From a6ce47cfaa750a3900a3c4a02eb13bc4a371adc0 Mon Sep 17 00:00:00 2001
From: Sball03 <123109497+Sball03@users.noreply.github.com>
Date: Tue, 24 Oct 2023 15:20:40 -0600
Subject: [PATCH] Add files via upload

Tool for automating the measurement data in XDC template sheets
---
 SDR_V2.py | 134 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 134 insertions(+)
 create mode 100644 SDR_V2.py

diff --git a/SDR_V2.py b/SDR_V2.py
new file mode 100644
index 0000000..f617e46
--- /dev/null
+++ b/SDR_V2.py
@@ -0,0 +1,134 @@
+import pandas as pd
+from openpyxl import load_workbook
+import numpy as np
+from openpyxl.utils import column_index_from_string #(row,column) to column index formula = ((r - 1) * 12 + c) + 1 maybe use df.iat for finding the values
+
+#helper functions | start:
+def find_first_blank(df, col_index, start_row):
+    # Select the part of the series starting from the given row
+    series_part = df.iloc[start_row:, col_index]
+    
+    # Find the index of the first NaN (blank) value
+    blank_index = series_part.index[series_part.isnull()].min()
+
+    return blank_index
+
+def extract_num(s):
+    """
+    Extracts the number from the end of a string.
+
+    Args:
+    - s (str): The input string.
+
+    Returns:
+    - int: The extracted number if present, None otherwise.
+    """
+    i = len(s) - 1
+    while i >= 0 and s[i].isdigit():
+        i -= 1
+
+    if i < len(s) - 1:
+        return int(s[i+1:])
+    else:
+        return None
+#helper functions | end
+
+#constants that can be changed with config
+time_col_name = "Time [s]"
+time_col_index = 1 #zero-indexed
+data_cols = "B:CU"
+
+#user input | star:
+XDC_file = input("Enter the XDC sheet filename: ").strip()
+
+    #ask for number of assays
+number_of_assays = int(input("Enter the number of assays you would like to load: ").strip())
+
+    #ask for assay 1 -- n file paths
+assay_file_list = []
+for i in range(number_of_assays):
+    assay_file_list.append(input(f"Enter the filename for assay{i + 1}: ").strip())
+#user inout | end:
+
+#read sample information | start:
+sample_info = pd.read_excel(
+    XDC_file,
+    header = None,
+    sheet_name = "Sample",
+    skiprows = 1,
+    usecols = "A:D"
+)
+#read sample information | end
+
+#generate dataframes | start:
+dataframe_list = []
+
+for i in range(number_of_assays):
+    raw = pd.read_excel(assay_file_list[i])
+    locations = (raw.where(raw == time_col_name).stack().index.tolist()) #used to locate where the data starts
+    blank = pd.DataFrame()
+    for j in range(len(locations)): #this loop is for sheets with multiple data sets
+        num_skiprows = locations[j][0] + 2 
+        num_read_rows = (find_first_blank(raw, time_col_index, locations[j][0]) - locations[j][0] - 1)
+        read_cols = data_cols
+        temp = pd.read_excel(
+            assay_file_list[i],
+            header = None, 
+            skiprows = num_skiprows,
+            nrows = num_read_rows,
+            usecols = read_cols
+        )
+        blank = pd.concat([blank,temp])
+    dataframe_list.append(blank)
+#generate dataframes | end
+
+#build final dataframe | start:
+output = pd.DataFrame()
+current_measurement = -1
+for i in range(len(sample_info)):
+    #extracting the information from the df
+    sample_id = sample_info.iat[i,0]
+    row = int(sample_info.iat[i,1])
+    column = int(sample_info.iat[i,2])
+    assay_id = sample_info.iat[i,3]
+    
+    #processing info
+    assay_read_col = (row - 1) * 12 + column + 1
+    assay_num = extract_num(assay_id) - 1
+    working_df = dataframe_list[assay_num].iloc[:, [0,assay_read_col]].copy() #time and value cols
+    
+    
+    
+    #signal label
+    signals = []
+    num_rows_per_signal = int(len(working_df) / len(locations))
+    for j in range(len(locations)):
+        for k in range(num_rows_per_signal):
+            signals.append(f"Signal{j + 1}")
+    working_df.insert(0, "Signal ID", signals)
+    
+    #sample label
+    sample_ids = [sample_id] * len(working_df)
+    working_df.insert(0, "Sample ID", sample_ids)
+
+    #measurement label
+    measurement_ids = []
+    for j in range(len(working_df)):
+        current_measurement += 1
+        measurement_ids.append(f"Measurement{current_measurement}")
+    working_df.insert(0, "Measurement ID", measurement_ids)
+    standard_cols = ['Measurement ID', 'Sample ID', 'Signal ID', 'Time', 'Value']
+    working_df.columns = standard_cols
+    #adding working df to output
+    output = pd.concat([output, working_df], ignore_index=True)
+#build final dataframe | end
+
+#write to xdc sheet
+book = load_workbook(XDC_file)
+with pd.ExcelWriter(XDC_file, engine = 'openpyxl') as writer:
+    writer.book = book
+
+    # Write the cleaned data to the output Excel sheet without overwriting
+    output.to_excel(writer, sheet_name = "Measurement", index = False, header = False, startrow = 1 , startcol = 0 )
+
+