74 lines
2.3 KiB
Cython
74 lines
2.3 KiB
Cython
# cython: cdivision=True
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# cython: boundscheck=False
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# cython: wraparound=False
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# cython: nonecheck=False
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# cython: language_level=3
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# Author: Nicolas Hug
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cimport cython
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import numpy as np
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cimport numpy as np
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from numpy.math cimport INFINITY
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from cython.parallel import prange
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from libc.math cimport isnan
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from .common cimport X_DTYPE_C, X_BINNED_DTYPE_C
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np.import_array()
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def _map_to_bins(const X_DTYPE_C [:, :] data,
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list binning_thresholds,
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const unsigned char missing_values_bin_idx,
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X_BINNED_DTYPE_C [::1, :] binned):
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"""Bin numerical values to discrete integer-coded levels.
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Parameters
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----------
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data : ndarray, shape (n_samples, n_features)
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The numerical data to bin.
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binning_thresholds : list of arrays
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For each feature, stores the increasing numeric values that are
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used to separate the bins.
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binned : ndarray, shape (n_samples, n_features)
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Output array, must be fortran aligned.
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"""
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cdef:
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int feature_idx
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for feature_idx in range(data.shape[1]):
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_map_num_col_to_bins(data[:, feature_idx],
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binning_thresholds[feature_idx],
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missing_values_bin_idx,
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binned[:, feature_idx])
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cdef void _map_num_col_to_bins(const X_DTYPE_C [:] data,
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const X_DTYPE_C [:] binning_thresholds,
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const unsigned char missing_values_bin_idx,
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X_BINNED_DTYPE_C [:] binned):
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"""Binary search to find the bin index for each value in the data."""
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cdef:
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int i
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int left
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int right
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int middle
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for i in prange(data.shape[0], schedule='static', nogil=True):
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if isnan(data[i]):
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binned[i] = missing_values_bin_idx
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else:
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# for known values, use binary search
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left, right = 0, binning_thresholds.shape[0]
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while left < right:
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# equal to (right + left - 1) // 2 but avoids overflow
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middle = left + (right - left - 1) // 2
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if data[i] <= binning_thresholds[middle]:
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right = middle
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else:
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left = middle + 1
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binned[i] = left
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