Merge pull request #30 from ALPHA-g-Experiment/plots

Fix plot axis limits

bin/chronobox_timestamps.py

@@ -2,6 +2,7 @@
 
 import argparse
 import matplotlib.pyplot as plt
+import numpy as np
 import polars as pl
 
 parser = argparse.ArgumentParser(
@@ -26,18 +27,18 @@
  pl.col("leading_edge"),
 )
 
-_, t_edges, _ = plt.hist(df["chronobox_time"], bins=args.t_bins)
-t_bin_width = t_edges[1] - t_edges[0]
-
-plt.xlabel("Chronobox time [s]")
-plt.ylabel("Counts")
-
+t_max = args.t_max if args.t_max < float("inf") else df["chronobox_time"].max()
+t_edges, t_bin_width = np.linspace(args.t_min, t_max, args.t_bins + 1, retstep=True)
 text = "\n".join(
  [
  r"$\bf{Bin\ width:}$" + f" {t_bin_width:.2E} s",
  r"$\bf{Number\ of\ hits:}$" + f" {len(df)}",
  ]
 )
+
+plt.hist(df["chronobox_time"], bins=t_edges)
+plt.xlabel("Chronobox time [s]")
+plt.ylabel("Counts")
 plt.figtext(0.005, 0.01, text, fontsize=6)
 plt.tight_layout()
 

bin/trg_scalers.py

@@ -35,10 +35,9 @@
 df = pl.read_csv(args.trg_scalers_csv, comment_prefix="#").filter(
  pl.col("trg_time").is_between(args.t_min, args.t_max)
 )
-# All histograms should have the same binning
-_, t_edges = np.histogram(df["trg_time"], bins=args.t_bins)
-t_bin_width = t_edges[1] - t_edges[0]
 
+t_max = args.t_max if args.t_max < float("inf") else df["trg_time"].max()
+t_edges, t_bin_width = np.linspace(args.t_min, t_max, args.t_bins + 1, retstep=True)
 text = r"$\bf{Bin\ width:}$" + f" {t_bin_width:.2E} s"
 plt.figtext(0.005, 0.01, text, fontsize=8)
 

bin/vertices.py

@@ -66,26 +66,32 @@
 fig = plt.figure(figsize=(19, 10), dpi=100)
 
 ax = fig.add_subplot(231)
+z_edges, z_bin_width = np.linspace(
+ args.z_min, args.z_max, args.z_bins + 1, retstep=True
+)
+ax.hist(df["reconstructed_z"], bins=z_edges)
 ax.set(xlabel="z [m]", ylabel="Number of vertices")
-ax.hist(df["reconstructed_z"], bins=args.z_bins)
 
 ax = fig.add_subplot(232)
+t_max = args.t_max if args.t_max < float("inf") else df["trg_time"].max()
+t_edges, t_bin_width = np.linspace(args.t_min, t_max, args.t_bins + 1, retstep=True)
+ax.hist(df["trg_time"], bins=t_edges)
 ax.set(xlabel="TRG time [s]", ylabel="Number of vertices")
-ax.hist(df["trg_time"], bins=args.t_bins)
 
 ax = fig.add_subplot(233)
-ax.set(xlabel="TRG time [s]", ylabel="z [m]")
-_, t_edges, z_edges, mesh = ax.hist2d(
- df["trg_time"], df["reconstructed_z"], bins=[args.t_bins, args.z_bins], cmin=1
+_, _, _, mesh = ax.hist2d(
+ df["trg_time"], df["reconstructed_z"], bins=[t_edges, z_edges], cmin=1
 )
-t_bin_width = t_edges[1] - t_edges[0]
-z_bin_width = z_edges[1] - z_edges[0]
+ax.set(xlabel="TRG time [s]", ylabel="z [m]")
 cbar = fig.colorbar(mesh)
 cbar.set_label("Number of vertices", rotation=270, labelpad=15)
 
 ax = fig.add_subplot(234)
+r_edges, r_bin_width = np.linspace(
+ args.r_min, args.r_max, args.r_bins + 1, retstep=True
+)
+hist, _, _ = ax.hist(df["r"], bins=r_edges)
 ax.set(xlabel="r [m]", ylabel="Number of vertices")
-hist, r_edges, _ = ax.hist(df["r"], bins=args.r_bins)
 ax = ax.twinx()
 ax.set(yticklabels=[])
 norm = hist / (math.pi * (r_edges[1:] ** 2 - r_edges[:-1] ** 2))
@@ -97,18 +103,17 @@
 )
 
 ax = fig.add_subplot(235)
+phi_edges, phi_bin_width = np.linspace(
+ args.phi_min, args.phi_max, args.phi_bins + 1, retstep=True
+)
+ax.hist(df["phi"], bins=phi_edges)
 ax.set(xlabel="phi [rad]", ylabel="Number of vertices")
-ax.hist(df["phi"], bins=args.phi_bins)
 
 axc = fig.add_subplot(236)
 axc.set(xlabel="x [m]", ylabel="y [m]")
 axc.set_aspect("equal")
-hist, phi_edges, r_edges = np.histogram2d(
- df["phi"], df["r"], bins=[args.phi_bins, args.r_bins]
-)
+hist, _, _ = np.histogram2d(df["phi"], df["r"], bins=[phi_edges, r_edges])
 hist[hist < 1] = np.nan
-phi_bin_width = phi_edges[1] - phi_edges[0]
-r_bin_width = r_edges[1] - r_edges[0]
 axc.set_xlim(-r_edges[-1], r_edges[-1])
 axc.set_ylim(-r_edges[-1], r_edges[-1])
 ax = fig.add_subplot(236, projection="polar")