol_groups) + cci + col_offset
try:
text = "{0} = {1:g}".format(self.subcolumn_facet, cc)
except ValueError:
text = "{0} = {1}".format(self.subcolumn_facet, cc)
t.add_cell(1,
col_idx,
width = width[col_idx],
height = height,
text = text)
ax.add_table(t)
def plot(self, experiment, plot_name=None, **kwargs):
"""Plot a table of the conditions, filenames, and number of events"""
if experiment is None:
raise util.CytoflowViewError('experiment',
"No experiment specified")
if self.subset:
try:
experiment = experiment.query(self.subset)
except Exception as e:
raise util.CytoflowViewError(
'subset', "Subset string '{0}' isn't valid".format(
self.subset)) from e
if len(experiment) == 0:
raise util.CytoflowViewError(
'subset', "Subset string '{0}' returned no values".format(
self.subset))
# if path is set, actually do an export. this isn't terribly elegant,
# but this is the only place we have an experiment! ExportFCS.export()
# raises CytoflowViewErrors, so it should be compatible with the
# existing error reporting stuff.
if self.path:
self.export(experiment)
return
# otherwise, make a table showing what will be exported
num_cols = len(self.by) + 2
fig = plt.figure()
ax = fig.add_subplot(111)
# hide the plot axes that matplotlib tries to make
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
for sp in ax.spines.values():
sp.set_color('w')
sp.set_zorder(0)
loc = 'upper left'
bbox = None
t = Table(ax, loc, bbox)
t.auto_set_font_size(False)
for c in range(num_cols):
t.auto_set_column_width(c)
width = [0.2] * num_cols
height = t._approx_text_height() * 1.8
t.add_cell(0, 0, width=width[0], height=height, text="#")
for ci, c in enumerate(self.by):
ci = ci + 1
t.add_cell(0, ci, width=width[ci], height=height, text=c)
ci = len(self.by) + 1
t.add_cell(0, ci, width=width[ci], height=height, text="Filename")
# ci = len(self.by) + 2
# t.add_cell(0, ci, width = width[ci], height = height, text = "Events")
for ri, row in enumerate(self.enum_conditions_and_files(experiment)):
t.add_cell(ri + 1,
0,
width=width[0],
height=height,
text="{:g}".format(ri + 1))
for ci, col in enumerate(row):
t.add_cell(ri + 1,
ci + 1,
width=width[ci + 1],
height=height,
text=col)
ax.add_table(t)
