eniric/resample.py
"""Functions for spectral resampling."""
from typing import Union
import numpy as np
from numpy import ndarray
def log_resample(
wavelength, sampling: Union[int, float], resolution: Union[int, float]
) -> ndarray:
"""Resample spectrum with a given sampling per resolution element.
Uses faster method using log and powers of a base.
The base is (1.0 + 1.0/(sampling*resolution).
Parameters
----------
wavelength: numpy.ndarray
Wavelength array.
sampling: int, float
Points to sample per resolution element
resolution: int, float
Instrumental resolution
Returns
-------
logspace: ndarray
Array of points with a set sampling per resolution element.
Note
----
Almost equivalent to using
``np.logspace(np.log(wavelength)/np.log(base), np.log(wavelength)/np.log(base),
np.log(wavelength_end / wavelength_start) / np.log(base), base)``.
"""
wavelength_start = np.nanmin(wavelength)
wavelength_end = np.nanmax(wavelength)
# Create grid using logarithms with base of (1.0 + 1.0/(sampling*resolution))
base = 1.0 + 1.0 / (float(sampling) * float(resolution)) # type: float
return wl_logspace(wavelength_start, wavelength_end, base, end_point=True)
def wl_logspace(start, stop, base, end_point: bool = False):
"""Like np.logspace but start and stop in wavelength units.
Parameters
----------
start: float
Starting point (in real units)
stop: float
End point (in real units)
base: float
Logarithmic base to jump between points.
end_point: bool
Make sure to include/go past the end point
Returns
-------
logspace: ndarray
Array of points with a spacing such that x[ii+1] = x[ii] * base
between start and stop (or stop*base if end_point = True).
"""
n = np.log(stop / start) / np.log(base)
# to use the end point
if end_point:
n = n + 1
powers = np.arange(np.ceil(n))
return start * base ** powers
def log_chunks(wavelength: ndarray, percent: float) -> ndarray:
r"""Define the bounds at which $(\Delta \lambda)/\lambda = X\%$.
Allows spectrum to be split into chunks in which the size is X% of the given wavelength.
This takes logarithmic steps with a base of (1+X/100).
Parameters
----------
wavelength: ndarry
Wavelength array.
percent: float
Base step in percentage.
Returns
-------
logspace: ndarray
Array of points with a growth in wavelength spanned of a given percent.
"""
base = 1 + percent / 100.0
wl_min = np.nanmin(wavelength)
wl_max = np.nanmax(wavelength)
return wl_logspace(wl_min, wl_max, base, end_point=True)