neurotools.stats.distributions module
Functions for computing the log-PDF of common distributions.
Some of these yield a more digits of precision than their counterparts in scipy.stats by computing log-probability values using np.longdouble.
- neurotools.stats.distributions.poisson_logpdf(k, l)[source]
Evaluate the log-pdf for a poisson distribution with rate l evaluated at points k.
- Parameters:
k (np.int32) – Counts at whih to evaluate the log-pdf
l (positive float) – Poisson rate
- Returns:
result – Log-probability of each k for a Poisson distribution with rate l.
- Return type:
np.longdouble
- neurotools.stats.distributions.poisson_pdf(k, l)[source]
Evaluate the pdf for a poisson distribution with rate l evaluated at points k.
- Parameters:
k (np.int32) – Counts at whih to evaluate the log-pdf
l (positive float) – Poisson rate
- Returns:
result – Probability of each k for a Poisson distribution with rate l.
- Return type:
np.longdouble
- neurotools.stats.distributions.gaussian_logpdf(mu, sigma, x)[source]
Evaluate the log-pdf of a (mu,sigma) normal distribution at points x.
- Parameters:
mu (float) – Distribution mean
sigma (positive float) – Distribution standard deviation
x (np.float32) – Points at which to evaluate.
- Returns:
result – log-PDF evaluated ast x.
- Return type:
np.longdouble
- neurotools.stats.distributions.gaussian_pdf(mu, sigma, x)[source]
Evaluate the pdf of a (mu,sigma) normal distribution at points x.
- Parameters:
mu (float) – Distribution mean
sigma (positive float) – Distribution standard deviation
x (np.float32) – Points at which to evaluate.
- Returns:
result – PDF evaluated ast x.
- Return type:
np.longdouble