Add script for sbit mapping test

gemos/analysis/ana_cluster.py

+"""S-Bit cluster mapping analysis"""
+import argparse
+
+import pandas as pd
+import numpy as np
+
+import matplotlib.pyplot as plt
+import mplhep as hep
+
+
+def most_frequent(hits):
+    counter = 0
+    num = hits[0]
+
+    for i in hits:
+        curr_frequency = hits.count(i)
+        if curr_frequency > counter:
+            counter = curr_frequency
+            num = i
+
+    return num
+
+
+def filter_and_plot(filename, ieta, plot_dir, use_size):
+    tag = filename.split("/")[-1].split(".txt")[0]
+    df = pd.read_csv(filename, sep="\t")
+    df = df.drop(["index"], axis=1)
+    df = df.values.flatten()
+    df = pd.DataFrame(data=df, columns=["CL"])
+    df["CL_address"] = df.CL & 0b111111111
+    df["CL_partition"] = (df.CL // 2 ** 9) & 0b111
+    df["CL_size"] = (df.CL // 2 ** 12) & 0b111
+    df = df.drop(["CL"], axis=1)
+    valid = df["CL_address"] != 511
+
+    plt.style.use(hep.style.CMS)
+    validDf = df[valid]
+
+    etaDf = validDf[validDf["CL_partition"] == ieta]
+    hit = []
+    for address, part, size in etaDf.values.tolist():
+        if use_size:
+            for i in range(size + 1):
+                hit.append(address + i)
+        else:
+            hit.append(address)
+    plt.xlabel("sbit address")
+    plt.ylabel("entries")
+    histlabel = "Eta Partition %d :: Entries:%d :: Max in %d" % (
+        ieta,
+        len(hit),
+        most_frequent(hit),
+    )
+    hist = plt.hist(hit, bins=192, range=[0, 192], label=histlabel)
+    plt.ylim([0, max(hist[0]) * 1.5])
+    plt.legend(fontsize=20, loc="upper left")
+    plt.savefig("%s/%s_test_plot_%d.png" % (plot_dir, tag, ieta))
+    plt.clf()
+
+
+def main():
+    parser = argparse.ArgumentParser(description="sbit cluster plotter with pandas")
+    parser.add_argument("--fileName", "-filename", required=True, help="data file name")
+    parser.add_argument("--ieta", "-eta", type=int, default=0, help="eta partition to draw")
+    parser.add_argument(
+        "--plot_dir", "-plot_dir", required=True, help="directory name to save plot"
+    )
+    parser.add_argemuet("--use_size", "-use_size", type=bool, default=False, action="store_true")
+    args = parser.parse_args()
+
+    filter_and_plot(args.fileName, args.ieta, args.plot_dir, args.use_size)