Hi,
I have another question about fitting. I have fit data with a polynomial function. Now I need to know how to get the minimum y value with the corresponding x value of the fit data. I have shown my code below, it is about the bold code at the bottom where things go wrong.
I did not succeed in getting the first 2 columns out of the FitNLCurve1 worksheet.
import originpro as op
import csv
import numpy as np
import time
import pandas as pd
#dont pay attention to this
n = 1
lijst_xc = np.zeros((n,2))
print(lijst_xc)
for i in range(n):
time.sleep(1)
# Create a new worksheet
wks = op.new_sheet()
# Specify the path to the CSV file
#csv_file_path = 'C:\\Users\\PC-043012\\Desktop\\GuySimon\\test.csv'
csv_file_path = f'C:\\Users\\PC-043012\\Desktop\\GuySimon\\sd\\sd_dpbs_2\\{str(i+1)}.csv'
# Load only the 4th and 5th columns from the CSV file into the worksheet
def load_csv_data(csv_file_path):
x_values = []
y_values = []
with open(csv_file_path, 'r') as file:
csvreader = csv.reader(file)
for row in csvreader:
# Extract the 4th and 5th columns and convert them to float
x_value = float(row[3]) # Assuming the 4th column index is 3 (0-indexed)
y_value = float(row[4]) # Assuming the 5th column index is 4 (0-indexed)
# Add the values to the lists
x_values.append(x_value)
y_values.append(y_value)
# Add the accumulated values to the worksheet
wks.from_list(0, x_values, 'X')
wks.from_list(1, y_values, 'Y')
# Load data from the CSV file
load_csv_data(csv_file_path)
model = op.NLFit('Poly')
model.set_data(wks, 0, 1)
model.fit()
r, c = model.report(True)
wReport=op.find_sheet('w', r)
wReport.activate()
sheet = op.find_sheet('w', '[Boo5]FitNLCurve1')
Thank you in advance!
GHof