add excel merge code into two sheets

.gitignore

@@ -26,3 +26,4 @@ yarn-error.log*
 
 src/components/testData.json
 public/world-110m.json
+public/india-states.json

scripts/merge_csv.py

@@ -2,16 +2,18 @@ import glob
 import pandas as pd
 import openpyxl
 import os
-from platform import system
+from tqdm import tqdm
+import platform
+from PyQt5.QtWidgets import QApplication, QWidget, QFileDialog
 
-rootdir = os.getcwd()
+def consolidate_and_perform_calculations(curdir, rootdir, path_delim, validation_file):
-
-def consolidate(curdir):
 
     print(os.path.split(curdir)[1])
     
     # list all csv files only  
-    csv_files = glob.glob(curdir + '/*.{}'.format('csv'))
+    csv_files = glob.glob(curdir + path_delim + '/*.{}'.format('csv'))
+    if len(csv_files) == 0:
+        print("no csv files in the sub folder")
     # print(csv_files)
 
     df_csv_append = pd.DataFrame()
@@ -20,45 +22,100 @@ def consolidate(curdir):
 
     # merge the CSV files
     for file in csv_files:
-        # print(file)
         if first:
             df_csv_append = pd.read_csv(file)
-            colname = file.split('.')[0].split('/')[-1] #file.split('.')[0]
+            colname = file.split('.')[0].split(path_delim)[-1] #file.split('.')[0]
-            # print(colname)
             df_csv_append.rename(columns={'ca': colname}, inplace = True)
             df_csv_append = df_csv_append.drop(['1'], axis=1)
             first = False
         else:
             df = pd.read_csv(file)
-            colname = file.split('.')[0].split('/')[-1] #file.split('.')[0]
+            colname = file.split('.')[0].split(path_delim)[-1] #file.split('.')[0]
-            # print(colname)
             df.rename(columns={'ca': colname}, inplace = True)
             df = df.drop(['1'], axis=1)
             df_csv_append = df_csv_append.merge(df, on='tv')
     
-    # print(df_csv_append[df_csv_append['tv'].between(300, 700)])
-
     df_csv_append = df_csv_append[df_csv_append['tv'].between(300, 700)]
 
-    df_csv_append.rename(columns={'tv': "123_tv"}, inplace = True)
+    wavelength_col = "123_tv" # to make sorting columns simpler
+
+    df_csv_append.rename(columns={'tv': wavelength_col}, inplace = True)
 
     df_csv_append = df_csv_append.reindex(sorted(df_csv_append.columns), axis=1)
 
-    outfile = rootdir + "/" + os.path.split(curdir)[1] + "_Merged.xlsx"
+    outfile = rootdir + path_delim + os.path.split(curdir)[1] + "_analysis.xlsx"
 
     # df_csv_append.to_excel(outfile, sheet_name="merged_data", index=False)
-
     # df_csv_append.to_csv("D8 Merged.csv", index=False)
 
-    writer = pd.ExcelWriter(outfile, engine = 'xlsxwriter')
+    # calculations
-    df_csv_append.to_excel(writer, sheet_name = 'x1')
+    df_427 = df_csv_append.loc[(df_csv_append[wavelength_col] >= 427) & (df_csv_append[wavelength_col] < 428)]
-    df_csv_append.to_excel(writer, sheet_name = 'x2')
+
+    df_555 = df_csv_append.loc[(df_csv_append[wavelength_col] >= 555) & (df_csv_append[wavelength_col] < 556)]
+
+    df_validation = pd.read_excel(validation_file)
+
+    df_analysis = df_427.iloc[0] + df_555.iloc[0]
+    # print(df_analysis)
+    # print(min(df_csv_append[0:5]))
+
+    midpoint1 = 427
+    midpoint2 = 555
+    bandwidth1 = 25
+    bandwidth2 = 10
+
+    df = df_analysis.rename(columns = {"NM":"Wavelength","CA":"Absorbance"}, inplace = True)
+
+    # 427 nm range
+    df1 = df[ (df['Wavelength'] > (midpoint1-bandwidth1)) & (df['Wavelength'] < (midpoint1+bandwidth1)) ]
+
+    # 555 nm range
+    df2 = df[ (df['Wavelength'] > (midpoint2-bandwidth2)) & (df['Wavelength'] < (midpoint2+bandwidth2)) ]
+    
+    procData.append({"Sample ID": sampleID, 
+                     "max_427": round(df1["Absorbance"].max() , 3),
+                     "wvmax_427": round(df1.at[df1["Absorbance"].idxmax(),"Wavelength"], 3),
+                     "avg_427": round(df1["Absorbance"].mean(), 3),
+                     "max_555": round(df2["Absorbance"].max(), 3),
+                     "wvmax_555": round(df2.at[df2["Absorbance"].idxmax(),"Wavelength"], 3),
+                     "avg_555": round(df2["Absorbance"].mean(), 3),
+                     "ratio_max": round(df2["Absorbance"].max()/df1["Absorbance"].max(), 3),
+                     "ratio_avg": round(df2["Absorbance"].mean()/df1["Absorbance"].mean(), 3)
+                    })
+
+    writer = pd.ExcelWriter(outfile, engine = 'openpyxl')
+    df_analysis.to_excel(writer, sheet_name = 'analysis', index=False)
+    df_csv_append.to_excel(writer, sheet_name = 'merged_data', index=False)
     writer.close()
 
+
+sampleID = 1
+allDF = pd.DataFrame()
+procData = []
+
+
 if __name__ == "__main__":
-    for file in os.listdir(rootdir):
+    environment = "dev" # dev, QC
-    curdir = os.path.join(rootdir, file)
+    rootdir = os.getcwd()
-    if os.path.isdir(d):
+    validation_file = rootdir + '/validation.xlsx'
-        # os.chdir(d)
+    if environment != "dev":
-        consolidate(curdir)
+        app = QApplication([])
-        
+
+        # window = QWidget()
+        # layout = QVBoxLayout(window)
+        rootdir = QFileDialog.getExistingDirectory(None, 'Select main folder')
+        choose_validation_file = QFileDialog.getOpenFileName(None, "Select validation excel")
+        validation_file = choose_validation_file[0]
+    
+    path_delim = ''
+    if platform.system() == 'Darwin':
+        path_delim = '/'
+    else:
+        path_delim = '\\'
+    
+    for file in tqdm(os.listdir(rootdir)):
+        curdir = os.path.join(rootdir, file)
+        if os.path.isdir(curdir):
+            # os.chdir(d)
+            consolidate_and_perform_calculations(curdir, rootdir, path_delim, validation_file)
+