diff --git a/ana/esa25eventdisplay/hcal_ch_mapping.csv b/ana/esa25eventdisplay/hcal_ch_mapping.csv
new file mode 100644
index 000000000..70a87df9b
--- /dev/null
+++ b/ana/esa25eventdisplay/hcal_ch_mapping.csv
@@ -0,0 +1,49 @@
+iLink,Ch,SiPM,Layer,Bar,End
+1,36,0,1,0,0
+1,37,1,1,1,0
+1,38,2,1,2,0
+1,39,3,1,3,0
+1,40,4,2,0,0
+1,41,5,2,1,0
+1,42,6,2,2,0
+1,43,7,2,3,0
+1,45,8,3,0,0
+1,46,9,3,1,0
+1,47,10,3,2,0
+1,48,11,3,3,0
+1,49,12,4,0,0
+1,50,13,4,1,0
+1,51,14,4,2,0
+1,52,15,4,3,0
+1,54,16,5,0,0
+1,55,17,5,1,0
+1,56,18,5,2,0
+1,57,19,5,3,0
+1,58,20,6,0,0
+1,59,21,6,1,0
+1,60,22,6,2,0
+1,61,23,6,3,0
+0,22,24,6,0,1
+0,23,25,6,1,1
+0,24,26,6,2,1
+0,25,27,6,3,1
+0,18,28,5,0,1
+0,19,29,5,1,1
+0,20,30,5,2,1
+0,21,31,5,3,1
+0,13,32,4,0,1
+0,14,33,4,1,1
+0,15,34,4,2,1
+0,16,35,4,3,1
+0,9,36,3,0,1
+0,10,37,3,1,1
+0,11,38,3,2,1
+0,12,39,3,3,1
+0,4,40,2,0,1
+0,5,41,2,1,1
+0,6,42,2,2,1
+0,7,43,2,3,1
+0,0,44,1,0,1
+0,1,45,1,1,1
+0,2,46,1,2,1
+0,3,47,1,3,1
diff --git a/ana/esa25eventdisplay/hcal_event_display.py b/ana/esa25eventdisplay/hcal_event_display.py
new file mode 100644
index 000000000..8d5ae5986
--- /dev/null
+++ b/ana/esa25eventdisplay/hcal_event_display.py
@@ -0,0 +1,119 @@
+import pandas as pd
+import numpy as np
+import hist
+import matplotlib.pyplot as plt
+from pathlib import Path
+import argparse
+import os
+
+parser = argparse.ArgumentParser()
+parser.add_argument('data', type=Path, help='decoded CSV file from rogue-decoder')
+parser.add_argument('outputdir', type=Path, help='plot output directory')
+parser.add_argument('runnumber', help='run number')
+parser.add_argument('nsamples', help='number of samples')
+parser.add_argument('n_events', help='number of events to be plotted')
+args = parser.parse_args()
+
+mapping_file = open("hcal_ch_mapping.csv","r")
+
+if not os.path.isdir(args.outputdir):
+    raise Exception("Output directory does not exist")
+
+chmap = {}
+
+for line in mapping_file:
+    line = line[:-1]
+    s = line.split(",")
+    if s[0] == "iLink":
+        continue
+    #print(line)
+    chmap[(int(s[3]),int(s[4]), int(s[5]))] = (int(s[0]),int(s[1]))
+
+
+samples = pd.read_csv(args.data)
+
+timestamps = list(set(samples['timestamp']))
+print(timestamps)
+
+#bunchCounts =[t & 0xFF for t in timestamps]
+#pulseId =[t >> 8 for t in timestamps]
+
+
+
+#events = sorted(list(set(samples['event'])))
+#print(events)
+
+event_i = 0
+
+for timestamp in timestamps:
+    if int(args.n_events) != -1 and event_i >= int(args.n_events):
+        print("Quitting, exceeded n_events")
+        break
+
+    print("Plotting event_i = " + str(event_i))
+
+    fig, axs = plt.subplots(4,6, figsize=(12,10))
+    
+    x = range(0,8)
+
+    event = samples[samples["timestamp"] == timestamp]
+
+    for layer in range(1,7):
+        for bar in range(0,4):
+            ilink_right,ch_right = chmap[(layer,bar,0)]
+            if ilink_right == 1:
+                ch_right -= 36
+            ilink_left,ch_left  = chmap[(layer,bar,1)] 
+            if ilink_left == 1:
+                ch_left -= 36
+
+            adc_left = []
+            adc_right = []
+
+            for i in range(0, int(args.nsamples)):
+                    #row_right = event[event["timestamp"] & 0xFF == bunchCount]
+                    row_right = event[event["i_sample"] == i]
+                    print(row_right)
+                    row_right = row_right[row_right["channel"] == str(ch_right)]
+                    print(row_right)
+                    row_right = row_right[row_right["i_link"] == ilink_right]
+                    print(row_right)
+                    print(timestamp)
+                    print(ilink_right)
+                    print(ch_right)
+                    adc_right.append(int(row_right['adc']))
+
+                    #row_left = samples[samples["timestamp"] & 0xFF == bunchCount]
+                    row_left = event[event["i_sample"] == i]
+                    row_left = row_left[row_left["channel"] == str(ch_left)]
+                    row_left = row_left[row_left["i_link"] == ilink_left]
+                    adc_left.append(int(row_left['adc']))
+
+
+            axs[3-bar, layer-1].plot(x, adc_left, color="red", marker="*", label="Left")
+            axs[3-bar, layer-1].plot(x, adc_right, color="blue", marker="*", label="Right")
+
+            axs[3-bar, layer-1].set_xlim(0,int(args.nsamples)-1)
+            axs[3-bar, layer-1].set_ylim(0,1023)
+            if bar == 0:
+                axs[3-bar, layer-1].set_xlabel("L"+str(layer))
+            else:
+                axs[3-bar,layer-1].set_xticklabels([])
+            
+            if layer == 1:
+                axs[3-bar,layer-1].set_ylabel("Bar "+str(bar))
+            else:
+                axs[3-bar,layer-1].set_yticklabels([])
+
+            if layer == 6 and bar == 3:
+                axs[3-bar,layer-1].legend()
+
+
+
+    fig.suptitle("Run " + args.runnumber + " event " + str(event_i))
+    plt.tight_layout()
+    #plt.show()
+    plt.savefig(str(args.outputdir)+"/run_"+args.runnumber+"_event_"+str(event_i)+".png",dpi=300)
+
+
+    event_i += 1
diff --git a/ana/esa25eventdisplay/hcal_hist.py b/ana/esa25eventdisplay/hcal_hist.py
new file mode 100644
index 000000000..4740137e6
--- /dev/null
+++ b/ana/esa25eventdisplay/hcal_hist.py
@@ -0,0 +1,179 @@
+import pandas as pd
+import numpy as np
+import hist
+import matplotlib.pyplot as plt
+from pathlib import Path
+import argparse
+import os
+
+parser = argparse.ArgumentParser()
+parser.add_argument('data', type=Path, help='decoded CSV file from rogue-decoder')
+parser.add_argument('outputdir', type=Path, help='plot output directory')
+parser.add_argument('runnumber', help='run number')
+parser.add_argument('nsamples', help='number of samples')
+parser.add_argument('n_events', help='number of events to be plotted')
+args = parser.parse_args()
+
+mapping_file = open("hcal_ch_mapping.csv","r")
+
+if not os.path.isdir(args.outputdir):
+    raise Exception("Output directory does not exist")
+
+chmap = {}
+
+for line in mapping_file:
+    line = line[:-1]
+    s = line.split(",")
+    if s[0] == "iLink":
+        continue
+    #print(line)
+    chmap[(int(s[3]),int(s[4]), int(s[5]))] = (int(s[0]),int(s[1]))
+
+
+samples = pd.read_csv(args.data)
+
+timestamps = list(set(samples['timestamp']))
+
+hists_x = {}
+hists_y = {}
+maxadc = {}
+for k in chmap.keys():
+    hists_x[k] = []
+    hists_y[k] = []
+    maxadc[k] = []
+
+
+event_i = 0
+for timestamp in timestamps:
+    if int(args.n_events) != -1 and event_i >= int(args.n_events):
+        print("Quitting, exceeded n_events")
+        break
+
+    print("Plotting event_i = " + str(event_i))
+    
+    x = range(0,8)
+
+    event = samples[samples["timestamp"] == timestamp]
+
+    for layer in range(1,7):
+        for bar in range(0,4):
+            ilink_right,ch_right = chmap[(layer,bar,0)]
+            if ilink_right == 1:
+                ch_right -= 36
+            ilink_left,ch_left  = chmap[(layer,bar,1)] 
+            if ilink_left == 1:
+                ch_left -= 36
+
+            adc_left = []
+            adc_right = []
+
+            for i in range(0, int(args.nsamples)):
+                    row_right = event[event["i_sample"] == i]
+                    row_right = row_right[row_right["channel"] == str(ch_right)]
+                    row_right = row_right[row_right["i_link"] == ilink_right]
+                    adc = int(row_right['adc'])
+                    adc_right.append(adc)
+                    hists_x[(layer,bar,0)].append(i)
+                    hists_y[(layer,bar,0)].append(adc)
+
+                    row_left = event[event["i_sample"] == i]
+                    row_left = row_left[row_left["channel"] == str(ch_left)]
+                    row_left = row_left[row_left["i_link"] == ilink_left]
+                    adc = int(row_left['adc'])
+                    adc_left.append(adc)
+                    hists_x[(layer,bar,1)].append(i)
+                    hists_y[(layer,bar,1)].append(adc)
+
+            maxadc[(layer,bar,0)].append(max(adc_right))
+            maxadc[(layer,bar,1)].append(max(adc_left))
+
+
+            """
+            axs[3-bar, layer-1].plot(x, adc_left, color="red", marker="*", label="Left")
+            axs[3-bar, layer-1].plot(x, adc_right, color="blue", marker="*", label="Right")
+
+            axs[3-bar, layer-1].set_xlim(0,int(args.nsamples)-1)
+            axs[3-bar, layer-1].set_ylim(0,1023)
+            if bar == 0:
+                axs[3-bar, layer-1].set_xlabel("L"+str(layer))
+            else:
+                axs[3-bar,layer-1].set_xticklabels([])
+            
+            if layer == 1:
+                axs[3-bar,layer-1].set_ylabel("Bar "+str(bar))
+            else:
+                axs[3-bar,layer-1].set_yticklabels([])
+
+            if layer == 6 and bar == 3:
+                axs[3-bar,layer-1].legend()
+            """
+
+    event_i += 1
+
+fig, axs = plt.subplots(4,6, figsize=(12,10))
+for layer in range(1,7):
+    for bar in range(0,4):
+            axs[3-bar, layer-1].hist2d(hists_x[(layer,bar,0)],hists_y[(layer,bar,0)])
+
+            if bar == 0:
+                axs[3-bar, layer-1].set_xlabel("L"+str(layer))
+            if layer == 1:
+                axs[3-bar,layer-1].set_ylabel("Bar "+str(bar))
+
+            if layer == 6 and bar == 3:
+                axs[3-bar,layer-1].legend()
+
+fig.suptitle("Run " + args.runnumber + ", right SiPMs")
+plt.tight_layout()
+plt.savefig(str(args.outputdir)+"/hist2d_right_run_"+args.runnumber+".png",dpi=300)
+plt.clf()
+fig, axs = plt.subplots(4,6, figsize=(12,10))
+for layer in range(1,7):
+    for bar in range(0,4):
+            axs[3-bar, layer-1].hist2d(hists_x[(layer,bar,1)],hists_y[(layer,bar,1)])
+
+            if bar == 0:
+                axs[3-bar, layer-1].set_xlabel("L"+str(layer))
+            if layer == 1:
+                axs[3-bar,layer-1].set_ylabel("Bar "+str(bar))
+            if layer == 6 and bar == 3:
+                axs[3-bar,layer-1].legend()
+
+fig.suptitle("Run " + args.runnumber + ", left SiPMs")
+plt.tight_layout()
+plt.savefig(str(args.outputdir)+"/hist2d_left_run_"+args.runnumber+".png",dpi=300)
+plt.clf()
+fig, axs = plt.subplots(4,6, figsize=(12,10))
+for layer in range(1,7):
+    for bar in range(0,4):
+            axs[3-bar, layer-1].hist(maxadc[(layer,bar,0)])
+
+            if bar == 0:
+                axs[3-bar, layer-1].set_xlabel("L"+str(layer))
+            if layer == 1:
+                axs[3-bar,layer-1].set_ylabel("Bar "+str(bar))
+
+            if layer == 6 and bar == 3:
+                axs[3-bar,layer-1].legend()
+
+fig.suptitle("Run " + args.runnumber + ", maxADC, right SiPMs")
+plt.tight_layout()
+plt.savefig(str(args.outputdir)+"/maxadc_right_run_"+args.runnumber+".png",dpi=300)
+plt.clf()
+fig, axs = plt.subplots(4,6, figsize=(12,10))
+for layer in range(1,7):
+    for bar in range(0,4):
+            axs[3-bar, layer-1].hist(maxadc[(layer,bar,1)])
+
+            if bar == 0:
+                axs[3-bar, layer-1].set_xlabel("L"+str(layer))
+            if layer == 1:
+                axs[3-bar,layer-1].set_ylabel("Bar "+str(bar))
+
+            if layer == 6 and bar == 3:
+                axs[3-bar,layer-1].legend()
+
+fig.suptitle("Run " + args.runnumber + ", maxADC, left SiPMs")
+plt.tight_layout()
+plt.savefig(str(args.outputdir)+"/maxadc_left_run_"+args.runnumber+".png",dpi=300)
+