improve all plots

comparison_plot.py

@@ -6,12 +6,13 @@ import numpy as np
 import pandas as pd
 from matplotlib import pyplot as plt
 from matplotlib.axes import Axes
-from matplotlib.axis import XTick, YTick
+from matplotlib.axis import YTick
 from matplotlib.collections import QuadMesh
 from matplotlib.colors import LogNorm
 from matplotlib.figure import Figure
 from matplotlib.patches import Polygon
 from numpy import inf
+from scipy.stats import norm
 
 from halo_vis import get_comp_id
 from paths import base_dir
@@ -102,27 +103,25 @@ def plot_comparison_hist2d(ax: Axes, file: Path, property: str):
                 rows.append(row)
         df = pd.concat(rows, axis=1).T
         print(df)
-    if property == "Mvir":
-        stds = []
-        means = []
+    if property in ["Mvir","Vmax"]:
+        percentiles = []
         for rep_row in range(num_bins):
             rep_x_left = bins[rep_row]
             rep_x_right = bins[rep_row] + 1
             rep_bin = (rep_x_left < df[x_col]) & (df[x_col] < rep_x_right)
             rep_values = df.loc[rep_bin][y_col] / df.loc[rep_bin][x_col]
-            if len(rep_bin) < 30:
+            if len(rep_values) < 10:
+                percentiles.append([np.nan, np.nan, np.nan])
                 continue
-            mean = rep_values.mean()
-            std = rep_values.std()
-            means.append(mean)
-            stds.append(std)
-        means = np.array(means)
-        stds = np.array(stds)
-        args = {"color": "C2", "zorder": 10}
-        ax.fill_between(bins, means - stds, means + stds, alpha=0.2, **args)
-        ax.plot(bins, means + stds, alpha=0.5, **args)
-        ax.plot(bins, means - stds, alpha=0.5, **args)
-        # ax_scatter.plot(bins, stds, label=f"{file.stem}")
+            percentiles.append(np.quantile(rep_values, [norm.cdf(-1), norm.cdf(0), norm.cdf(1)]))
+
+        percentiles = np.asarray(percentiles)
+        print(percentiles.shape)
+        args = {"color": "C1", "zorder": 10}
+        # ax.fill_between(bins, percentiles[::, 0], percentiles[::, 2], alpha=0.1, **args)
+        ax.plot(bins, percentiles[::, 0], alpha=0.9, **args)
+        ax.plot(bins, percentiles[::, 1], alpha=0.9, **args)
+        ax.plot(bins, percentiles[::, 2], alpha=0.9, **args)
 
     if property in vmaxs:
         vmax = vmaxs[property]
@@ -135,6 +134,7 @@ def plot_comparison_hist2d(ax: Axes, file: Path, property: str):
         df[y_col] / df[x_col],
         bins=(bins, np.linspace(0, 2, num_bins)),
         norm=LogNorm(vmax=vmax),
+        cmap="gray_r",
         rasterized=True,
     )
     # ax.plot([rep_x_left, rep_x_left], [mean - std, mean + std], c="C1")
@@ -151,7 +151,7 @@ def plot_comparison_hist2d(ax: Axes, file: Path, property: str):
     ax.set_xlim(min(df[x_col]), max(df[y_col]))
 
     ax.plot(
-        [min(df[x_col]), max(df[y_col])], [1, 1], linewidth=1, color="C1", zorder=10
+        [min(df[x_col]), max(df[y_col])], [1, 1], linewidth=1, color="C0", zorder=10, linestyle="dotted"
     )
 
     return x_col, y_col
@@ -179,7 +179,6 @@ def plot_comparison_hist(ax: Axes, file: Path, property: str, m_min=None, m_max=
     else:
         bins = num_bins
     if property == "match":
-        histtype = "step"
         labels = {
             (-inf, 30): "$M<30$",
             (None, None): "$M$",
@@ -198,7 +197,7 @@ def plot_comparison_hist(ax: Axes, file: Path, property: str, m_min=None, m_max=
     else:
         patches: List[Polygon]
         hist_val, bin_edges, patches = ax.hist(
-            df[property], bins=bins, histtype=histtype, label=label, density=density
+            df[property], bins=bins, histtype="step", label=label, density=density
         )
 
 

matplotlibrc

@@ -5,4 +5,6 @@ font.serif     : Computer Modern Roman
 font.sans-serif: Computer Modern Sans Serif
 font.monospace : Computer Modern Typewriter
 
+lines.linewidth: 1.2 # 1.5 is the default
+
 axes.prop_cycle: cycler('color', ['3f90da', 'ffa90e', 'bd1f01', '94a4a2', '832db6', 'a96b59', 'e76300', 'b9ac70', '717581', '92dadd'])

spectra_plot.py

@@ -1,13 +1,15 @@
 import itertools
 from pathlib import Path
 from sys import argv
+from typing import List
 
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 from matplotlib.axes import Axes
-from matplotlib.axis import XTick, YTick
+from matplotlib.axis import XTick
 from matplotlib.figure import Figure
+from matplotlib.lines import Line2D
 
 from paths import base_dir
 from utils import figsize_from_page_fraction, waveforms
@@ -38,7 +40,7 @@ colors = [f"C{i}" for i in range(10)]
 
 
 def spectra_data(
-    waveform: str, resolution_1: int, resolution_2: int, Lbox: int, time: str
+        waveform: str, resolution_1: int, resolution_2: int, Lbox: int, time: str
 ):
     dir = base_dir / f"spectra/{waveform}_{Lbox}"
 
@@ -86,7 +88,7 @@ def create_plot(mode):
         3,
         sharex=True,
         sharey=True,
-        figsize=figsize_from_page_fraction(columns=2),
+        figsize=figsize_from_page_fraction(columns=2, height_to_width=.5),
     )
     crossings = np.zeros((len(waveforms), len(combination_list)))
     for i, waveform in enumerate(waveforms):
@@ -125,7 +127,7 @@ def create_plot(mode):
             ax.grid(color="black", linestyle=":", linewidth=0.5, alpha=0.5)
 
             for j, res in enumerate(
-                resolutions[:-1] if mode == "cross" else resolutions
+                    resolutions[:-1] if mode == "cross" else resolutions
             ):
                 ax.axvline(
                     k0 * res,
@@ -213,22 +215,35 @@ def create_plot(mode):
                 crossing_value = end_pcross[crossing_index]  # and here
                 crossings[i][j] = crossing_value
 
-
             ax_end.set_xlim(right=k0 * resolutions[-1])
             ax_end.set_ylim(0.8, 1.02)
         if bottom_row:
-            # ax_z1.legend()
-            ax_ics.legend(loc="lower left")
+            if mode == "power":
+                ax_ics.legend(loc="lower left")
+            else:
+                lines: List[Line2D] = ax_ics.get_lines()
+                half_lines1 = []
+                half_lines2 = []
+                for line in lines:
+                    if line.get_label().startswith("128"):
+                        half_lines1.append(line)
+                    else:
+                        half_lines2.append(line)
+
+                ax_ics.legend(handles=half_lines1, loc="lower left")
+                ax_z1.legend(handles=half_lines2, loc="lower left")
+
         if not bottom_row:
             last_xtick: XTick = ax_ics.yaxis.get_major_ticks()[0]
             last_xtick.set_visible(False)
 
         # fig.suptitle(f"Cross Spectra {time}") #Not needed for paper
         # fig.tight_layout()
-    print(crossings)
-    crossings_df = pd.DataFrame(crossings, columns=combination_list, index=waveforms)
-    # print(crossings_df.to_markdown())
-    print(crossings_df.to_latex())
+    if mode=="cross":
+        print(crossings)
+        crossings_df = pd.DataFrame(crossings, columns=combination_list, index=waveforms)
+        # print(crossings_df.to_markdown())
+        print(crossings_df.to_latex())
     fig.tight_layout()
     fig.subplots_adjust(wspace=0, hspace=0)