def populate_region_selection_tab(self):
self.region_figures = matts_admin_functions.create_empty_list(number_of_planes)
self.region_canvases = matts_admin_functions.create_empty_list(number_of_planes)
self.region_widgets = matts_admin_functions.create_empty_list(number_of_planes)
self.roi_displays = matts_admin_functions.create_empty_list(number_of_planes)
global region_combo_boxes
for plane in range(number_of_planes):
figure, canvas, widget = create_canvas_widget(400, 400)
self.region_figures[plane] = figure
self.region_canvases[plane] = canvas
self.region_widgets[plane] = widget
self.roi_displays[plane] = QGraphicsView()
self.roi_displays[plane].setMinimumWidth(500)
region_combo_boxes[plane] = QComboBox()
region_combo_boxes[plane].addItem("Forebrain")
region_combo_boxes[plane].addItem("Tectum")
region_combo_boxes[plane].addItem("Midbrain")
region_combo_boxes[plane].addItem("Hindbrain")
combo_box_function = self.create_region_combo_box_function(plane)
region_combo_boxes[plane].currentIndexChanged.connect(combo_box_function)
self.region_selection_scroll_area_contents_layout.addWidget(region_combo_boxes[plane], plane, 0)
self.region_selection_scroll_area_contents_layout.addWidget(self.region_widgets[plane], plane, 1)
self.region_selection_scroll_area_contents_layout.addWidget(self.roi_displays[plane], plane, 2)
def draw_roi_scene(plane):
scene = QGraphicsScene()
scale_factor = 3
#scene.setSceneRect(0,0, tiff_dimensions[0], tiff_dimensions[1])
roi_size = 10
roi_elipses = matts_admin_functions.create_empty_list(
len(neuron_coordinates[plane]))
y_offset = -50
x_offset = -50
for roi_index in range(len(neuron_coordinates[plane])):
x_cord = neuron_coordinates[plane][roi_index][1]
y_cord = neuron_coordinates[plane][roi_index][0]
probability = cell_probabilities[plane][roi_index]
colour = get_colour(probability, "hot", 0.8)
roi_elipses[roi_index] = QGraphicsEllipseItem(
(x_cord + x_offset), (y_cord + y_offset), roi_size, roi_size)
roi_elipses[roi_index].setBrush(QBrush(colour))
roi_elipses[roi_index].setPos(x_cord / scale_factor,
y_cord / scale_factor)
if neuron_decisions[plane][roi_index] == False:
roi_elipses[roi_index].setOpacity(0.2)
scene.addItem(roi_elipses[roi_index])
main.roi_displays[plane].setScene(scene)
def create_lasso_functions():
plane_functions = matts_admin_functions.create_empty_list(number_of_planes)
for plane in range(number_of_planes):
plane_functions[plane] = create_plane_function(plane)
return plane_functions
def create_lassos():
lassos = matts_admin_functions.create_empty_list(number_of_planes)
lasso_functions = create_lasso_functions()
for plane in range(number_of_planes):
axis = main.region_figures[plane].get_axes()
lassos[plane] = LassoSelector(axis[0], lasso_functions[plane])
return lassos
def load_cell_probabilities():
global cell_probabilities
cell_probabilities = matts_admin_functions.create_empty_list(number_of_planes)
for plane in range(number_of_planes):
is_cell_file_location = str(folder_location + str(r"\plane"+str(plane)) +"\iscell.npy")
is_cell = np.load(is_cell_file_location)
for cell in range(len(is_cell)):
cell_probabilities[plane].append(is_cell[cell][1])
def bcl_function(trace):
# BCL Parameters
wdt = 0.1
lamb = 0.6
varB = 2e-2
varC = 2
initial_baseline = 1
Cmean = 0
frequency = 2.7
#Preprocess Function
t1 = trace / np.mean(trace)
y = lowpass_filter(t1, 500) #2000 too high, #200 too low
difft = diff(y)
varX = get_variance_of_the_decreases(difft)
#Declare Variables
N = len(y)
B = matts_admin_functions.create_empty_list(N)
c = matts_admin_functions.create_list_of_zeros(N)
sks = matts_admin_functions.create_list_of_zeros(N)
B[0] = initial_baseline
loglik = 0
dt = float(1) / frequency
for t in range(1, N):
cnew = c[t - 1] * np.exp(-lamb * dt)
Bnew = (varX * B[t - 1] + varB * dt *
(y[t] - cnew)) / (varX + varB * dt)
logp0 = log(1 -
wdt) - 0.5 * log(2 * pi) - 0.5 * log(varX + varB * dt) - (
y[t] - cnew - B[t - 1])**2 / (2 * varX + 2 * varB * dt)
cspike = Cmean + cnew + (y[t] - cnew - B[t - 1]) / (
1 + varB * dt / varC + varX / varC)
Bspike = B[t - 1] + varB * dt / varC * (cspike - cnew - Cmean)
logp1 = log(wdt) - 0.5 * log(2 * pi) - 0.5 * log(
varX + varB * dt + varC) - (y[t] - cnew - B[t - 1] - Cmean)**2 / (
2 * varX + 2 * varB * dt + 2 * varC)
if logp1 < logp0:
c[t] = cnew
B[t] = Bnew
loglik = loglik + logp0
else:
c[t] = cspike
B[t] = Bspike
sks[t] = 1
loglik = loglik + logp1
return c, B, sks
def load_flourescence_traces():
global flourescence_traces
global number_of_timepoints
flourescence_traces = matts_admin_functions.create_empty_list(number_of_planes)
for plane in range(number_of_planes):
trace_file_location = str(folder_location + str(r"\plane"+str(plane)) + "\F.npy")
traces = np.load(trace_file_location)
flourescence_traces[plane] = traces
number_of_timepoints = len(flourescence_traces[plane][0])
def create_region_selection_tab(self):
self.region_selection_tab = QWidget()
self.region_selection_tab_layout = QGridLayout()
self.region_selection_tab.setLayout(self.region_selection_tab_layout)
#Input Directory Button
self.input_directory_button = QPushButton("Load Suite2p Data")
self.input_directory_button.clicked.connect(load_data)
#Number of Planes Input
self.number_of_planes_spinner = QSpinBox()
self.number_of_planes_spinner.setValue(number_of_planes)
self.number_of_planes_label = QLabel("Number Of Planes: ")
self.number_of_planes_spinner.valueChanged.connect(
self.set_number_of_planes)
#Cell Probability Q-Slider
self.probabiltiy_slider = QSlider(Qt.Horizontal)
self.probabiltiy_slider.valueChanged.connect(
self.threshold_slider_value_changed)
self.probabiltiy_slider.setValue(cell_probability_threshold * 100)
self.probability_threshold_button = QPushButton(
"Threshold Cell Probability")
self.probability_threshold_button.clicked.connect(
threshold_cell_probability)
self.probabiltiy_slider_label = QLabel("Cell Probability Threshold")
self.probabiltiy_slider_value_label = QLabel(
str(cell_probability_threshold))
#Save Traces Button
self.save_traces_button = QPushButton("Save Traces")
self.save_traces_button.clicked.connect(save_traces)
#Extract Spikes Button
self.extract_spikes_button = QPushButton("Extract Spikes")
self.extract_spikes_button.clicked.connect(extract_spikes)
#Number of Neurons Button and Label
self.number_of_neurons_button = QPushButton(
"Calculate Number of Remaining Neurons")
self.number_of_neurons_button.clicked.connect(
calculate_number_of_cells)
self.number_of_neurons_label = QLabel()
#Create Scroll Area
self.region_selection_scroll_area_contents = QWidget()
self.region_selection_scroll_area_contents_layout = QGridLayout()
self.region_selection_scroll_area_contents.setLayout(
self.region_selection_scroll_area_contents_layout)
self.region_selection_scroll_area = QScrollArea()
self.region_selection_scroll_area.setWidget(
self.region_selection_scroll_area_contents)
self.region_selection_scroll_area.setWidgetResizable(True)
self.region_figures = matts_admin_functions.create_empty_list(
number_of_planes)
self.region_canvases = matts_admin_functions.create_empty_list(
number_of_planes)
self.region_widgets = matts_admin_functions.create_empty_list(
number_of_planes)
self.roi_displays = matts_admin_functions.create_empty_list(
number_of_planes)
self.region_combo_boxes = matts_admin_functions.create_empty_list(
number_of_planes)
for plane in range(number_of_planes):
figure, canvas, widget = create_canvas_widget(400, 400)
self.region_figures[plane] = figure
self.region_canvases[plane] = canvas
self.region_widgets[plane] = widget
self.roi_displays[plane] = QGraphicsView()
self.roi_displays[plane].setMinimumWidth(500)
self.region_combo_boxes[plane] = QComboBox()
self.region_combo_boxes[plane].addItem("Forebrain")
self.region_combo_boxes[plane].addItem("Tectum")
self.region_combo_boxes[plane].addItem("Midbrain")
self.region_combo_boxes[plane].addItem("Hindbrain")
self.region_selection_scroll_area_contents_layout.addWidget(
self.region_combo_boxes[plane], plane, 0)
self.region_selection_scroll_area_contents_layout.addWidget(
self.region_widgets[plane], plane, 1)
self.region_selection_scroll_area_contents_layout.addWidget(
self.roi_displays[plane], plane, 2)
self.region_selection_tab_layout.setColumnMinimumWidth(0, 1000)
self.region_selection_tab_layout.addWidget(self.input_directory_button,
0, 1, 1, 4)
self.region_selection_tab_layout.addWidget(
self.number_of_planes_spinner, 1, 2, 1, 1)
self.region_selection_tab_layout.addWidget(self.number_of_planes_label,
1, 1, 1, 1)
self.region_selection_tab_layout.addWidget(
self.region_selection_scroll_area, 0, 0, 20, 1)
self.region_selection_tab_layout.addWidget(
self.probabiltiy_slider_label, 2, 1, 1, 1)
self.region_selection_tab_layout.addWidget(self.probabiltiy_slider, 2,
2, 1, 2)
self.region_selection_tab_layout.addWidget(
self.probabiltiy_slider_value_label, 2, 4, 1, 1)
self.region_selection_tab_layout.addWidget(
self.probability_threshold_button, 3, 1, 1, 4)
self.region_selection_tab_layout.addWidget(self.save_traces_button, 4,
1, 1, 4)
self.region_selection_tab_layout.addWidget(self.extract_spikes_button,
5, 1, 1, 4)
self.region_selection_tab_layout.addWidget(
self.number_of_neurons_button, 6, 1, 1, 1)
self.region_selection_tab_layout.addWidget(
self.number_of_neurons_label, 6, 3, 1, 2)
self.tabs.addTab(self.region_selection_tab, "Region Selection")
def load_rois():
global neuron_coordinates
global neuron_decisions
global within_region_decisions
global cell_probability_decisions
global cell_noises
global cell_noise_decisions
global region_assignments
global full_neuron_regions
global spike_matricies
global cell_trace_figures
global position_indicator_axes
global cell_trace_canvases
neuron_coordinates = matts_admin_functions.create_empty_list(
number_of_planes)
neuron_decisions = matts_admin_functions.create_empty_list(
number_of_planes)
within_region_decisions = matts_admin_functions.create_empty_list(
number_of_planes)
cell_probability_decisions = matts_admin_functions.create_empty_list(
number_of_planes)
cell_noises = matts_admin_functions.create_empty_list(number_of_planes)
cell_noise_decisions = matts_admin_functions.create_empty_list(
number_of_planes)
region_assignments = matts_admin_functions.create_empty_list(
number_of_planes)
spike_matricies = matts_admin_functions.create_empty_list(number_of_planes)
cell_trace_figures = matts_admin_functions.create_empty_list(
number_of_planes)
cell_trace_canvases = matts_admin_functions.create_empty_list(
number_of_planes)
position_indicator_axes = matts_admin_functions.create_empty_list(
number_of_planes)
for plane in range(number_of_planes):
stats_file_location = str(folder_location +
str(r"\plane" + str(plane)) + "\stat.npy")
stats = np.load(stats_file_location)
for neuron in range(len(stats)):
neuron_coordinates[plane].append(stats[neuron]["med"])
neuron_decisions[plane].append(True)
within_region_decisions[plane].append(True)
cell_probability_decisions[plane].append(True)
cell_noises[plane].append(0)
cell_noise_decisions[plane].append(True)
region_assignments[plane].append("N/A")
spike_matricies[plane].append([])
cell_trace_figures[plane].append([])
position_indicator_axes[plane].append([])
cell_trace_canvases[plane].append([])
populate_trace_combobox()
def setup_variables():
global neuron_coordinates
global neuron_decisions
global within_region_decisions
global cell_probability_decisions
global cell_noises
global cell_noise_decisions
global region_assignments
global full_neuron_regions
global spike_matricies
global cell_trace_figures
global position_indicator_axes
global cell_trace_canvases
global calcium_traces
global baseline_traces
global region_combo_boxes
global currently_selected_region
global neuron_locations
global fourier_traces
neuron_coordinates = matts_admin_functions.create_empty_list(number_of_planes)
neuron_decisions = matts_admin_functions.create_empty_list(number_of_planes)
within_region_decisions = matts_admin_functions.create_empty_list(number_of_planes)
cell_probability_decisions = matts_admin_functions.create_empty_list(number_of_planes)
cell_noises = matts_admin_functions.create_empty_list(number_of_planes)
cell_noise_decisions = matts_admin_functions.create_empty_list(number_of_planes)
region_assignments = matts_admin_functions.create_empty_list(number_of_planes)
spike_matricies = matts_admin_functions.create_empty_list(number_of_planes)
cell_trace_figures = matts_admin_functions.create_empty_list(number_of_planes)
cell_trace_canvases = matts_admin_functions.create_empty_list(number_of_planes)
position_indicator_axes = matts_admin_functions.create_empty_list(number_of_planes)
calcium_traces = matts_admin_functions.create_empty_list(number_of_planes)
baseline_traces = matts_admin_functions.create_empty_list(number_of_planes)
region_combo_boxes = matts_admin_functions.create_empty_list(number_of_planes)
neuron_locations = matts_admin_functions.create_empty_list(number_of_planes)
fourier_traces = matts_admin_functions.create_empty_list(number_of_planes)
currently_selected_region = matts_admin_functions.create_list_of_item(number_of_planes,"Forebrain")
print "Number of neurons", number_of_neurons
for plane in range(number_of_planes):
for neuron in range(number_of_neurons[plane]):
neuron_decisions [plane].append(True)
within_region_decisions [plane].append(False) #change back later
cell_probability_decisions [plane].append(True)
cell_noises [plane].append(0)
cell_noise_decisions [plane].append(True)
region_assignments [plane].append("N/A")
spike_matricies [plane].append([])
cell_trace_figures [plane].append([])
position_indicator_axes [plane].append([])
cell_trace_canvases [plane].append([])
calcium_traces [plane].append([])
baseline_traces [plane].append([])
fourier_traces [plane].append([])
neuron_locations [plane].append(0)
populate_trace_combobox()
