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--- namespace:getting_data [2025/11/06 22:22] – created admin
+++ namespace:getting_data [2025/11/06 22:26] (current) – [Gil/Dylan getting started to collect data] admin
@@ Line 1: / Line 1: @@
 {{ :namespace:moria_database_manual.pdf |}}
+=====Gil/Dylan getting started to collect data======
+######## GIL’s SCRIPT ############
+from galadriel.control.exp_setup import Setup\\
+from galadriel.control.optimizations import FRODO_class\\
+from galadriel.analysis import image_calculations\\
+# Math\\
+import numpy as np\\
+import time\\
+from datetime import datetime\\
+import io\\
+from PIL import Image\\
+import os\\
+\\
+#%%\\
+class rasterrunner():\\
+   def __init__(self):\\
+       super().__init__()\\
+       self.setup = Setup()\\
+       print(self.setup.acquisition_dict)\\
+       print(self.setup.actuator_dict)\\
+       if self.setup.actuator_dict: print(self.setup.input_map)\\
+       print('')\\
+#%%  ESTABLISH NAMES FOR ALL THE STUFF I WANT TO TALK TO.\\
+opt = rasterrunner()\\
+#%%\\
+opt.setup.query.clear_query()\\
+lsn = opt.setup.query.get_last_shot_number()\\
+\\
+value_query_dict = {'metadata' : {'experiment' :['20250304_especcalibration']}}#,\\
+#value_query_dict = {'metadata' : {'experiment' :['20250304_especcalibration']}}#,\\
+\\
+range_query_dict = {'metadata' : {'shot_number' : [lsn-200, lsn]}}    #198579#198066\\
+\\
+#First round:shit archive; 198060, 198573]\\
+opt.setup.query.query_data_range(range_query_dict)\\
+raw_res, proc_res = opt.setup.query.run_query(fetch_related_data = False, make_dict = True)\\
+#%%\\
+dataout = []\\
+\\
+##### MY SCRIPT #########
+#!/usr/bin/env python3
+"""
+A script to create overlaid histograms comparing the peak signal distribution
+of all seven focus metrics for all four filtered channels (Cu, Al, Fe, Ni).
+"""
+import sys
+import os
+import matplotlib.pyplot as plt
+import seaborn as sns
+import numpy as np
+# --- USER CONFIGURATION ---
+# Use the confirmed path to the directory containing the 'exp_setup.py' file.
+PATH_TO_PROJECT_FOLDER = '/home/dahlked/galadriel/galadriel/control'
+# The folder where the new plots will be saved.
+SAVE_DIRECTORY = '/home/dahlked/envs/MetricPeakOscilloscopeDistributionPlots'
+# -----------------------------
+# --- Path Correction Block (Do not change) ---
+sys.path.insert(0, PATH_TO_PROJECT_FOLDER)
+# ---------------------------------------------
+try:
+    from exp_setup import Setup
+except (ImportError, KeyError) as e:
+    print(f"Import Error: Could not import Setup. Error: {e}")
+    sys.exit()
+class rasterrunner():
+    def __init__(self):
+        super().__init__()
+        print("Initializing connection...")
+        self.setup = Setup()
+        print("Connection successful.")
+    def plot_all_filter_histograms(self):
+        """
+        Loops through all metrics, aggregates peak data, and creates
+        overlaid "step" histograms for all four channels.
+        """
+        os.makedirs(SAVE_DIRECTORY, exist_ok=True)
+        print(f"Plots will be saved to: {SAVE_DIRECTORY}")
+        metrics_to_plot = [
+            'Intensity only',
+            'Variance only',
+            'Laplacian only',
+            'Brenner Gradient',
+            'Spot size',
+            'Top 50 pixels',
+            'Sobel Tenengrad Operator'
+        ]
+        # Use a dictionary to store all peak data, organized by metric
+        all_metrics_data = {metric: [[] for _ in range(4)] for metric in metrics_to_plot}
+        for metric in metrics_to_plot:
+            print(f"\n--- Processing Metric: {metric} ---")
+            self.setup.query.clear_query()
+            value_query_dict = {
+                'metadata': {'process': ['FRODO']},
+                'data': {'Metric Used': [metric]}
+            }
+            self.setup.query.query_data_value(value_query_dict)
+            raw_res, proc_res = self.setup.query.run_query(fetch_related_data=True, make_dict=True)
+            if 'FRODO' not in proc_res or not proc_res['FRODO']:
+                print(f"No shots found for metric '{metric}'. Skipping.")
+                continue
+            matching_shots = sorted(list({doc['metadata']['shot_number'] for doc in proc_res['FRODO']}))
+            # Aggregate peak data for the current metric
+            for shot in matching_shots:
+                for i in range(1, 5):
+                    ch_name, ch_key = f'oscilloscope_ch{i}', f'channel_{i}'
+                    scope_doc = next((doc for doc in raw_res.get(ch_name, []) if 'data' in doc and doc['metadata']['shot_number'] == shot), None)
+                    if scope_doc:
+                        trace_data = scope_doc['data'].get(ch_key)
+                        if trace_data:
+                            all_metrics_data[metric][i-1].append(np.max(trace_data))
+        # --- Create and Save Overlaid Plots ---
+        print("\n--- Generating Overlaid Histogram Plots for All Filters ---")
+        sns.set_theme(style="whitegrid")
+        # Plot for Copper Filter (Channel 1)
+        plt.figure(figsize=(10, 7))
+        for metric in metrics_to_plot:
+            peak_data = all_metrics_data[metric][0] # Index 0 for Channel 1
+            if peak_data:
+                plt.hist(peak_data, bins='auto', label=metric, histtype='step', linewidth=1.5)
+        plt.title('Metric Comparison for Copper (Cu) Filter')
+        plt.xlabel('Peak Voltage (V)'); plt.ylabel('Number of Shots'); plt.legend()
+        filename_cu = os.path.join(SAVE_DIRECTORY, "Copper_Filter_Metric_Comparison.png")
+        plt.savefig(filename_cu); plt.close()
+        print(f"Saved plot: {filename_cu}")
+        # Plot for Aluminum Filter (Channel 2)
+        plt.figure(figsize=(10, 7))
+        for metric in metrics_to_plot:
+            peak_data = all_metrics_data[metric][1] # Index 1 for Channel 2
+            if peak_data:
+                plt.hist(peak_data, bins='auto', label=metric, histtype='step', linewidth=1.5)
+        plt.title('Metric Comparison for Aluminum (Al) Filter')
+        plt.xlabel('Peak Voltage (V)'); plt.ylabel('Number of Shots'); plt.legend()
+        filename_al = os.path.join(SAVE_DIRECTORY, "Aluminum_Filter_Metric_Comparison.png")
+        plt.savefig(filename_al); plt.close()
+        print(f"Saved plot: {filename_al}")
+        # NEW: Plot for Iron Filter (Channel 3)
+        plt.figure(figsize=(10, 7))
+        for metric in metrics_to_plot:
+            peak_data = all_metrics_data[metric][2] # Index 2 for Channel 3
+            if peak_data:
+                plt.hist(peak_data, bins='auto', label=metric, histtype='step', linewidth=1.5)
+        plt.title('Metric Comparison for Iron (Fe) Filter')
+        plt.xlabel('Peak Voltage (V)'); plt.ylabel('Number of Shots'); plt.legend()
+        filename_fe = os.path.join(SAVE_DIRECTORY, "Iron_Filter_Metric_Comparison.png")
+        plt.savefig(filename_fe); plt.close()
+        print(f"Saved plot: {filename_fe}")
+        # NEW: Plot for Nickel Filter (Channel 4)
+        plt.figure(figsize=(10, 7))
+        for metric in metrics_to_plot:
+            peak_data = all_metrics_data[metric][3] # Index 3 for Channel 4
+            if peak_data:
+                plt.hist(peak_data, bins='auto', label=metric, histtype='step', linewidth=1.5)
+        plt.title('Metric Comparison for Nickel (Ni) Filter')
+        plt.xlabel('Peak Voltage (V)'); plt.ylabel('Number of Shots'); plt.legend()
+        filename_ni = os.path.join(SAVE_DIRECTORY, "Nickel_Filter_Metric_Comparison.png")
+        plt.savefig(filename_ni); plt.close()
+        print(f"Saved plot: {filename_ni}")
+if __name__ == "__main__":
+    opt = rasterrunner()
+    opt.plot_all_filter_histograms()