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9c16be8bf3
...
f92a121758
16
ipmap.py
16
ipmap.py
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@ -21,7 +21,7 @@ import numpy as np
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ip_bytes = 4
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ip_bits = ip_bytes * 8
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num_ips = 1 << ip_bits
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num_ips_sqrt = 1 << (ip_bits >> 1)
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num_ips_sqrt = 1 << ip_bits // 2
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def make_coord_range(start: int, end: int):
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return decode(np.arange(start, end, dtype = np.uint32), num_dims = 2, num_bits = 16).astype(np.uint16)
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@ -239,7 +239,7 @@ def make_tiles(coords_path: Path, input_path: Path, tiles_dir: Path, *,
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def squish():
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nonlocal density_data
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nonlocal possible_overlaps
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density_data = np.swapaxes(density_data.reshape(density_data.shape[0] >> 1, 2, density_data.shape[1] >> 1, 2), 1, 2)
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density_data = np.swapaxes(density_data.reshape(density_data.shape[0] // 2, 2, density_data.shape[1] // 2, 2), 1, 2)
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print("calculating density sum...", end = " ", flush = True)
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density_data[:, :, 0, 0] += density_data[:, :, 0, 1]
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density_data[:, :, 0, 0] += density_data[:, :, 1, 0]
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@ -293,7 +293,7 @@ def make_tiles(coords_path: Path, input_path: Path, tiles_dir: Path, *,
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def squish():
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nonlocal rtt_data
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print(f"sorting rtt values for median calculation...", end = " ", flush = True)
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rtt_data = np.swapaxes(rtt_data.reshape(rtt_data.shape[0] >> 1, 2, rtt_data.shape[1] >> 1, 2), 1, 2)
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rtt_data = np.swapaxes(rtt_data.reshape(rtt_data.shape[0] // 2, 2, rtt_data.shape[1] // 2, 2), 1, 2)
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mask = np.empty((rtt_data.shape[0], rtt_data.shape[1]), dtype = np.bool_)
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np.less(rtt_data[:, :, 0, 0], rtt_data[:, :, 0, 1], out = mask) # sort first row
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rtt_data[mask, 0] = rtt_data[mask, 0, ::-1]
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@ -310,15 +310,15 @@ def make_tiles(coords_path: Path, input_path: Path, tiles_dir: Path, *,
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print("calculating median rtt values...", end = " ", flush = True)
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mask2 = np.empty((rtt_data.shape[0], rtt_data.shape[1]), dtype = np.bool_) # need second mask for binary ops
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np.not_equal(rtt_data[:, :, 1, 1], 0, out = mask) # four nums populated
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rtt_data[mask, 0, 1] //= 2
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rtt_data[mask, 1, 0] //= 2
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rtt_data[mask, 0, 0] = rtt_data[mask, 0, 1]
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rtt_data[mask, 0, 0] -= rtt_data[mask, 1, 0]
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rtt_data[mask, 0, 0] >>= 1
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rtt_data[mask, 0, 0] += rtt_data[mask, 1, 0] # take average of middle two nums
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np.logical_and(np.not_equal(rtt_data[:, :, 1, 0], 0, out = mask), np.equal(rtt_data[:, :, 1, 1], 0, out = mask2), out = mask) # three nums populated
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rtt_data[mask, 0, 0] = rtt_data[mask, 0, 1] # take middle of three nums
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np.logical_and(np.not_equal(rtt_data[:, :, 0, 1], 0, out = mask), np.equal(rtt_data[:, :, 1, 0], 0, out = mask2), out = mask) # two nums populated
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rtt_data[mask, 0, 0] -= rtt_data[mask, 0, 1]
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rtt_data[mask, 0, 0] >>= 1
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rtt_data[mask, 0, 0] //= 2
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rtt_data[mask, 0, 1] //= 2
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rtt_data[mask, 0, 0] += rtt_data[mask, 0, 1] # take average of first two nums
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# everything else (1 or 0 nums populated) don't need any modifications
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print("done")
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@ -329,6 +329,8 @@ def make_tiles(coords_path: Path, input_path: Path, tiles_dir: Path, *,
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if skip_iters is not None:
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for _ in range(skip_iters):
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squish()
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def write_all_colormaps():
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if raws_path is not None:
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@ -230,7 +230,7 @@
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}
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const apiUrl = "https://ipapi.7circles.moe"
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const defaultVariant = "density"
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const defaultVariant = "rtt"
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const defaultColormap = "viridis"
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const tileSize = 256
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const tilesDir = "assets/tiles"
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