Add Prism style

Author: schilling40

scripts/figures/plot_fig2.py

@@ -9,6 +9,7 @@
 from skimage.segmentation import find_boundaries
 
 from util import literature_reference_values, SYNAPSE_DIR_ROOT
+from util import prism_style, prism_cleanup_axes
 
 png_dpi = 300
 FILE_EXTENSION = "png"
@@ -122,6 +123,7 @@ def fig_02c(save_path, plot=False, all_versions=False):
     """Scatter plot showing the precision, recall, and F1-score of SGN (distance U-Net, manual),
     IHC (distance U-Net, manual), and synapse detection (U-Net).
     """
+    prism_style()
     # precision, recall, f1-score
     sgn_unet = [0.887, 0.88, 0.884]
     sgn_annotator = [0.95, 0.849, 0.9]
@@ -172,7 +174,7 @@ def fig_02c(save_path, plot=False, all_versions=False):
         offset = 0.08  # horizontal shift for scatter separation
 
         # Plot
-        plt.figure(figsize=(8, 5))
+        fig, ax = plt.subplots(figsize=(8, 5))
 
         main_label_size = 22
         sub_label_size = 16
@@ -192,11 +194,12 @@ def fig_02c(save_path, plot=False, all_versions=False):
         plt.yticks(fontsize=main_tick_size)
         plt.ylabel("Value", fontsize=main_label_size)
         plt.ylim(0.76, 1)
-        plt.legend(loc="upper center", bbox_to_anchor=(0.5, 1.11),
-                   ncol=3, fancybox=True, shadow=False, framealpha=0.8, fontsize=legendsize)
+        plt.legend(loc="lower right",
+                   fontsize=legendsize)
         plt.grid(axis="y", linestyle="--", alpha=0.5)
 
         plt.tight_layout()
+        prism_cleanup_axes(ax)
 
         if ".png" in save_path:
             plt.savefig(save_path, bbox_inches="tight", pad_inches=0.1, dpi=png_dpi)

scripts/figures/plot_fig3.py

@@ -5,7 +5,6 @@
 
 import imageio.v3 as imageio
 from glob import glob
-from pathlib import Path
 
 import matplotlib
 import matplotlib.pyplot as plt
@@ -14,7 +13,7 @@
 from matplotlib import cm, colors
 
 from flamingo_tools.s3_utils import BUCKET_NAME, create_s3_target
-from util import sliding_runlength_sum, frequency_mapping, SYNAPSE_DIR_ROOT, to_alias
+from util import sliding_runlength_sum, frequency_mapping, prism_style, prism_cleanup_axes, SYNAPSE_DIR_ROOT
 
 # INPUT_ROOT = "/home/pape/Work/my_projects/flamingo-tools/scripts/M_LR_000227_R/scale3"
 INPUT_ROOT = "/mnt/vast-nhr/projects/nim00007/data/moser/cochlea-lightsheet/frequency_mapping/M_LR_000227_R/scale3"
@@ -181,7 +180,8 @@ def fig_03c_rl(save_path, plot=False):
         plt.close()
 
 
-def fig_03c_octave(tonotopic_data, save_path, plot=False, use_alias=True):
+def fig_03c_octave(tonotopic_data, save_path, plot=False, use_alias=True, trendlines=False):
+    prism_style()
     ihc_version = "ihc_counts_v4c"
     tables = glob(os.path.join(SYNAPSE_DIR_ROOT, ihc_version, "ihc_count_M_LR*.tsv"))
     assert len(tables) == 4, len(tables)
@@ -207,16 +207,55 @@ def fig_03c_octave(tonotopic_data, save_path, plot=False, use_alias=True):
     result["x_pos"] = result["octave_band"].map(band_to_x)
 
     fig, ax = plt.subplots(figsize=(8, 4))
+    trend_dict = {}
     for name, grp in result.groupby("cochlea"):
         ax.scatter(grp["x_pos"], grp["value"], label=name, s=60, alpha=0.8)
 
+        if trendlines:
+            x_positions = grp["x_pos"]
+            sorted_idx = np.argsort(x_positions)
+            x_sorted = np.array(x_positions)[sorted_idx]
+            y_sorted = np.array(grp["value"])[sorted_idx]
+            trend_dict[name] = {"x_sorted": x_sorted,
+                                "y_sorted": y_sorted,
+                                }
+
+    if trendlines:
+        def get_trendline_values(trend_dict):
+            x_sorted = [trend_dict[k]["x_sorted"] for k in trend_dict.keys()][0]
+            y_sorted_all = [trend_dict[k]["y_sorted"] for k in trend_dict.keys()]
+            y_sorted = []
+            for num in range(len(x_sorted)):
+                y_sorted.append(np.mean([y[num] for y in y_sorted_all]))
+            return x_sorted, y_sorted
+
+        # Trendline left
+        x_sorted, y_sorted = get_trendline_values(trend_dict)
+
+        trend, = ax.plot(
+            x_sorted,
+            y_sorted,
+            linestyle="dotted",
+            color="grey",
+            alpha=0.7
+        )
+
+        # trendline_legend = ax.legend(handles=[trend], loc='lower center')
+        # trendline_legend = ax.legend(
+        #     handles=[trend],
+        #     labels=["Trendline"],
+        #     loc="upper left"
+        # )
+        # # Add the legend manually to the Axes.
+        # ax.add_artist(trendline_legend)
+
     ax.set_xticks(range(len(bin_labels)))
     ax.set_xticklabels(bin_labels)
     ax.set_xlabel("Octave band (kHz)")
 
-    ax.set_ylabel("Average Ribbon Synapse Count per IHC")
-    ax.set_title("Ribbon synapse count per octave band")
+    ax.set_ylabel("Average Ribbon Synapse Count per IHC", fontsize=10)
     plt.legend(title="Cochlea")
+    prism_cleanup_axes(ax)
 
     if ".png" in save_path:
         plt.savefig(save_path, bbox_inches="tight", pad_inches=0.1, dpi=png_dpi)
@@ -314,7 +353,7 @@ def main():
     # fig_03c_rl(save_path=os.path.join(args.figure_dir, f"fig_03c_runlength.{FILE_EXTENSION}"), plot=args.plot)
     fig_03c_octave(tonotopic_data=tonotopic_data,
                    save_path=os.path.join(args.figure_dir, f"fig_03c_octave.{FILE_EXTENSION}"),
-                   plot=args.plot)
+                   plot=args.plot, trendlines=True)
 
     # Panel D: Spatial distribution of SGN sub-types.
     # fig_03d_fraction(save_path=os.path.join(args.figure_dir, f"fig_03d_fraction.{FILE_EXTENSION}"), plot=args.plot)

scripts/figures/plot_fig4.py

@@ -8,7 +8,7 @@
 import pandas as pd
 from flamingo_tools.s3_utils import BUCKET_NAME, create_s3_target
 
-from util import frequency_mapping  # , literature_reference_values
+from util import frequency_mapping, prism_style, prism_cleanup_axes  # , literature_reference_values
 
 # from statsmodels.nonparametric.smoothers_lowess import lowess
 
@@ -117,6 +117,7 @@ def fig_04c(chreef_data, save_path, plot=False, plot_by_side=False, use_alias=Tr
     # cochlea = ["M_LR_000144_L", "M_LR_000145_L", "M_LR_000151_R"]
     # alias = ["c01", "c02", "c03"]
     # sgns = [7796, 6119, 9225]
+    prism_style()
 
     # TODO have central function for alias for all plots?
     if use_alias:
@@ -132,27 +133,25 @@ def fig_04c(chreef_data, save_path, plot=False, plot_by_side=False, use_alias=Tr
     x = np.arange(len(alias))
 
     # Plot
-    plt.figure(figsize=(8, 5))
+    fig, ax = plt.subplots(figsize=(5, 5))
 
     main_label_size = 20
     sub_label_size = 16
     main_tick_size = 16
-    legendsize = 16
+    legendsize = 12
 
     if plot_by_side:
-        plt.scatter(x, sgns_left, label="Left", marker="o", s=80)
-        plt.scatter(x, sgns_right, label="Right", marker="x", s=80)
+        plt.scatter(x, sgns_left, label="Injected", marker="o", s=80)
+        plt.scatter(x, sgns_right, label="Non-Injected", marker="x", s=80)
     else:
         plt.scatter(x, sgns, label="SGN count", marker="o", s=80)
 
     # Labels and formatting
     plt.xticks(x, alias, fontsize=sub_label_size)
     plt.yticks(fontsize=main_tick_size)
     plt.ylabel("SGN count per cochlea", fontsize=main_label_size)
-    plt.ylim(4000, 13800)
-    plt.legend(loc="best", fontsize=sub_label_size)
-    plt.legend(loc="upper center", bbox_to_anchor=(0.5, 1.11),
-               ncol=3, fancybox=True, shadow=False, framealpha=0.8, fontsize=legendsize)
+    plt.ylim(4000, 15800)
+    plt.legend(loc="upper right", fontsize=legendsize)
 
     xmin = -0.5
     xmax = len(alias) - 0.5
@@ -172,12 +171,14 @@ def fig_04c(chreef_data, save_path, plot=False, plot_by_side=False, use_alias=Tr
     lower_y = sgn_value - 1.96 * sgn_std
 
     plt.hlines([lower_y, upper_y], xmin, xmax, colors=["C1" for _ in range(2)])
-    plt.text(1.5, upper_y + 100, "healthy cochleae (95% confidence interval)",
-             color="C1", fontsize=main_tick_size, ha="center")
+    plt.text(2, upper_y + 200, "untreated cochleae\n(95% confidence interval)",
+             color="C1", fontsize=14, ha="center")
     plt.fill_between([xmin, xmax], lower_y, upper_y, color="C1", alpha=0.05, interpolate=True)
 
     plt.tight_layout()
 
+    prism_cleanup_axes(ax)
+
     if ".png" in save_path:
         plt.savefig(save_path, bbox_inches="tight", pad_inches=0.1, dpi=png_dpi)
     else:
@@ -192,6 +193,7 @@ def fig_04c(chreef_data, save_path, plot=False, plot_by_side=False, use_alias=Tr
 def fig_04d(chreef_data, save_path, plot=False, plot_by_side=False, intensity=False, gerbil=False, use_alias=True):
     """Transduction efficiency per cochlea.
     """
+    prism_style()
     if use_alias:
         alias = [COCHLEAE_DICT[k]["alias"] for k in chreef_data.keys()]
     else:
@@ -219,35 +221,34 @@ def fig_04d(chreef_data, save_path, plot=False, plot_by_side=False, intensity=Fa
     x = np.arange(len(alias))
 
     # Plot
-    plt.figure(figsize=(8, 5))
+    fig, ax = plt.subplots(figsize=(5, 5))
 
     main_label_size = 20
     sub_label_size = 16
     main_tick_size = 16
-    legendsize = 16
+    legendsize = 12
 
     label = "Intensity" if intensity else "Transduction efficiency"
 
     if plot_by_side:
-        plt.scatter(x, values_left, label="Left", marker="o", s=80)
-        plt.scatter(x, values_right, label="Right", marker="x", s=80)
+        plt.scatter(x, values_left, label="Injected", marker="o", s=80)
+        plt.scatter(x, values_right, label="Non-Injected", marker="x", s=80)
     else:
         plt.scatter(x, values, label=label, marker="o", s=80)
 
     # Labels and formatting
     plt.xticks(x, alias, fontsize=sub_label_size)
     plt.yticks(fontsize=main_tick_size)
     plt.ylabel(label, fontsize=main_label_size)
-    plt.legend(loc="best", fontsize=sub_label_size)
-    plt.legend(loc="upper center", bbox_to_anchor=(0.5, 1.11),
-               ncol=3, fancybox=True, shadow=False, framealpha=0.8, fontsize=legendsize)
+    plt.legend(loc="upper right", fontsize=legendsize)
     if not intensity:
         if gerbil:
             plt.ylim(0.3, 1.05)
         else:
             plt.ylim(0.5, 1.05)
 
     plt.tight_layout()
+    prism_cleanup_axes(ax)
 
     if ".png" in save_path:
         plt.savefig(save_path, bbox_inches="tight", pad_inches=0.1, dpi=png_dpi)
@@ -261,6 +262,7 @@ def fig_04d(chreef_data, save_path, plot=False, plot_by_side=False, intensity=Fa
 
 
 def fig_04e(chreef_data, save_path, plot, intensity=False, gerbil=False, use_alias=True, trendlines=False):
+    prism_style()
 
     result = {"cochlea": [], "octave_band": [], "value": []}
     for name, values in chreef_data.items():
@@ -295,15 +297,14 @@ def fig_04e(chreef_data, save_path, plot, intensity=False, gerbil=False, use_ali
     if intensity:
         band_label_offset_y = 0.09
     else:
-        band_label_offset_y = 0.07
+        band_label_offset_y = 0.09
         if gerbil:
             ax.set_ylim(0.05, 1.05)
         else:
             ax.set_ylim(0.45, 1.05)
 
     # Offsets within each octave band
     offset_map = {"L": -0.15, "R": 0.15}
-    sublabels = {"L": "L", "R": "R"}
 
     # Assign a color to each cochlea (ignoring side)
     cochleas = sorted({name_lr[:-1] for name_lr in result["cochlea"].unique()})
@@ -315,9 +316,6 @@ def fig_04e(chreef_data, save_path, plot, intensity=False, gerbil=False, use_ali
     # Track which cochlea names we have already added to the legend
     legend_added = set()
 
-    all_x_positions = []
-    all_x_labels = []
-
     trend_dict = {}
 
     for name_lr, grp in result.groupby("cochlea"):
@@ -352,10 +350,6 @@ def fig_04e(chreef_data, save_path, plot, intensity=False, gerbil=False, use_ali
                                    "side": side,
                                    }
 
-        # Store for sublabel ticks
-        all_x_positions.extend(x_positions)
-        all_x_labels.extend([sublabels[side]] * len(x_positions))
-
     if trendlines:
         def get_trendline_values(trend_dict, side):
             x_sorted = [trend_dict[k]["x_sorted"] for k in trend_dict.keys() if trend_dict[k]["side"] == side][0]
@@ -387,7 +381,7 @@ def get_trendline_values(trend_dict, side):
         trendline_legend = ax.legend(handles=[trend_l, trend_r], loc='lower center')
         trendline_legend = ax.legend(
             handles=[trend_l, trend_r],
-            labels=["Left", "Right"],
+            labels=["Injected", "Non-Injected"],
             loc="lower center",
             fontsize=legend_size,
             title="Trendlines"
@@ -398,10 +392,9 @@ def get_trendline_values(trend_dict, side):
     # Create combined tick positions & labels
     main_ticks = range(len(bin_labels))
     # add a final tick for label '>64k'
-    ax.set_xticks([pos + offset_map["L"] for pos in main_ticks[:-1]] +
-                  [pos + offset_map["R"] for pos in main_ticks[:-1]] +
-                  [pos for pos in main_ticks[-1:]])
-    ax.set_xticklabels(["L"] * len(main_ticks[:-1]) + ["R"] * len(main_ticks[:-1]) + [""], fontsize=sub_tick_label_size)
+    ax.set_xticks([pos + offset_map["L"] for pos in main_ticks] +
+                  [pos + offset_map["R"] for pos in main_ticks])
+    ax.set_xticklabels(["I"] * len(main_ticks) + ["N"] * len(main_ticks), fontsize=sub_tick_label_size)
 
     # Add main octave band labels above sublabels
     for i, label in enumerate(bin_labels):
@@ -416,11 +409,11 @@ def get_trendline_values(trend_dict, side):
         ax.set_title("Intensity per octave band (Left/Right)")
     else:
         ax.set_ylabel("Transduction Efficiency", fontsize=label_size)
-        ax.set_title("Transduction efficiency per octave band (Left/Right)")
 
     ax.legend(title="Cochlea", fontsize=legend_size)
 
     plt.tight_layout()
+    prism_cleanup_axes(ax)
 
     if ".png" in save_path:
         plt.savefig(save_path, bbox_inches="tight", pad_inches=0.1, dpi=png_dpi)
@@ -462,33 +455,33 @@ def main():
     fig_04d(chreef_data,
             save_path=os.path.join(args.figure_dir,  f"fig_04d_transduction.{FILE_EXTENSION}"),
             plot=args.plot, plot_by_side=True, use_alias=use_alias)
-    fig_04d(chreef_data,
-            save_path=os.path.join(args.figure_dir, f"fig_04d_intensity.{FILE_EXTENSION}"),
-            plot=args.plot, plot_by_side=True, intensity=True, use_alias=use_alias)
+    # fig_04d(chreef_data,
+    #         save_path=os.path.join(args.figure_dir, f"fig_04d_intensity.{FILE_EXTENSION}"),
+    #         plot=args.plot, plot_by_side=True, intensity=True, use_alias=use_alias)
 
     fig_04e(chreef_data,
             save_path=os.path.join(args.figure_dir, f"fig_04e_transduction.{FILE_EXTENSION}"),
             plot=args.plot, use_alias=use_alias, trendlines=True)
-    fig_04e(chreef_data,
-            save_path=os.path.join(args.figure_dir, f"fig_04e_intensity.{FILE_EXTENSION}"),
-            plot=args.plot, intensity=True, use_alias=use_alias)
+    # fig_04e(chreef_data,
+    #         save_path=os.path.join(args.figure_dir, f"fig_04e_intensity.{FILE_EXTENSION}"),
+    #         plot=args.plot, intensity=True, use_alias=use_alias)
 
     chreef_data_gerbil = get_chreef_data(animal="gerbil")
     fig_04d(chreef_data_gerbil,
             save_path=os.path.join(args.figure_dir, f"fig_04d_gerbil_transduction.{FILE_EXTENSION}"),
             plot=args.plot, plot_by_side=True, gerbil=True, use_alias=use_alias)
 
-    fig_04d(chreef_data_gerbil,
-            save_path=os.path.join(args.figure_dir, f"fig_04d_gerbil_intensity.{FILE_EXTENSION}"),
-            plot=args.plot, plot_by_side=True, intensity=True, use_alias=use_alias)
+    # fig_04d(chreef_data_gerbil,
+    #         save_path=os.path.join(args.figure_dir, f"fig_04d_gerbil_intensity.{FILE_EXTENSION}"),
+    #         plot=args.plot, plot_by_side=True, intensity=True, use_alias=use_alias)
 
     fig_04e(chreef_data_gerbil,
             save_path=os.path.join(args.figure_dir, f"fig_04e_gerbil_transduction.{FILE_EXTENSION}"),
             plot=args.plot, gerbil=True, use_alias=use_alias)
 
-    fig_04e(chreef_data_gerbil,
-            save_path=os.path.join(args.figure_dir, f"fig_04e_gerbil_intensity.{FILE_EXTENSION}"),
-            plot=args.plot, intensity=True, use_alias=use_alias)
+    # fig_04e(chreef_data_gerbil,
+    #         save_path=os.path.join(args.figure_dir, f"fig_04e_gerbil_intensity.{FILE_EXTENSION}"),
+    #         plot=args.plot, intensity=True, use_alias=use_alias)
 
 
 if __name__ == "__main__":