logbesselk 2.2.4

Provide function to calculate the modified Bessel function of the second kind

logbesselk

Provide function to calculate the modified Bessel function of the second kind and its derivatives.

Author

TAKEKAWA Takashi [e-mail]

Reference

Takashi Takekawa, Fast parallel calculation of modified Bessel function of the second kind and its derivatives, SoftwareX, 17, 100923, 2022.

Require

• python >= 3.7.1
• tensorflow >= 2.6.1

Installation

pip install logbesselk

Examples

import tensorflow as tf
from logbesselk.integral import log_bessel_k


log_k = log_bessel_k(v=1.0, x=1.0)
log_dkdv = log_bessel_k(v=1.0, x=1.0, 1, 0)
log_dkdx = log_bessel_k(v=1.0, x=1.0, 0, 1)


# build graph at first execution time
log_bessel_k_tensor = tf.function(log_bessel_k)
log_bessel_dkdv_tensor = tf.function(lambda v, x: log_bessel_k(v, x, 1, 0))
log_bessel_dkdx_tensor = tf.function(lambda v, x: log_bessel_k(v, x, 0, 1))

n = 1000
for i in range(10):
    v = 10. ** (2. * tf.random.uniform((n,), dtype=tf.float64) - 1.
    x = 10. ** (3. * tf.random.uniform((n,), dtype=tf.float64) - 1.)

    log_k = log_bessel_k_tensor(v, x)
    log_dkdv = log_bessel_dkdv_tensor(v, x)
    log_dkdx = log_bessel_dkdx_tensor(v, x)

Evaluation

python -m eval.prec
python -m eval.time
python -m eval.scale
python -m eval.fig1
python -m eval.fig2
python -m eval.fig3
python -m eval.fig4
python -m eval.fig5
python -m eval.fig6
python -m eval.fig7