def save_sinesweep_analysis_CSV(self):
def callback(specimens):
analysers = self.core.get_manalysers(specimen)
sinesweep.save_sinesweep_analysis_CSV(analysers)
select_specimens(self.core, callback, with_movements=True)
def export_LR_displacement_CSV(self, strong_weak_division=False):
'''
Grouped to left right
'''
def callback(specimens):
group_name = ask_string('Group name', 'Name the selected group of specimens', self.tk_root)
analysers = self.core.get_manalysers(specimens)
left_right_displacements(analysers, group_name,
strong_weak_division=strong_weak_division)
select_specimens(self.core, callback, with_movements=True)
def save_kinematics_analysis_CSV(self):
def callback(specimens):
fn = tk.filedialog.asksaveasfilename(title='Save kinematics analysis', initialfile='latencies.csv')
if fn:
analysers = self.core.get_manalysers(specimens)
kinematics.save_sigmoidal_fit_CSV(analysers, fn)
select_specimens(self.core, callback, with_movements=True)
def averaged_vectormap_DASH_rotating_video_multiprocessing(self):
def run_workers(specimens):
if len(specimens) > 0:
N_workers = os.cpu_count()
for i_worker in range(N_workers):
if i_worker != 0:
additional = '--dont-show'
else:
additional = ''
self.core.adm_subprocess(specimens, '--tk_waiting_window --worker-info {} {} --average -A vectormap_video'.format(i_worker, N_workers))
select_specimens(self.core, run_workers, with_movements=True)
def link_ERG_data_from_labbook(self):
select_specimens(self.core, linked_data.link_erg_labbook, command_args=[lambda: filedialog.askopenfilename(title='Select ERG'), lambda: filedialog.askdirectory(title='Select data folder')], return_manalysers=True )
def _preedit():
select_specimens(self.core, _postedit)
def comparision_to_optic_flow_DASH_video(self):
select_specimens(self.core, lambda specimens: self.core.adm_subprocess(specimens, '--tk_waiting_window --average -A flow_analysis_pitch'), with_movements=True)
def averaged_vectormap_DASH_rotating_video_DASH_set_title(self):
ask_string('Set title', 'Give video title', lambda title: select_specimens(self.core, lambda specimens: self.core.adm_subprocess(specimens, '--tk_waiting_window --average --short-name {} -A vectormap_video'.format(title)), with_movements=True))
def averaged_vectormap_DASH_rotating_video(self):
select_specimens(self.core, lambda specimens: self.core.adm_subprocess(specimens, '--tk_waiting_window --average -A vectormap_video'), with_movements=True)
def averaged_vectormap_DASH_interactive_plot(self):
select_specimens(self.core, lambda specimens: self.core.adm_subprocess(specimens, '--tk_waiting_window --average -A vectormap'), with_movements=True)
def measure_movements_DASH_in_absolute_coordinates(self):
func = lambda specimens: self._batch_measure(specimens, absolute_coordinates=True)
select_specimens(self.core, func, with_rois=True)
def measure_movements_DASH_list_only_unmeasured(self):
select_specimens(self.core, self._batch_measure, with_rois=True, with_movements=False)
def measure_movements_DASH_list_all(self):
select_specimens(self.core, self._batch_measure, with_rois=True)