random_sample_gen

import numpy as np
from random import randint
#randint generates random integers

def generate_random_samples(raw_file, sample_size, num_samples, output_prefix):
  #reads a raw file, generates random 3D samples, and saves them as raw images.
    #raw_file: Path to the raw file 
    #sample_size: Size of the 3D sample 
    #num_samples: Number of random samples to generate.
    #output_prefix: Prefix for the output filenames.

  with open(raw_file, 'rb') as f:
    data = np.fromfile(f, dtype=np.uint8)
    data = data.reshape(1000, 1000, 1000)

  #check if sample size is valid
  if sample_size[0] > 1000 or sample_size[1] > 1000 or sample_size[2] > 1000:
    raise ValueError("Sample size cannot be greater than input dimensions")

  for i in range(num_samples):
    #generate random starting coordinates for the sample
    x_min = randint(0, 1000 - sample_size[0])
    y_min = randint(0, 1000 - sample_size[1])
    z_min = randint(0, 1000 - sample_size[2])

    sample = data[x_min:x_min + sample_size[0], y_min:y_min + sample_size[1], z_min:z_min + sample_size[2]]

    #save the sample as a raw image
    output_file = f"{output_prefix}_{i}.raw"
    with open(output_file, 'wb') as f:
      sample.tofile(f)

#define input and output parameters
raw_file = "sequence_8bit_scaled.raw" #make sure is in same folder as code
sample_size = (200, 200, 50)          #adjust as needed
num_samples = 10                      #adjust as needed
output_prefix = "sample"              #adjust as needed

generate_random_samples(raw_file, sample_size, num_samples, output_prefix)
print(f"Generated {num_samples} random samples and saved them as raw images.")