"""Tools moduls
This module provides a number of generic tools.
"""
import os
import numpy as np
[docs]def get_default_yaml_path():
""" Hack to find where the default yaml is, to be fixed properly
"""
first_path = '../data/LSST_CCOB_r.yaml'
if os.path.exists(first_path):
return first_path
second_path = './data/LSST_CCOB_r.yaml'
if os.path.exists(second_path):
return second_path
return None
[docs]def get_vector(axis, value):
""" Returns a vector containing the given value at the right spot for the given axis
Parameters
----------
axis : `string`
the name of the rotation axis, x, y or z
value : `float`
the value of the rotation angle in degrees or of the shift in meters
Returns
-------
vector : `list` of `floats`
a list containing value at the corresponding spot of the given axis
"""
if axis == 'x':
vector = [value, 0, 0]
elif axis == 'y':
vector = [0, value, 0]
elif axis == 'z':
vector = [0, 0, value]
else:
raise Exception(f'Unknown axis {axis}: axis should be x, y or z')
return vector
# define function to get nice ranges
[docs]def get_ranges(x, y, dr=0.010):
""" Get x and y ranges around their mean values with a delta of dr
This is useful to center plots around a region of interest
Parameters
----------
x : `numpy.array`
The input array along the x-axis
y : `numpy.array`
The input array along the y-axis
dr : `float`
The delta around the mean value, or the box size if you wish
Returns
-------
x_min, x_max, y_min, y_max : a tuple of 4 `floats`
The min and max values for x- and y-axis, i.e. the box boundaries.
"""
x_min = x.mean() - dr
x_max = x.mean() + dr
y_min = y.mean() - dr
y_max = y.mean() + dr
return x_min, x_max, y_min, y_max
[docs]def get_main_impact_point(r_forward):
""" Return main image light rays
Direct path will be r_forward with fewest number of things in "path"
.. todo::
`get_main_impact_point` should compute a real barycentre?
Parameters
----------
r_forward : `list` of `batoid.RayVector`
a list of batoid RayVector with a bunch of rays propagated through the system.
Returns
-------
i_straight : `int`
the index of the main image
direct_x, direct_y : `float`, `float`
the x and y coordinate of the center of the main image
direct_f : `float`
the main image flux, relative to 1
"""
# the main image corresponds to the "shortest" path
i_straight = np.argmin([len(rrr.path) for rrr in r_forward])
direct_x = np.mean(r_forward[i_straight].x)
direct_y = np.mean(r_forward[i_straight].y)
direct_f = r_forward[i_straight].flux[0] # these are all equal
return i_straight, direct_x, direct_y, direct_f
[docs]def unpack_geom_params(geom_params, geom_labels):
""" Convert a list of geometry parameters into a dictionary as a telescope geometry configuration
Parameters
----------
geom_params : `list`
an ordered list of parameters corresponding to a geometry configuration
geom_labels : `list`
a list of the geometry parameter labels (names) matching the list above
Returns
-------
fitted_geom_config : `dict`
a dictionary with the geometry of the telescope to fit
"""
fitted_geom_config = {}
for i, lab in enumerate(geom_labels):
fitted_geom_config[lab] = geom_params[i]
return fitted_geom_config