remove outdated exercise

Exercise2c/OUTDATED_process_image.py

@@ -1,27 +0,0 @@
-import os
-import sys
-
-# This module provides the magic_signature() function, safely and
-# securely calculated to provide invaluable signature of an image.
-
-def magic(fname):
-    n_threads = os.getenv('OMP_NUM_THREADS', '(unset)')
-    print(f"Worker {fname=} OMP_NUM_THREADS={n_threads}")
-
-    # We delay the import of numpy because we want to set OMP_NUM_THREADS.
-    # We delay the import of PIL in case is uses numpy internally.
-
-    import numpy as np
-    from PIL import Image
-
-    im = Image.open(fname)
-    try:
-        m = np.median(im, axis=2)
-    except np.AxisError:
-        return -1
-    n = (m @ m.T).mean()
-    return int(n)
-
-if __name__ == '__main__':
-    for fname in sys.argv[1:]:
-        print(f'{fname} → {magic(fname)}')

Exercise2c/OUTDATED_process_many_times.py

@@ -1,35 +0,0 @@
-import os
-import sys
-import time
-
-from process_multiple_images import process
-
-n_threads = ...
-n_processes = ...
-
-def measure_one(n_processes, n_threads, fnames):
-    result_fname = f'{n_processes:02}_{n_threads:02}.txt'
-
-    if os.path.exists(result_fname):
-        print(f'Skipping job with {n_processes} processes and {n_threads} threads, results file exists')
-        return
-
-    t0 = time.time()
-    process(n_processes, n_threads, fnames)
-    dt = time.time() - t0
-
-    print(f'Job with {n_processes} processes and {n_threads} threads/worker and {len(fnames)} jobs: {dt}')
-
-    with open(result_fname, 'wt') as results:
-        print(f'{n_processes:02} {n_threads:02} {dt}', file=results)
-
-def measure(n_processes, n_threads, fnames):
-    for n1 in n_processes:
-        for n2 in n_threads:
-            measure_one(n1, n2, fnames)
-
-if __name__ == '__main__':
-    measure(
-        [1, 2, 3, 4, 5, 6, 7, 8, 9],
-        [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11],
-        sys.argv[1:])

Exercise2c/OUTDATED_process_multiple_images.py

@@ -1,25 +0,0 @@
-import os
-import sys
-from multiprocessing import Pool as ProcessPool
-
-import process_image
-
-def process(n_processes, n_threads, fnames):
-    print(f"Controller with {n_processes} processes and {n_threads} threads / worker")
-
-    # The environment that is set in the parent is inherited by child workers,
-    # but here process_image import numpy, so we need to set the variable
-    # before process_image is imported.
-    os.environ['OMP_NUM_THREADS'] = str(n_threads)
-
-    with ProcessPool(n_processes) as p:
-        signatures = p.map(process_image.magic, fnames)
-    for fname, signature in zip(fnames, signatures):
-        print(f'{fname} → {signature}')
-
-if __name__ == '__main__':
-    n_processes = int(sys.argv[1])
-    n_threads = int(sys.argv[2])
-    fnames = sys.argv[3:]
-
-    process(n_processes, n_threads, fnames)

Exercise2c/README.md

@@ -1,20 +0,0 @@
-## Exercise 2c
-
-Processing images with simultaneous multiprocessing and multithreading.
-
-`process_image.py` processes a single image.
-It can be used as a script: `process_image.py foo.jpg`
-It is also an importable module. `process_image.magic("foo.jpg")`
-
-`process_multiple_images` uses `process_image` to process a series of images.
-It should be called as following:
-`process_multiple_images n_processes n_threads filename1.png filename2.png …`
-
-1. start a separate terminal window with `htop`: `gnome-terminal -- htop &`
-
-2. call `python process_multiple_images.py 2 2 images/*.png`
-
-You should see `htop` showing 4 threads (2 worked processes × 2 numpy threads).
-
-Play with different numbers of processes and threads.
-Which combination is optimum (fastest)?