the actual code stuff

Author: RandomGamingDev

.gitignore

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+extracted-data
+__pycache__

blockmodel_avg_mapper.py

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+import numpy as np
+import pandas as pd
+
+# Get the blockmodel_avgs
+blockmodel_avgs_df = pd.read_csv("blockmodel_avgs.csv").transpose()
+raw_blockmodel_avgs = blockmodel_avgs_df.to_dict()
+
+# Decode it into a nice easy to use datastructures
+blockmodel_avgs = { raw_blockmodel_avg["block_name"]: np.array([raw_blockmodel_avg[i] for i in ['r', 'g', 'b', 'a']]) for raw_blockmodel_avg in raw_blockmodel_avgs.values() }
+blockmodel_names, avgs = list(blockmodel_avgs.keys()), np.array(list(blockmodel_avgs.values()))
+
+# Get the average color of a block (returns None if there isn't any)
+def get_block_avg_color(blockname):
+    return blockmodel_avgs.get(blockname)
+
+# Get a block with the closest average to the specified color, its average, and the difference (there's no need to use a 16-tuple tree here so I didn't)
+def get_closest_colored_block(color):
+    # Convert the color to a numpy array if it isn't already
+    if not isinstance(color, np.ndarray):
+        color = np.array(color)
+
+    distances = np.sqrt(np.sum((avgs - color) ** 2, axis=1))
+    closests_index = np.argmin(distances)
+    closest = blockmodel_names[closests_index]
+    closest_avg = avgs[closests_index]
+    distance = distances[closests_index]
+    return (closest, closest_avg, distance)
+
+# Get the blocks that have an exact color
+def get_blocks_of_color(color):
+    # Convert the color to a numpy array if it isn't already
+    if not isinstance(color, np.ndarray):
+        color = np.array(color)
+
+    return [blockmodel_names[i] for i in np.nonzero((color == avgs).all(axis=1))[0]]