Merge remote-tracking branch 'origin/development' into development

Author: gjbex

scientific_python_linux64_conda_specs.txt

@@ -41,3 +41,5 @@ to create it.  There is some material not covered in the presentation as well.
 * [`vpython`]: illustrations of using VPython for physics and mathematics animations.
 * [`cannon.ipynb`]: Jupyter notebook illustrating the use of numpy, scipy, sympy and
   bokeh.
+* [`manim`](manim): sample code for illustrating manim, a framework to create
+  mathematical animations.

source-code/README.md

@@ -42,9 +42,7 @@ def normalize(signal, ampl):
     arg_parser.add_argument('--out', action='store_true',
                             help='print signal to standard output')
     options = arg_parser.parse_args()
-    if options.specs_file:
-        pass
-    else:
+    if not options.specs_file:
         if len(options.freqs) != len(options.ampls):
             msg = '# error: {0:d} frequencies for {1:d} amplitudes\n'
             sys.stderr.write(msg.format(len(options.freqs),

source-code/birdsong/create_signal.py

@@ -13,22 +13,21 @@
     counter = 0
     try:
         densities = []
-        while (True):
+        while True:
             status, frame = capture.read()
-            if status:
-                counter += 1
-                nr_pixels = frame.shape[0]*frame.shape[1]
-                red_channel = frame[:, :, 0]
-                green_channel = frame[:, :, 1]
-                blue_channel = frame[:, :, 2]
-                densities.append((counter,
-                                  red_channel.sum()/nr_pixels,
-                                  green_channel.sum()/nr_pixels,
-                                  blue_channel.sum()/nr_pixels))
-                cv2.imshow('frame', frame)
-                if cv2.waitKey(1) & 0xFF == ord('q'):
-                    break
-            else:
+            if not status:
+                break
+            counter += 1
+            nr_pixels = frame.shape[0]*frame.shape[1]
+            red_channel = frame[:, :, 0]
+            green_channel = frame[:, :, 1]
+            blue_channel = frame[:, :, 2]
+            densities.append((counter,
+                              red_channel.sum()/nr_pixels,
+                              green_channel.sum()/nr_pixels,
+                              blue_channel.sum()/nr_pixels))
+            cv2.imshow('frame', frame)
+            if cv2.waitKey(1) & 0xFF == ord('q'):
                 break
         capture.release()
         cv2.destroyAllWindows()

source-code/diffusion_limited_aggregation.ipynb

@@ -25,15 +25,14 @@
     try:
         while True:
             status, frame = capture.read()
-            if status:
-                counter += 1
-                # frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-                if options.output:
-                    output.write(frame)
-                cv2.imshow('frame', frame)
-                if cv2.waitKey(1) & 0xFF == ord('q'):
-                    break
-            else:
+            if not status:
+                break
+            counter += 1
+            # frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+            if options.output:
+                output.write(frame)
+            cv2.imshow('frame', frame)
+            if cv2.waitKey(1) & 0xFF == ord('q'):
                 break
     except KeyboardInterrupt:
         capture.release()

source-code/image-processing/analyze.py

@@ -39,7 +39,7 @@
                                  (frame.shape[1], frame.shape[0]))
     else:
         output = None
-                                 
+
     track_window = (options.col, options.row, options.width, options.height)
     hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
     mask = cv2.inRange(hsv_frame,
@@ -52,24 +52,23 @@
     nr_frames = 1
     while True:
         status, frame = capture.read()
-        if status == True:
-            nr_frames += 1
-            hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
-            dst = cv2.calcBackProject([hsv], [0], roi_hist, [0, 50], 1)
-            status, track_window = cv2.meanShift(dst, track_window,
-                                                 termination_cond)
-            if not status:
-                continue
-            x, y, w, h = track_window
-            img = cv2.rectangle(frame, (x, y), (x + w, y + h), 255, 2)
-            cv2.imshow('image', img)
-            if output:
-                output.write(img)
-            if cv2.waitKey(1) % 0xFF == ord('q'):
-                break
-        else:
+        if status != True:
             break
 
+        nr_frames += 1
+        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+        dst = cv2.calcBackProject([hsv], [0], roi_hist, [0, 50], 1)
+        status, track_window = cv2.meanShift(dst, track_window,
+                                             termination_cond)
+        if not status:
+            continue
+        x, y, w, h = track_window
+        img = cv2.rectangle(frame, (x, y), (x + w, y + h), 255, 2)
+        cv2.imshow('image', img)
+        if output:
+            output.write(img)
+        if cv2.waitKey(1) % 0xFF == ord('q'):
+            break
     print(f'{nr_frames} frames processed')
     cv2.destroyAllWindows()
     if output:

source-code/image-processing/capture.py

@@ -49,27 +49,26 @@ def write_movie(base_name, extension, scene_nr, frames, fps):
             prev_rgb = avg_rgb(frame)
             scene_nr = 1
             saved_scenes = 0
-            while (True):
+            while True:
                 status, frame = capture.read()
-                if status:
-                    counter += 1
-                    cv2.imshow('frame', frame)
-                    rgb = avg_rgb(frame)
-                    if is_new_scene(prev_rgb, rgb, options.threshold):
-                        if len(frames) >= options.min_frames:
-                            saved_scenes += 1
-                            write_movie(base_name, extension, saved_scenes,
-                                        frames, options.fps)
-                        print(f'scene {scene_nr}: {len(frames)} frames')
-                        scene_nr += 1
-                        counter = 1
-                        frames = [frame]
-                    else:
-                        frames.append(frame)
-                    prev_rgb = rgb
-                    if cv2.waitKey(1) & 0xFF == ord('q'):
-                        break
+                if not status:
+                    break
+                counter += 1
+                cv2.imshow('frame', frame)
+                rgb = avg_rgb(frame)
+                if is_new_scene(prev_rgb, rgb, options.threshold):
+                    if len(frames) >= options.min_frames:
+                        saved_scenes += 1
+                        write_movie(base_name, extension, saved_scenes,
+                                    frames, options.fps)
+                    print(f'scene {scene_nr}: {len(frames)} frames')
+                    scene_nr += 1
+                    counter = 1
+                    frames = [frame]
                 else:
+                    frames.append(frame)
+                prev_rgb = rgb
+                if cv2.waitKey(1) & 0xFF == ord('q'):
                     break
             if frames:
                 if len(frames) >= options.min_frames:

source-code/image-processing/follow_ball.py

@@ -0,0 +1 @@
+media/

source-code/image-processing/split_scenes.py

@@ -0,0 +1,20 @@
+# manim
+
+`manim` is a framework to create mathematical animation in the style of
+[3Blue1Brown](https://www.3blue1brown.com/).  This directory contains
+a few examples.
+
+
+## What is it?
+
+1. `square_and_circle.py`: a square is rendered, flips and rotates, and
+   is transformed into a circle.
+1. `environment.yml`: conda environment description to use `manim`.
+
+
+## How to use it?
+
+To render and run the animation, use:
+```bash
+$ manim  -p  square_and_circle.py
+```