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Copy pathcompare_animations.py
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332 lines (268 loc) · 12.3 KB
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import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from PIL import Image
import io
from pathlib import Path
import numpy.testing as npt
def create_animation_and_capture_frames():
# Load the same data
file = r'example.dat'
nx = 8
ny = 9
num_frames = 72
data = np.fromfile(file, np.float32).reshape(num_frames, ny, nx)
# Create figure and plot
fig, ax = plt.subplots()
vmax = 100
vmin = 0
h = ax.imshow(data[0], cmap=plt.get_cmap('CMRmap_r'), origin='lower',
interpolation='none', vmin=vmin, vmax=vmax, animated=True)
ax.set_xticks(range(nx))
ax.set_xticklabels(range(1, nx + 1))
ax.set_yticks(range(ny))
ax.set_yticklabels(range(1, ny + 1))
plt.colorbar(h)
fig.tight_layout()
# List to store direct frames
direct_frames = []
def capture_frame(fig):
buf = io.BytesIO()
fig.savefig(buf, format='png', dpi=300)
buf.seek(0)
img = Image.open(buf)
# Print transparency info for first and last few frames
if len(direct_frames) < 2 or len(direct_frames) > num_frames - 2:
print(f"\nFrame {len(direct_frames)} transparency info:")
print(f"Mode: {img.mode}")
if img.mode in ('RGBA', 'LA'):
alpha_extrema = img.getchannel('A').getextrema()
print(f"Alpha channel extrema: {alpha_extrema}")
return np.array(img)
def update(frame):
img = data[frame,]
h.set_array(img)
direct_frames.append(capture_frame(fig))
return h,
# Create animation
interval = 100
ani = animation.FuncAnimation(fig, update, frames=range(num_frames),
interval=interval, blit=True)
# Save animation
ani.save('example_fixed.gif', writer='pillow', fps=2, dpi=300)
plt.close() # Close the figure to free memory
return direct_frames
def capture_gif_frames(gif_path):
gif_frames = []
gif = Image.open(gif_path)
frame_num = 0
try:
while True:
# Print info about first and last few frames
if frame_num < 2 or frame_num > 69:
print(f"\nGIF Frame {frame_num} info:")
print(f"Mode: {gif.mode}")
if hasattr(gif, 'info'):
print(f"Frame info: {gif.info}")
gif_frames.append(np.array(gif))
frame_num += 1
gif.seek(gif.tell() + 1)
except EOFError:
pass
return gif_frames
def convert_frame_for_comparison(frame):
"""Convert frame to RGB for comparison, handling different formats."""
if isinstance(frame, np.ndarray):
if frame.ndim == 2: # Palette mode
# Convert to RGB by repeating the channel
return np.stack([frame] * 3, axis=-1)
elif frame.shape[-1] == 4: # RGBA
return frame[..., :3] # Take only RGB channels
elif frame.shape[-1] == 3: # RGB
return frame
return None
def create_plot_mask(shape):
"""Create a mask that excludes axes regions."""
mask = np.ones(shape[:2], dtype=bool)
# Exclude everything up to and including the left border
mask[:, :390] = False
# Exclude bottom axis region
mask[-150:, :] = False
# Exclude top margin
mask[:100, :] = False
# Exclude everything up to and including the right border
mask[:, -495:] = False
# Debug: Save mask visualization
plt.figure(figsize=(10, 8))
plt.imshow(mask, cmap='gray')
plt.title('Plot Region Mask (White = Included, Black = Excluded)')
plt.savefig('mask_visualization.png')
plt.close()
return mask
def visualize_difference(direct_rgb, gif_rgb, diff, coords, frame_num):
"""Visualize the difference between frames at the point of maximum difference."""
y, x = coords
# Create a figure with a 2x3 grid
fig, axes = plt.subplots(2, 3, figsize=(15, 10))
# Plot original frame
axes[0,0].imshow(direct_rgb)
axes[0,0].set_title('Direct Frame')
# Plot GIF frame
axes[0,1].imshow(gif_rgb)
axes[0,1].set_title('GIF Frame')
# Plot difference
diff_plot = axes[0,2].imshow(np.mean(diff, axis=2), cmap='hot')
axes[0,2].set_title('Difference Map')
plt.colorbar(diff_plot, ax=axes[0,2])
# Define zoom region
zoom_size = 20
x_start = max(0, x - zoom_size)
x_end = min(direct_rgb.shape[1], x + zoom_size)
y_start = max(0, y - zoom_size)
y_end = min(direct_rgb.shape[0], y + zoom_size)
# Plot zoomed regions with pixel values
zoom_direct = direct_rgb[y_start:y_end, x_start:x_end]
zoom_gif = gif_rgb[y_start:y_end, x_start:x_end]
zoom_diff = np.mean(diff[y_start:y_end, x_start:x_end], axis=2)
axes[1,0].imshow(zoom_direct)
axes[1,0].set_title(f'Zoomed Direct\nPixel at ({x},{y}): {direct_rgb[y,x]}')
axes[1,1].imshow(zoom_gif)
axes[1,1].set_title(f'Zoomed GIF\nPixel at ({x},{y}): {gif_rgb[y,x]}')
zoom_diff_plot = axes[1,2].imshow(zoom_diff, cmap='hot')
axes[1,2].set_title(f'Zoomed Difference\nDiff at ({x},{y}): {diff[y,x]}')
plt.colorbar(zoom_diff_plot, ax=axes[1,2])
# Mark the maximum difference point
axes[0,2].plot(x, y, 'r+', markersize=10) # Correctly place crosshairs on full-frame difference map
for ax in [axes[1,0], axes[1,1], axes[1,2]]:
ax.plot(x - x_start, y - y_start, 'r+', markersize=10)
# Print detailed color values
direct_color = direct_rgb[y, x]
gif_color = gif_rgb[y, x]
color_diff = np.abs(direct_color - gif_color)
text = f'Color values at ({x}, {y}):\n'
text += f'Direct RGB: {direct_color}\n'
text += f'GIF RGB: {gif_color}\n'
text += f'Difference: {color_diff}\n'
text += f'Max channel diff: {np.max(color_diff)}'
fig.text(0.02, 0.02, text, fontsize=10, family='monospace')
plt.tight_layout()
plt.savefig(f'frame_{frame_num}_diff.png', dpi=300)
plt.close()
def compare_animations():
print("Generating direct matplotlib animation frames...")
direct_frames = create_animation_and_capture_frames()
print("Capturing frames from saved GIF...")
gif_frames = capture_gif_frames('example_fixed.gif')
print(f"\nOriginal frame counts:")
print(f"Direct animation: {len(direct_frames)} frames")
print(f"GIF: {len(gif_frames)} frames")
direct_frames = direct_frames[2:74] # Take frames 2 through 73 (72 frames)
print(f"\nAfter selecting animation frames:")
print(f"Direct animation: {len(direct_frames)} frames")
print(f"GIF: {len(gif_frames)} frames")
if len(direct_frames) != len(gif_frames):
print(f"\nERROR: Frame count mismatch!")
print(f"Direct frames: {len(direct_frames)}, GIF frames: {len(gif_frames)}")
return
print("\n=== Comparing Frame Colors ===\n")
# Create mask for the plot region
first_frame = convert_frame_for_comparison(direct_frames[0])
plot_mask = create_plot_mask(first_frame.shape)
non_identical_frames = []
max_diff_after_first = 0
max_diff_details = None
plot_region_stats = []
for i, (direct_frame, gif_frame) in enumerate(zip(direct_frames, gif_frames)):
direct_rgb = convert_frame_for_comparison(direct_frame)
gif_rgb = convert_frame_for_comparison(gif_frame)
if direct_rgb is None or gif_rgb is None:
print(f"Error: Could not convert frame {i} for comparison")
continue
# Ensure we're comparing integers
direct_rgb = direct_rgb.astype(np.uint8)
gif_rgb = gif_rgb.astype(np.uint8)
# Calculate differences
diff = np.abs(direct_rgb.astype(int) - gif_rgb.astype(int))
# Calculate statistics for plot region only
plot_diff = diff[plot_mask]
plot_stats = {
'mean': np.mean(plot_diff),
'max': np.max(plot_diff),
'std': np.std(plot_diff)
}
plot_region_stats.append(plot_stats)
# Full frame statistics for comparison
max_pixel_diff = np.max(diff)
mean_diff = np.mean(diff)
if not np.array_equal(direct_rgb, gif_rgb):
non_identical_frames.append(i)
if i == 0:
print(f"Frame 0 analysis (palette mode):")
print(f"Mean color difference: {mean_diff:.4f}")
print(f"Max pixel difference: {max_pixel_diff:.4f}")
print(f"Red channel mean difference: {np.mean(diff[..., 0]):.4f}")
print(f"Green channel mean difference: {np.mean(diff[..., 1]):.4f}")
print(f"Blue channel mean difference: {np.mean(diff[..., 2]):.4f}\n")
else:
# Find location of maximum difference within plot region
masked_mean_diff = np.mean(diff, axis=2).copy()
masked_mean_diff[~plot_mask] = -1
# Find all points with actual differences
diff_points = np.argwhere(masked_mean_diff > 0)
if len(diff_points) > 0:
# Find the point with maximum difference among valid points
max_diff_point_idx = np.argmax([masked_mean_diff[y,x] for y,x in diff_points])
y, x = diff_points[max_diff_point_idx]
current_max_diff = np.max(diff[y,x])
if current_max_diff > max_diff_after_first:
max_diff_after_first = current_max_diff
max_diff_frame = i
max_diff_details = {
'coords': (y, x),
'mean': mean_diff,
'max': current_max_diff,
'red': np.mean(diff[..., 0]),
'green': np.mean(diff[..., 1]),
'blue': np.mean(diff[..., 2]),
'direct_rgb': direct_rgb,
'gif_rgb': gif_rgb,
'diff': diff
}
# Debug output
print(f"\nDebug: Frame {i} maximum difference found:")
print(f"Location: ({x}, {y})")
print(f"Direct RGB: {direct_rgb[y, x]}")
print(f"GIF RGB: {gif_rgb[y, x]}")
print(f"Difference: {diff[y, x]}")
print(f"Is in mask?: {plot_mask[y, x]}")
# Convert stats to numpy array for easier analysis
plot_region_stats = np.array([(s['mean'], s['max'], s['std']) for s in plot_region_stats])
print("\n=== Plot Region Analysis (excluding axes) ===")
print(f"Mean difference: {np.mean(plot_region_stats[1:, 0]):.4f}") # Exclude first frame
print(f"Max difference: {np.max(plot_region_stats[1:, 1]):.4f}")
print(f"Standard deviation: {np.mean(plot_region_stats[1:, 2]):.4f}")
print("\n=== Exact Frame Comparison Results ===")
if len(non_identical_frames) == 0:
print("All frames are exactly identical!")
else:
print(f"Found {len(non_identical_frames)} non-identical frames")
print(f"Frame numbers: {non_identical_frames}")
if max_diff_details is not None:
y, x = max_diff_details['coords']
print(f"\nLargest difference in non-palette frames (Frame {max_diff_frame}):")
print(f"Location: (x={x}, y={y})")
print(f"Mean color difference: {max_diff_details['mean']:.4f}")
print(f"Max pixel difference: {max_diff_details['max']:.4f}")
print(f"Red channel mean difference: {max_diff_details['red']:.4f}")
print(f"Green channel mean difference: {max_diff_details['green']:.4f}")
print(f"Blue channel mean difference: {max_diff_details['blue']:.4f}")
visualize_difference(
max_diff_details['direct_rgb'],
max_diff_details['gif_rgb'],
max_diff_details['diff'],
max_diff_details['coords'],
max_diff_frame
)
print(f"\nVisualization saved as frame_{max_diff_frame}_diff.png")
if __name__ == '__main__':
compare_animations()
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