def test_get_tier_boundaries(self):
self.failUnlessEqual([int(x) for x in get_tier_boundaries(\
self.withPoint['A'])],
[2, 179])
self.failUnlessEqual([int(x) for x in get_tier_boundaries(\
self.withPoint['P'])],
[2, 32])
self.failUnlessEqual(get_tier_boundaries(None), None)
self.failUnlessEqual(get_tier_boundaries(pd.DataFrame(None, columns=\
['start_time',
'end_time',
'text'])),
None)
self.failUnlessEqual([int(x) for x in get_tier_boundaries(\
self.withPoint['P'][:1])], [2, 2])
def test_get_tier_boundaries(self):
self.failUnlessEqual([int(x) for x in get_tier_boundaries(\
self.withPoint['A'])],
[2, 179])
self.failUnlessEqual([int(x) for x in get_tier_boundaries(\
self.withPoint['P'])],
[2, 32])
self.failUnlessEqual(get_tier_boundaries(None), None)
self.failUnlessEqual(get_tier_boundaries(pd.DataFrame(None, columns=\
['start_time',
'end_time',
'text'])),
None)
self.failUnlessEqual([int(x) for x in get_tier_boundaries(\
self.withPoint['P'][:1])], [2, 2])
def plot_annotations(tierdict, time_begin=None, time_end=None, tierorder=None,
colorindex=None, hscale=1, vscale=1, linespan=20,
pointwidth=0.05, tickspacing=1,
text_kwargs=None, filepath=None):
"""Plot ELAN annotations, imported from textgrids
arguments:
tierdict a dictionary of intervalframes
keyword arguments:
time_begin -- minimum time (in seconds) of plot. If set to None, the
minimum time is found from the data
time_end -- maximum time (in seconds) of plot. If set to None, the
maximum time is found from the data
tierorder -- list of tierKey names to set the order of plotting.
Specifying less names than in the tierdict itself
results in only those tiers being drawn
colorindex -- list of colors to cycle through for each tier, or
dictionary with labels as keys and colorcodes as values,
for plotting annotation tiers with finite label sets
hscale, vscale -- horizontal/vertical scaling of the plot
linespan -- time displayed per line of the plot (default 20 seconds)
pointwidth -- width of lines for point tiers (in seconds)
tickspacing -- number of seconds between ticks on x axis (default 1)
text_kwargs -- a fontdict for plt.text() in order to print the
text labels. Set to None to avoid printing any text
filepath -- path to filename to save the figure, e.g:
'~/Desktop/myfile.pdf'
The file must have one of the matplolib-supported
extensions, e.g. 'pdf', 'png', 'jpg'
"""
if colorindex == None:
colorindex = ['r', 'g', 'b', 'c', 'm', 'y', 'k']
#determine tiers to draw and the order
thekeys = []
if tierorder == None:
thekeys = tierdict.keys()
else:
thekeys = tierorder
if len(thekeys) == 0:
return "No tiers to plot!"
#find boundaries
tiermin = min([get_tier_boundaries(tierdict[tierkey])[0] for tierkey \
in thekeys])
tiermax = max([get_tier_boundaries(tierdict[tierkey])[1] for tierkey \
in thekeys])
if time_begin == None:
time_begin = tiermin
else:
time_begin = max(time_begin, tiermin)
if time_end == None:
time_end = tiermax
else:
time_end = min(time_end, tiermax)
#Check time limits
duration = time_end - time_begin
if duration <= 0:
return "Wrong time limits!"
elif duration < linespan:
linespan = duration
number_of_lines = 1
else:
number_of_lines = int((float(duration) / linespan)) + 1
fig = plt.figure(figsize=(hscale * linespan,
vscale * number_of_lines * len(thekeys)))
for line in range(number_of_lines):
#Drawing loop of tiers
for tiernumber, tierkey in enumerate(thekeys):
#Trim tier at time limits
t1 = time_begin + line * linespan
t2 = min(t1 + linespan, time_end)
if get_tier_type(tierdict[tierkey]) == 'point':
tier = slice_intervalframe_by_time(\
__point_tier_to_intervals__(tierdict[tierkey],
pointwidth), t1, t2)
elif get_tier_type(tierdict[tierkey]) == 'interval':
tier = slice_intervalframe_by_time(tierdict[tierkey], t1, t2)
else:
continue
#Add subplots
ax = fig.add_subplot(number_of_lines * len(thekeys), 1,
line * len(thekeys) + tiernumber + 1)
xticks = range(int(t1), int(t2) + 1, tickspacing)
if tiernumber == len(thekeys)-1:
xlabels = xticks
else:
xlabels = []
#Set the color
if isinstance(colorindex, list):
tiercolor = colorindex[tiernumber % len(colorindex)]
elif isinstance(colorindex, dict):
tiercolor = colorindex
__draw_tier__(ax, fig.canvas.get_renderer(), tier, xmin=t1,
xmax=(t1 + linespan), ymin=0, ymax=1,
xticks=xticks, xlabels=xlabels, tierkey=tierkey,
tiercolor=tiercolor, edgecolor='w',
textkwargs=text_kwargs)
fig.subplots_adjust(hspace=0.5)
if filepath is not None:
fig.savefig(filepath, format=filepath.split('.')[1])
def plot_annotations(tierdict,
time_begin=None,
time_end=None,
tierorder=None,
colorindex=None,
hscale=1,
vscale=1,
linespan=20,
pointwidth=0.05,
tickspacing=1,
text_kwargs=None,
filepath=None):
"""Plot ELAN annotations, imported from textgrids
arguments:
tierdict a dictionary of intervalframes
keyword arguments:
time_begin -- minimum time (in seconds) of plot. If set to None, the
minimum time is found from the data
time_end -- maximum time (in seconds) of plot. If set to None, the
maximum time is found from the data
tierorder -- list of tierKey names to set the order of plotting.
Specifying less names than in the tierdict itself
results in only those tiers being drawn
colorindex -- list of colors to cycle through for each tier, or
dictionary with labels as keys and colorcodes as values,
for plotting annotation tiers with finite label sets
hscale, vscale -- horizontal/vertical scaling of the plot
linespan -- time displayed per line of the plot (default 20 seconds)
pointwidth -- width of lines for point tiers (in seconds)
tickspacing -- number of seconds between ticks on x axis (default 1)
text_kwargs -- a fontdict for plt.text() in order to print the
text labels. Set to None to avoid printing any text
filepath -- path to filename to save the figure, e.g:
'~/Desktop/myfile.pdf'
The file must have one of the matplolib-supported
extensions, e.g. 'pdf', 'png', 'jpg'
"""
if colorindex == None:
colorindex = ['r', 'g', 'b', 'c', 'm', 'y', 'k']
#determine tiers to draw and the order
thekeys = []
if tierorder == None:
thekeys = tierdict.keys()
else:
thekeys = tierorder
if len(thekeys) == 0:
return "No tiers to plot!"
#find boundaries
tiermin = min([get_tier_boundaries(tierdict[tierkey])[0] for tierkey \
in thekeys])
tiermax = max([get_tier_boundaries(tierdict[tierkey])[1] for tierkey \
in thekeys])
if time_begin == None:
time_begin = tiermin
else:
time_begin = max(time_begin, tiermin)
if time_end == None:
time_end = tiermax
else:
time_end = min(time_end, tiermax)
#Check time limits
duration = time_end - time_begin
if duration <= 0:
return "Wrong time limits!"
elif duration < linespan:
linespan = duration
number_of_lines = 1
else:
number_of_lines = int((float(duration) / linespan)) + 1
fig = plt.figure(figsize=(hscale * linespan,
vscale * number_of_lines * len(thekeys)))
for line in range(number_of_lines):
#Drawing loop of tiers
for tiernumber, tierkey in enumerate(thekeys):
#Trim tier at time limits
t1 = time_begin + line * linespan
t2 = min(t1 + linespan, time_end)
if get_tier_type(tierdict[tierkey]) == 'point':
tier = slice_intervalframe_by_time(\
__point_tier_to_intervals__(tierdict[tierkey],
pointwidth), t1, t2)
elif get_tier_type(tierdict[tierkey]) == 'interval':
tier = slice_intervalframe_by_time(tierdict[tierkey], t1, t2)
else:
continue
#Add subplots
ax = fig.add_subplot(number_of_lines * len(thekeys), 1,
line * len(thekeys) + tiernumber + 1)
xticks = range(int(t1), int(t2) + 1, tickspacing)
if tiernumber == len(thekeys) - 1:
xlabels = xticks
else:
xlabels = []
#Set the color
if isinstance(colorindex, list):
tiercolor = colorindex[tiernumber % len(colorindex)]
elif isinstance(colorindex, dict):
tiercolor = colorindex
__draw_tier__(ax,
fig.canvas.get_renderer(),
tier,
xmin=t1,
xmax=(t1 + linespan),
ymin=0,
ymax=1,
xticks=xticks,
xlabels=xlabels,
tierkey=tierkey,
tiercolor=tiercolor,
edgecolor='w',
textkwargs=text_kwargs)
fig.subplots_adjust(hspace=0.5)
if filepath is not None:
fig.savefig(filepath, format=filepath.split('.')[1])
