device precision

scripts/device_precision.py

@@ -0,0 +1,57 @@
+import pandas as pd
+import numpy as np
+import os
+import re
+import xlsxwriter
+from datetime import datetime
+
+
+curdir = os.getcwd()
+path_delim = '/'
+
+df = pd.read_excel(curdir + path_delim + "data" + path_delim + "data_03_12_2023_11_25.xlsx", sheet_name="Sheet1")
+
+texts_to_check = ['Tar', 'KM']
+df['solution'] = df['name'].str.extract(f"({'|'.join(texts_to_check)})", flags=re.IGNORECASE)
+df['solution'] = df['solution'].replace({'Tar': 'Tartrazine', 'KM': 'KMnO4'}, regex=True)
+
+def extract_numbers(s):
+    match = re.match(r'\d+', s)
+    if match:
+        return int(match.group())
+    else:
+        return None
+
+df["concentration"] =  df['name'].apply(extract_numbers)
+df['absorbance'] = df.apply(lambda row: row['led2Average'] if row['solution'] == 'Tartrazine' else row['led1Average'], axis=1)
+output_filename = f'precision_{datetime.today().strftime("%d_%m_%Y_%H_%M")}.xlsx'
+writer = pd.ExcelWriter(output_filename, engine = 'xlsxwriter')
+
+df_precision = df[["deviceId", "solution", "concentration", "led1Average", "led2Average", "absorbance"]].groupby(["deviceId", "solution", "concentration"]).describe()["absorbance"][["count", "min", "max"]]
+# df_precision = df_precision.reset_index(drop=True)
+df_precision['precision'] = df_precision['max'] - df_precision['min']
+threshold = 0.02
+df_precision['result'] = ['Fail' if diff > threshold else 'Pass' for diff in df_precision['precision']]
+
+device_results = {}
+for index, group_df in df_precision.groupby(level=[0, 1, 2]):
+    soln = index[1]
+    concen = index[2]
+    result_values = group_df['result'].values
+
+    if index[0] not in device_results:
+        device_results[index[0]] = "Pass"
+    else:
+        result = 'Fail' if 'Fail' in result_values else 'Pass'
+        if result == 'Fail':
+            device_results[index[0]] = 'Fail'
+    
+print(device_results)
+df_device_results = pd.DataFrame(list(device_results.items()), columns=['Device', 'Result'])
+
+
+df.to_excel(writer, sheet_name="in")
+df_precision.to_excel(writer, sheet_name="precision")
+df_device_results.to_excel(writer, sheet_name="device_results")
+
+writer.close()