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import argparse
import json
import math
import time
import tkinter as tk
import numpy as np
from utils import rgb_to_hex
def parse_args():
return {
"cell_size": 8, # in pixels
"num_cells_w": 100, # TODO: w/h or r/c?
"num_cells_h": 100,
"colors_path": "configs/colors_64_v0.json",
"corners_path": "configs/corners_hollow4x4_v0.json",
"frame_delay": 1000 // 15, # time b/w frames, in millis
}
def seq_to_frames(bin_seq: np.ndarray, args: dict) -> np.ndarray: # TODO: Namespace
"""
Converts a binary sequence to an array of frames.
TODO: doc, expecting size of exactly one frame in the future?
np.packbits seems relevant but limited to 8 bits
Args:
bin_seq: a 1D array of binary values.
args: config parameters
Returns:
array of shape (num_frames, args["num_cells_h"], args["num_cells_w"]), where each element is
a hex string for the color of that cell
"""
bin_seq = bin_seq.copy() # so that we don't mutate bin_seq
with open(args["colors_path"], "r") as f:
colors = json.load(f)
with open(args["corners_path"], "r") as f:
corners = json.load(f)
assert len(corners["corner_colors"]) == 4, "Hardcoded for 4 corners"
corner_width = corners["corner_width"]
corner_height = corners["corner_height"]
num_colors = len(colors)
bits_per_cell = int(math.log2(num_colors))
assert 2**bits_per_cell == num_colors, "Assumed the number of colors is a power of 2."
# bits_per_frame = bits_per_cell * args["num_cells_w"] * args["num_cells_h"]
# num_frames = int(math.ceil(len(bin_seq) / bits_per_frame))
# bin_seq.resize(bits_per_frame * num_frames)
# # frames_bits = bin_seq.reshape(num_frames, args["num_cells_h"], args["num_cells_w"], bits_per_cell)
#
# pows = 2 ** np.arange(bits_per_cell)
# frames_vals = (frames_bits * pows).sum(axis=-1) # low to high bit order
cells_per_frame = args["num_cells_w"] * args["num_cells_h"] - 4 * corner_width * corner_height
bits_per_frame = bits_per_cell * cells_per_frame
num_frames = int(math.ceil(len(bin_seq) / bits_per_frame))
bin_seq.resize(bits_per_frame * num_frames)
frames_bits = bin_seq.reshape(num_frames, cells_per_frame, bits_per_cell)
pows = 2 ** np.arange(bits_per_cell)
frames_vals = (frames_bits * pows).sum(axis=-1) # low to high bit order
# Efficiently map frame_vals to the corresponding hex colors (https://stackoverflow.com/a/55950051)
color_mapping_arr = np.empty(num_colors, dtype="<U7")
for i in range(num_colors):
color_mapping_arr[i] = rgb_to_hex(colors[str(i)]) # JSON keys stored as str
frames_colors = color_mapping_arr[frames_vals]
num_top_cells = (args["num_cells_w"] - 2 * corner_width) * corner_height # TODO: explain
top_cells = frames_colors[:, :num_top_cells].reshape(num_frames, corner_height, -1)
center_cells = frames_colors[:, num_top_cells:-num_top_cells].reshape(num_frames, -1, args["num_cells_w"])
bottom_cells = frames_colors[:, -num_top_cells:].reshape(num_frames, corner_height, -1)
corners_numpy_dict = {key: np.broadcast_to(val, (num_frames, corner_height, corner_width))
for key, val in corners["corner_colors"].items()}
top_rows = np.concatenate([corners_numpy_dict["0"], top_cells, corners_numpy_dict["1"]], axis=2)
bottom_rows = np.concatenate([corners_numpy_dict["2"], bottom_cells, corners_numpy_dict["3"]], axis=2)
return np.concatenate([top_rows, center_cells, bottom_rows], axis=1)
class AnimatedFrames:
def __init__(self, frames: np.ndarray, args: dict):
self.frames = frames
self.args = args
self.width_pixels = args["cell_size"] * args["num_cells_w"]
self.height_pixels = args["cell_size"] * args["num_cells_h"]
self.root = tk.Tk()
self.root.columnconfigure(0, weight=1)
self.root.rowconfigure(0, weight=1)
self.canvas = tk.Canvas(self.root, width=self.width_pixels, height=self.height_pixels,
borderwidth=0, highlightthickness=0) # https://stackoverflow.com/a/63220348
self.canvas.grid(column=0, row=0)
# We will create each cell (rectangle) now, and then update their colors in different frames
self.inds_to_id = dict() # map from (row_ind, col_ind) to the id of the rectangle at that cell position
for i in range(args["num_cells_h"]):
for j in range(args["num_cells_w"]):
self.inds_to_id[(i, j)] = self.canvas.create_rectangle(
i * args["cell_size"], j * args["cell_size"], (i + 1) * args["cell_size"],
(j + 1) * args["cell_size"], width=0
)
self.frame_ind = 0 # the index in `self.frames` of the next frame to display
self.start_time = None
self._debug_text_id = self.canvas.create_text((args["num_cells_w"] - 2) * args["cell_size"], (args["num_cells_h"] - 2) * args["cell_size"])
def display_frame(self):
func_start_time = time.time_ns()
for inds_tuple, color_hex in np.ndenumerate(self.frames[self.frame_ind % len(self.frames)]):
self.canvas.itemconfigure(self.inds_to_id[inds_tuple], fill=color_hex)
self.canvas.itemconfigure(self._debug_text_id, text=self.frame_ind)
self.frame_ind += 1
adjusted_delay = round((self.start_time + self.args["frame_delay"] * int(1e6)
* self.frame_ind - func_start_time) / 1e6)
assert adjusted_delay > 1, adjusted_delay # o/w we lagged too far behind, assuming 1 ms for this instruction
self.canvas.after(adjusted_delay, self.display_frame) # TODO: check delay is exact
# TODO: set self time and just sleep until then
def animate(self):
epilepsy_warning_id = self.canvas.create_text(self.width_pixels / 2, self.height_pixels / 2,
text="Warning: Epilepsy")
def delete_and_animate():
self.canvas.delete(epilepsy_warning_id)
self.start_time = time.time_ns()
self.display_frame()
self.canvas.after(5000, delete_and_animate)
# self.display_frame()
self.root.mainloop()
if __name__ == "__main__":
args = parse_args()
rand_bin_seq = np.random.randint(2, size=1000000)
frames = seq_to_frames(rand_bin_seq, args)
AnimatedFrames(frames, args).animate()
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