54 lines
1.3 KiB
Python
54 lines
1.3 KiB
Python
import numpy as np
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from utils import *
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from nn import B, compile_b
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from draw import draw
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import time
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def chunker(seq, size):
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return (seq[pos:pos + size] for pos in range(0, len(seq), size))
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year = MAX_YEAR - 1
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df = pd.read_pickle('data.p')
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compile_b()
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for change in range(0, 1):
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print('TEMPERATURE MODIFICATION OF {}'.format(change))
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inputs = ['elevation', 'distance_to_water', 'latitude']
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for season in SEASONS:
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inputs += [
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'temp_{}_{}'.format(season, year),
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'precip_{}_{}'.format(season, year)
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]
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print(inputs)
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# print(inputs)
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frame = df[inputs + ['longitude']]
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# print(frame.head())
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for season in SEASONS:
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frame.loc[:, 'temp_{}_{}'.format(season, year)] += change
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columns = ['latitude', 'longitude', 'biome_num']
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new_data = pd.DataFrame(columns=columns)
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for i, chunk in enumerate(chunker(frame, B.batch_size)):
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if chunk.shape[0] < B.batch_size:
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continue
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input_data = normalize_ndarray(chunk.loc[:, inputs].values)
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out = B.predict(input_data)
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f = pd.DataFrame({
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'longitude': chunk.loc[:, 'longitude'],
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'latitude': chunk.loc[:, 'latitude'],
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'biome_num': out
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}, columns=columns)
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new_data = new_data.append(f)
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draw(new_data)
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