40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
import numpy as np
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import tensorflow as tf
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import pandas as pd
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from constants import *
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inputs = ['elevation', 'distance_to_water']
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output = 'biome_num'
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def dataframe_to_dataset_biomes(df):
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rows = df.shape[0]
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# 8 for seasonal temp and precipitation
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# 3 for latitude, elevation and distance_to_water
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columns = 11
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tf_inputs = np.empty((0, columns))
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tf_output = np.empty((0))
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latitude = np.array(df.index.get_level_values(1))
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longitude = np.array(df.index.get_level_values(0))
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for year in range(MIN_YEAR, MAX_YEAR + 1):
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local_inputs = list(inputs)
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for season in SEASONS:
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local_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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local_df = df[local_inputs]
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local_df.loc[:, 'latitude'] = pd.Series(latitude, index=local_df.index)
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tf_inputs = np.concatenate((tf_inputs, local_df.values), axis=0)
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tf_output = np.concatenate((tf_output, df[output].values), axis=0)
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tf_inputs = tf.cast(tf_inputs, tf.float32)
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tf_output = tf.cast(tf_output, tf.int32)
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return tf.data.Dataset.from_tensor_slices((tf_inputs, tf_output))
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