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diff --git a/mask_tests/mask.py.bak b/mask_tests/mask.py.bak
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+#!/usr/bin/env python3
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.animation as animation
+import pyopencl as cl
+from alive_progress import alive_bar
+from matplotlib.backend_bases import MouseButton
+from PIL import Image
+
+img_res_x = 1000
+img_res_y = 1000
+total_pixels = img_res_x * img_res_y # so we don't gotta compute it every time
+
+periods = 1
+square_x = 0
+square_y = 0
+
+x_min = (-periods * np.pi) + (square_x * np.pi)
+x_max = (periods  * np.pi) + (square_x * np.pi)
+y_min = (-periods * np.pi) + (square_y * np.pi)
+y_max = (periods * np.pi) + (square_y * np.pi)
+
+escape = 10000
+iterations = 255*3
+c_x = 2 * np.pi
+c_y = 2 * np.pi
+
+animation_progres_save = "ani1_less.mp4"
+single_frame_save = "asdf.png"
+
+opencl_context = cl.create_some_context(interactive=False)
+opencl_queue = cl.CommandQueue(opencl_context)
+
+kernel_src_path = "./kernel.c"
+
+frames = 1
+rendered_frames = []
+
+image = np.empty([img_res_x, img_res_y], np.uint32)
+image_buffer = cl.Buffer(opencl_context, cl.mem_flags.WRITE_ONLY, image.nbytes)
+
+plt.style.use('dark_background')
+# fuck this shit
+fig = plt.figure(frameon=False)
+fig.set_size_inches(img_res_x/fig.dpi, img_res_y/fig.dpi)
+#fig.set_size_inches(width/height, 1, forward=False)
+
+
+ax = plt.Axes(fig, [0., 0., 1., 1.])
+#ax.set_axis_off()
+fig.add_axes(ax)
+
+cmap = plt.cm.viridis
+cmap.set_bad((0,0,0))
+cmap.set_over((0,0,0))
+cmap.set_under((0,0,0))
+
+mask_path = "mask.png"
+
+bruh = None
+
+def on_click(event):
+    global bruh
+    split_ratio = 1
+    if (event.button is MouseButton.MIDDLE) and (event.inaxes):
+        # there's probably a way to set global coordinates;
+        # I don't expect this to go anywhere so I don't really care
+        on_x = ((event.xdata / img_res_x) * abs(x_max - x_min)) + x_min
+        on_y = ((event.ydata / img_res_y) * abs(y_max - y_min)) + y_min
+
+        #I, uh, also don't know the best way to replicate the openCL code automaticly in python
+        #so ajust if nessesary
+        x_hops = []
+        y_hops = []
+        for i in range(iterations):
+            x_hops.append(((on_x - x_min) / abs(x_max - x_min)) * img_res_x)
+            y_hops.append(((on_y - y_min) / abs(y_max - y_min)) * img_res_y)
+            next_x = on_x/np.tan(on_y)
+            on_y = on_y/np.tan(on_x)
+            on_x = next_x
+            if on_x**2 + on_y**2 > escape:
+                break
+        print(y_hops[0])
+        print(on_y)
+        print("{} hops".format(len(x_hops)))
+        if bruh:
+            bruh.pop(0).remove()
+        bruh = ax.plot(x_hops, y_hops)
+        plt.draw()
+
+         
+
+        print(on_x, on_y)
+
+
+print("compiling openCL kernel...")
+with open(kernel_src_path, 'r') as kernel_src:
+  compiled_kernel = cl.Program(opencl_context, kernel_src.read()).build()
+
+encoding_progress = alive_bar(frames, bar = 'filling', spinner = 'waves')
+
+def display_encoder_progress(current_frame: int, total_frames: int):
+    print("Encoding: frame {}/{}".format(current_frame, frames))
+
+with open G
+
+
+# TODO clean this up
+print("Rendering {} frames...".format(frames))
+if frames > 1:
+    with alive_bar(frames, bar = 'filling', spinner = 'waves') as bar_total:
+        for frame_i in range(0, frames):
+            compiled_kernel.render_frame(opencl_queue, image.shape, None, image_buffer,
+                                         np.double(abs(x_max - x_min) / img_res_x),
+                                         np.double(abs(y_max - y_min) / img_res_y),
+                                         np.double(x_min), np.double(y_min), 
+                                         np.uint32(iterations), np.uint32(escape),
+                                         np.double(frame_i / frames))
+
+
+            cl.enqueue_copy(opencl_queue, image, image_buffer).wait()
+            rendered_frame = ax.imshow(image, norm="log", aspect="auto", cmap=cmap, animated="True")
+            rendered_frames.append([rendered_frame])
+            bar_total()
+    print("Encoding/Saving...")
+    ani = animation.ArtistAnimation(fig, rendered_frames, interval=30, blit=True)
+    ani.save(animation_progres_save, extra_args=['-preset', 'lossless'], progress_callback=display_encoder_progress, codec="h264_nvenc")
+else:
+        compiled_kernel.render_frame(opencl_queue, image.shape, None, image_buffer,
+                                     np.double(abs(x_max - x_min) / img_res_x),
+                                     np.double(abs(y_max - y_min) / img_res_y),
+                                     np.double(x_min), np.double(y_min), 
+                                     np.uint32(iterations), np.uint32(escape),
+                                     np.double(1))
+        cl.enqueue_copy(opencl_queue, image, image_buffer).wait()
+        ax.imshow(image, norm="log", aspect="auto", cmap=cmap)
+        fig.savefig(single_frame_save)
+        plt.autoscale(False)
+        plt.connect('motion_notify_event', on_click)
+        plt.show()
+
+