Add wip dashboard

derotation/postprocessing/dashboard.py

@@ -0,0 +1,179 @@
+from pathlib import Path
+
+import fastplotlib as fpl
+import numpy as np
+import pandas as pd
+from ipywidgets import AppLayout
+
+from derotation.postprocessing.load_processed_data import (
+    get_dff,
+    get_plane_segmentation,
+    load_registered_binary,
+    load_suite2p_data,
+)
+
+# warnings.filterwarnings("ignore", category=DeprecationWarning)
+
+# ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯
+# Load data
+
+path_to_nwb = Path(
+    "/Users/lauraporta/Source/local/NWB_conversions/data/suite2p.nwb"
+)
+
+suite2p_data = load_suite2p_data(path_to_nwb)
+
+dff, timebase = get_dff(suite2p_data)
+
+ROI_centroids, is_cell, labels, contours = get_plane_segmentation(suite2p_data)
+
+
+# Load csv file containing rotation information
+rotation_info = pd.read_csv("rotation_info.csv")
+
+
+# import the registered binary as it is not included in the NWB file
+path_to_bin_file = Path(
+    "/Users/laura/data/derotation/raw/230802_CAA_1120182/derotated/archive/test/suite2p/plane0/data.bin"
+)
+
+registered = load_registered_binary(path_to_bin_file, (512, 512, len(dff)))
+
+# ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯ ⚁⚀ ⚯
+# Starting point of the dashboard
+
+
+def find_ROI(nearest):
+    x, y, _ = np.asarray(nearest.data.value).mean(axis=0)
+    # print(f'x:{x}, y:{y}')
+    closest_x = np.abs(ROI_centroids[:, 0] - x).argmin()
+    closest_y = np.abs(ROI_centroids[:, 1] - y).argmin()
+    # print(f'closest x: {closest_x}, closest_y: {closest_y}')
+    if closest_x != closest_y:
+        delta_x = ROI_centroids[closest_x, 0] - x
+        delta_y = ROI_centroids[closest_y, 1] - y
+        if delta_x < delta_y:
+            return closest_x
+        else:
+            return closest_y
+    else:
+        return closest_x
+
+
+# Panel 1
+colors = {key: "white" for key in range(len(rotation_info["rotation_angle"]))}
+for i, row in rotation_info.iterrows():
+    if row["direction"] == -1:
+        colors[i] = "green"
+    if row["direction"] == 1:
+        colors[i] = "magenta"
+
+rotation_fig = fpl.Figure((3, 1), size=(1200, 300))
+angles_top_plot = rotation_fig[0, 0].add_line(
+    data=rotation_info["rotation_angle"],
+    thickness=1,
+    colors=list(colors.values()),
+)
+
+region_selector = angles_top_plot.add_linear_region_selector()
+zoomed_init = region_selector.get_selected_data()
+zoomed_x = rotation_fig[1, 0].add_line(zoomed_init)
+
+selector = angles_top_plot.add_linear_selector()
+
+selection_boundaries = region_selector.get_selected_indices()
+sliced_dff = dff[selection_boundaries[0] : selection_boundaries[-1]]
+
+dff_lines = rotation_fig[2, 0].add_line_stack(
+    np.asarray(sliced_dff).T[is_cell],
+    cmap="jet",
+    thickness=1,
+    separation=1,
+)
+
+
+@region_selector.add_event_handler("selection")
+def slice_dff_array(ev):
+    global zoomed_x
+    selected_data = ev.get_selected_data()
+    rotation_fig[1, 0].remove_graphic(zoomed_x)
+    zoomed_x = rotation_fig[1, 0].add_line(selected_data)
+    rotation_fig[1, 0].auto_scale()
+
+    global dff_lines
+    global sliced_dff
+    selection_boundaries = ev.get_selected_indices()
+    sliced_dff = dff[selection_boundaries[0] : selection_boundaries[-1]]
+
+    rotation_fig[2, 0].clear()
+    dff_lines = rotation_fig[2, 0].add_line_stack(
+        np.asarray(sliced_dff).T[is_cell],
+        cmap="jet",
+        thickness=1,
+        separation=1,
+    )
+    rotation_fig[2, 0].auto_scale()
+
+    fig_single_trace[0, 0].clear()
+    fig_single_trace[0, 0].add_line(
+        data=np.asarray(sliced_dff).T[idx],
+        thickness=2,
+        cmap="plasma",
+    )
+    fig_single_trace[0, 0].auto_scale()
+
+
+# Panel 2
+iw = fpl.ImageWidget(
+    registered[: len(rotation_info["rotation_angle"])], cmap="gnuplot2"
+)
+iw.show()
+contours_graphic = iw.figure[0, 0].add_line_collection(
+    contours, thickness=2, colors="green"
+)
+
+# Panel 3
+fig_single_trace = fpl.Figure()
+idx = 0
+single_line = fig_single_trace[0, 0].add_line(
+    data=np.asarray(sliced_dff).T[idx],
+    thickness=2,
+    cmap="plasma",
+)
+
+rotation_fig.show(maintain_aspect=False)
+
+
+def set_selected_component(ev):
+    xy = iw.figure[0, 0].map_screen_to_world(ev)[:-1]
+    global nearest
+    nearest = fpl.utils.get_nearest_graphics(xy, contours_graphic)[0]
+    contours_graphic.colors = "green"
+    nearest.colors = "w"
+
+    global idx
+    global single_line
+    idx = find_ROI(nearest)
+    fig_single_trace[0, 0].clear()
+    single_line = fig_single_trace[0, 0].add_line(
+        data=np.asarray(sliced_dff).T[idx],
+        thickness=2,
+        cmap="plasma",
+    )
+    fig_single_trace[0, 0].auto_scale()
+
+
+iw.figure.renderer.add_event_handler(set_selected_component, "click")
+selector.add_ipywidget_handler(iw.sliders["t"], step=1)
+
+
+def dashboard():
+    AppLayout(
+        header=rotation_fig.show(maintain_aspect=False),
+        left_sidebar=iw.show(),
+        right_sidebar=fig_single_trace.show(maintain_aspect=False),
+    )
+
+
+if __name__ == "__main__":
+    dashboard()