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| import sys | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| # To find txt files , needs to be run in proposal before final center point is found | |
| """ | |
| with open("ProposalNetwork/proposals/conditions.txt", "a") as f: | |
| # Redirect the standard output to the file | |
| sys.stdout = f | |
| # Your print statements here | |
| print(f"{torch.median(z)},{gt_cube.center[2].item()}") | |
| # Reset the standard output | |
| sys.stdout = sys.__stdout__ | |
| """ | |
| # Conditions | |
| x_cond = [] | |
| y_cond = [] | |
| # Read data from the file | |
| with open("ProposalNetwork/proposals/conditions_x.txt", "r") as file: | |
| for line in file: | |
| # Split each line by comma | |
| parts = line.strip().split(",") | |
| # Extract x and y values | |
| x_val = float(parts[0].strip()) | |
| y_val = float(parts[1].strip()) | |
| # Append x and y values to the arrays | |
| x_cond.append(x_val) | |
| y_cond.append(y_val) | |
| # System of equations in matrix form | |
| A = np.array([[x, 1] for x in x_cond]) | |
| # Solve for coefficients | |
| coefficients, _, _, _ = np.linalg.lstsq(A, y_cond, rcond=None) | |
| print(coefficients) | |
| # Reset the standard output | |
| sys.stdout = sys.__stdout__ | |
| plt.figure() | |
| plt.scatter(x_cond,y_cond) | |
| plt.savefig("ProposalNetwork/proposals/x_values_to_find.png", dpi=300, bbox_inches='tight') | |
| plt.close() | |