Access pflm Cython API

Available extensions

• pflm.smooth.polyfit: low-level kernels and polynomial fitters - calculate_kernel_value_f32, calculate_kernel_value_f64 - polyfit1d_helper, polyfit2d_helper

• pflm.interp.interp: internal interpolation routines - interp1d_linear, interp1d_spline_small, interp1d_spline - interp2d_linear, interp2d_spline

• pflm.pflm.utils.elastic_net_solver: ADMM solver for elastic net regression - fit_gaussian_helper, fit_nongaussian_helper and fit_multinomial_helper

• pflm.utils.lapack_helper: LAPACK wrappers - _gels, _gelss, _gtsv, _posv and _syevd

• pflm.utils.blas_helper: BLAS wrappers - _gemv and gemm

• pflm.utils.trapz: numeric helpers - trapz

Example: call GEMV

from pflm.utils.blas_helper cimport BLAS_Order, BLAS_Trans, _gemv
cimport numpy as np
import numpy as np

# y := alpha * op(A) @ x + beta * y
def call_gemv_f64(
    np.float64_t[:, :] A, np.float64_t[:] x,
    BLAS_Trans trans = BLAS_Trans.NoTrans,
    double alpha = 1.0, double beta = 0.0,
):
    cdef int m = A.shape[0]
    cdef int n = A.shape[1]
    cdef BLAS_Order order = BLAS_Order.ColMajor if A.strides[0] == A.itemsize else BLAS_Order.RowMajor
    cdef int lda = m if order == BLAS_Order.ColMajor else n
    cdef int out_size = m if trans == BLAS_Trans.NoTrans else n
    cdef np.ndarray[np.float64_t, ndim=1] y = np.zeros(out_size, dtype=np.float64)
    _gemv(order, trans, m, n, alpha, &A[0, 0], lda, &x[0], 1, beta, &y[0], 1)
    return y

Usage in Python:

import numpy as np

A = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float64)
b = np.array([1.0, 2.0], dtype=np.float64)
y = call_gemv_f64(A, b)
print(y)