choix de cloche et vidéo gif fonctionnelle

Dockerfile

@@ -19,8 +19,5 @@ RUN pip install -r requirements.txt
 COPY *.py ./
 RUN python install.py
 
-# Copy the app's code
-COPY main.py .
-
 # Run the application
 CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

animate_fractal.py

@@ -0,0 +1,39 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib import animation
+
+from mandelbrot import mandelbrot
+
+
+def animategif():
+    x_start, y_start = -2, -1.5  # an interesting region starts here
+    width, height = 3, 3  # for 3 units up and right
+    density_per_unit = 100  # how many pixels per unit
+
+    # real and imaginary axis
+    re = np.linspace(x_start, x_start + width, width * density_per_unit)
+    im = np.linspace(y_start, y_start + height, height * density_per_unit)
+
+    fig = plt.figure(figsize=(5, 5))  # instantiate a figure to draw
+    ax = plt.axes()  # create an axes object
+
+    def animate(i):
+        ax.clear()  # clear axes object
+        ax.set_xticks([], [])  # clear x-axis ticks
+        ax.set_yticks([], [])  # clear y-axis ticks
+
+        X = np.empty((len(re), len(im)))  # re-initialize the array-like image
+        threshold = round(1.15 ** (i + 1))  # calculate the current threshold
+
+        # iterations for the current threshold
+        for i in range(len(re)):
+            for j in range(len(im)):
+                X[i, j] = mandelbrot(re[i], im[j], threshold)
+
+        # associate colors to the iterations with an iterpolation
+        img = ax.imshow(X.T, interpolation="bicubic", cmap='magma')
+
+        return [img]
+
+    anim = animation.FuncAnimation(fig, animate, frames=45, interval=120, blit=True)
+    return anim

main.py

@@ -9,6 +9,7 @@ from AccelBrainBeat.brainbeat.binaural_beat import BinauralBeat
 import pydub
 import random
 
+from animate_fractal import animategif
 from blend_av import blend_av
 
 app = FastAPI()
@@ -37,7 +38,7 @@ class VideoProperties(BaseModel):
     main_frequency: int
     breath_pattern_in: int
     breath_pattern_out: int
-    color_palette = str
+    color_scheme = str
 
 
 class AvProperties(BaseModel):
@@ -66,12 +67,11 @@ async def get_generate_audio(audio_properties: AudioProperties):
     :param audio_properties:
     :return:
     """
-    # Generate a random 32 hexadecimal string
     tmp_dir = pathlib.Path("tmp_sound")
     tmp_dir.mkdir(parents=True, exist_ok=True)
     # Remove existing files in tmp_dir
     for filename in os.listdir(tmp_dir):
-        os.remove(str(tmp_dir / filename))
+        os.remove(tmp_dir / str(filename))
     bell_dir = pathlib.Path("bell")
     filename_prefix = ''.join([random.choice('0123456789ABCDEF') for i in range(32)])
     filename = f"{filename_prefix}.wav"
@@ -80,18 +80,32 @@ async def get_generate_audio(audio_properties: AudioProperties):
     b.save_beat(output_file_name=str(tmp_dir / "binaural_beat.wav"),
                 frequencys=(audio_properties.main_frequency,
                             audio_properties.lag_frequency),
-                play_time=(audio_properties.breath_pattern_in + audio_properties.breath_pattern_out)*2,
+                play_time=(audio_properties.breath_pattern_in + audio_properties.breath_pattern_out) * 2,
                 volume=audio_properties.volume
                 )
     pydub_background = pydub.AudioSegment.from_wav(tmp_dir / "binaural_beat.wav")
-    pydub_bell = pydub.AudioSegment.from_wav(bell_dir / audio_properties.bell_sound)
-    pydub_mix = pydub_background. \
-        overlay(pydub_bell, position=0). \
-        overlay(pydub_bell, position=audio_properties.breath_pattern_in * 1000). \
-        overlay(pydub_bell, position=(audio_properties.breath_pattern_in+audio_properties.breath_pattern_out) * 1000). \
-        overlay(pydub_bell, position=(audio_properties.breath_pattern_in*2+audio_properties.breath_pattern_out) * 1000)
+    bell_file = ""
+    if audio_properties.bell_sound == "Cloche":
+        bell_file = "339810__inspectorj__hand-bells-a-single-mod.wav"
+        skip_bell = False
+    elif audio_properties.bell_sound == "Bol tibétain":
+        bell_file = "417116__dersinnsspace__tibetan-bowl_right-hit-mod.wav"
+        skip_bell = False
+    else:
+        skip_bell = True
+    if skip_bell:
+        pydub_mix = pydub_background
+    else:
+        pydub_bell = pydub.AudioSegment.from_wav(bell_dir / bell_file)
+        pydub_mix = pydub_background. \
+            overlay(pydub_bell, position=0). \
+            overlay(pydub_bell, position=audio_properties.breath_pattern_in * 1000). \
+            overlay(pydub_bell,
+                    position=(audio_properties.breath_pattern_in + audio_properties.breath_pattern_out) * 1000). \
+            overlay(pydub_bell,
+                    position=(audio_properties.breath_pattern_in * 2 + audio_properties.breath_pattern_out) * 1000)
     pydub_mix.export(tmp_dir / filename, format="wav")
-    return filename
+    return FileResponse(tmp_dir / filename)
 
 
 @app.get("/generate_video")
@@ -101,7 +115,16 @@ async def get_generate_video(video_properties: VideoProperties):
     :param video_properties:
     :return:
     """
-    return None
+    tmp_dir = pathlib.Path("tmp_video")
+    tmp_dir.mkdir(parents=True, exist_ok=True)
+    # Remove existing files in tmp_dir
+    for filename in os.listdir(tmp_dir):
+        os.remove(tmp_dir / str(filename))
+    anim = animategif()
+    filename_prefix = ''.join([random.choice('0123456789ABCDEF') for i in range(32)])
+    filename = f"{filename_prefix}.gif"
+    anim.save(str(tmp_dir / filename), writer='imagemagick')
+    return FileResponse(str(tmp_dir / filename))
 
 
 @app.get("/generate_av")

mandelbrot.py

@@ -0,0 +1,21 @@
+# Source: https://matplotlib.org/matplotblog/posts/animated-fractals/
+def mandelbrot(x, y, threshold):
+    """Calculates whether the number c = x + i*y belongs to the
+    Mandelbrot set. In order to belong, the sequence z[i + 1] = z[i]**2 + c
+    must not diverge after 'threshold' number of steps. The sequence diverges
+    if the absolute value of z[i+1] is greater than 4.
+
+    :param float x: the x component of the initial complex number
+    :param float y: the y component of the initial complex number
+    :param int threshold: the number of iterations to considered it converged
+    """
+    # initial conditions
+    c = complex(x, y)
+    z = complex(0, 0)
+
+    for i in range(threshold):
+        z = z ** 2 + c
+        if abs(z) > 4.:  # it diverged
+            return i
+
+    return threshold - 1  # it didn't diverge

requirements.txt

@@ -5,3 +5,5 @@ starlette~=0.26.1
 AccelBrainBeat~=1.0.5
 httpx~=0.23.3
 pydub~=0.25.1
+numpy~=1.24.2
+matplotlib~=3.7.1