Sedlik Labs

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=====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()

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