def set_zoom(self, events_ds=None, address=None, pad=10):
"""
Set the time range of the data that is displayed based on events.
events_ds :
index of vizualizer/dataset containing events (None to
reset zoom and show all data)
address :
event-address of events to display
pad: scalar
time to display outside of events
**See also:** .set_window()
"""
if events_ds is not None:
v = self.visualizers[events_ds]
ds = v.dataset
if ds.properties['data_type'] != 'event':
ui.message("'%s' is not an event dataset!"%ds.name, "", '!')
return
self._zoom_events = events_ds
self._zoom_address = address
self._zoom_pad = pad
self._zoom_window = None
self.OnRefresh(None)
def read_example_file(self, path):
self._example_path = path
if path == None:
self.p.channels._set_n_channels(0)
self._example_data = None
self._example_prop = None
else:
data, properties = self.get_file(path)
assert data.ndim == 2, "get_file returned invalid data"
t, n = data.shape
# save example
properties['dtype'] = data.dtype
self._example_data = data
self._example_prop = properties
# use example properties to set p
self.p.channels._set_n_channels(n)
if 'samplingrate' in properties:
new_sr = properties['samplingrate']
old_sr = self.p.samplingrate.get()
if old_sr != new_sr and bool(new_sr):
self.p.samplingrate(new_sr)
ui.message("Samplingrate updated %s Hz -> %s Hz"%(old_sr, new_sr),
"The importer's samplingrate parameter has been "
"updated based on the file's properties.")
def _OnThreshold(self, event):
"""
above: True, False, None
how to mark segments that exceed the threshold: True->good;
False->bad; None->don't change
below:
same as ``above`` but for segments that do not exceed the threshold
"""
threshold = None
above = False
below = True
msg = "What value should be used to threshold the data?"
while threshold is None:
dlg = wx.TextEntryDialog(self, msg, "Choose Threshold", "2e-12")
if dlg.ShowModal() == wx.ID_OK:
value = dlg.GetValue()
try:
threshold = float(value)
except ValueError:
ui.message("Invalid Entry", "%r is not a valid entry. Need "
"a float." % value, '!')
else:
return
process.mark_by_threshold(self._dataset, DV=self._data,
threshold=threshold, above=above,
below=below, target=self._target)
self._Refresh(event)
def _is_bin_path(package, path):
if package == 'mne':
test = ['mne_add_patch_info', 'mne_analyze']
elif package == 'freesurfer':
test = ['mri_annotation2label']
elif package == 'edfapi':
test = ['edf2asc']
else:
raise KeyError("Unknown package: %r" % package)
test_paths = [os.path.join(path, testname) for testname in test]
if all(map(os.path.exists, test_paths)):
return True
else:
msg = ("You need to select a directory containing the following "
"executables: %r" % test)
ui.message("Invalid Binary Directory", msg, 'error')
def OnCopyTextab(self, event=None):
try:
fmtxt.copy_pdf()
except Exception as e:
ui.message("Error in Copy Tex", str(e), '!')
def plot(self, fig_num=None):#, tmax=1000):
if self._example_path == None:
ui.message("No files specified", "Before an import preview can be "
"plotted, at least one source file has "
"to be specified through the p.source parameter.", '!')
return
data = self._example_data#[:tmax]
# range correct data
t, n = data.shape
data = data - np.min(data, 0)
data /= np.max(data, 0) * 1.1
data += np.arange(n-1, -1, -1) # channel 1 on the top
# collect properties
name = os.path.basename(self._example_path)
samplingrate = self.p.samplingrate.get()
T = np.arange(0, t)
if samplingrate:
T /= samplingrate
# start plot
P.figure(fig_num)
P.subplots_adjust(.2, .05, .99, .9)
P.suptitle("Example: %s"%fmtxt.texify(name))
ax = P.axes()
lines = [ax.plot(data[:,i], c='.75', antialiased=False)[0] for i in xrange(n)]
y_ticks = np.arange(n-1, -1, -1) + .45
y_ticklabels = range(n)
# get channels data
for index, settings in self.p.channels.iterchannels():
# ax = P.subplot(n, 1, i+1, sharex=ax)
name, ds_type, arg1, arg2 = settings
# y_ticklabels.append(name)
if isinstance(index, int):
ls = [lines[index]]
y_ticklabels[index] = name
# y_ticks.append(i)
else:
if isinstance(index, slice):
start, stop = index.start, index.stop
ls = lines[index]
indexes = xrange(start+1, stop+1)
else:
start = index[0]
indexes = index[1:]
ls = [lines[i] for i in index]
y_ticklabels[start] = name
for i in indexes:
y_ticklabels[i] = ''
# tick_y = start + (stop-start)//2
# y_ticks.append(tick_y)
if ds_type == 'uts':
c = 'k'
elif ds_type == 'topo':
c = 'r'
elif ds_type == 'evt':
c = 'b'
for l in ls:
l.set_color(c)
if hasattr(ax, 'tick_params'):
ax.tick_params(axis='y', length=0)
ax.set_xlim(0, len(data))
ax.set_yticks(y_ticks)
ax.set_yticklabels(y_ticklabels)
# ax.set_xlim(T[0], T[-1])
# ax.set_xlim(0, tmax)
P.show()
