73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
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import torch
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import scipy
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import os
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import matplotlib.pyplot as plt
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import numpy as np
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import glob
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import logging
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# this code calculates the mean number of Gabor patches inside a stimulus for each class
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logging.basicConfig(filename='AngularAvrg.txt', filemode='w', format='%(message)s', level=logging.INFO)
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avg_avg_size: list = []
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n_contours = 0
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x_range = [140, 940]
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y_range = [140, 940]
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for i in range(10):
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path = f"/data_1/kk/StimulusGeneration/Alicorn/Angular/Ang0{i}0_n10000"
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files = glob.glob(path + os.sep + "*.mat")
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n_files = len(files)
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print(f"Going through {n_files} contour files...")
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logging.info(f"Going through {n_files} contour files...")
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varname=f"Table_intr_crn0{i}0"
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varname_dist=f"Table_intr_crn0{i}0_dist"
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for i_file in range(n_files):
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# get path, basename, suffix...
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full = files[i_file]
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path, file = os.path.split(full)
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base, suffix = os.path.splitext(file)
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# load file
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print(full)
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mat = scipy.io.loadmat(full)
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if "dist" in full:
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posori = mat[varname_dist]
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else:
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posori = mat[varname]
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sec_dim_sizes = [] #[posori[i][0].shape[1] for i in range(posori.shape[0])]
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for s in range(posori.shape[0]):
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# Extract the entry
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entry = posori[s][0]
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# Get the x and y coordinates
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x = entry[1]
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y = entry[2]
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# Find the indices of the coordinates that fall within the specified range
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idx = np.where((x >= x_range[0]) & (x <= x_range[1]) & (y >= y_range[0]) & (y <= y_range[1]))[0]
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# Calculate the size of the second dimension while only considering the coordinates within the specified range
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sec_dim_size = len(idx)
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# Append the size to the list
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sec_dim_sizes.append(sec_dim_size)
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avg_size = np.mean(sec_dim_sizes)
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print(f"Average 2nd dim of posori: {avg_size}")
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logging.info(f"Average 2nd dim of posori: {avg_size}")
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avg_avg_size.append(avg_size)
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n_contours += posori.shape[0]
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print(f"...overall {n_contours} contours so far.")
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logging.info(f"...overall {n_contours} contours so far.")
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# calculate avg number Gabors over whole condition
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overall = np.mean(avg_avg_size)
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print(f"OVERALL average 2nd dim of posori: {overall}")
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logging.info(f"OVERALL average 2nd dim of posori: {overall}")
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