import numpy as np
from astropy.io import ascii
from astropy.table import Table
import astropy.units as u
import re
[docs]def isLambda(obj: object):
"""
Check if a object is of type lambda
Parameters
----------
obj : object
The object to check.
Returns
-------
res : bool
Result of the check
"""
return isinstance(obj, type(lambda: None)) and obj.__name__ == (lambda: None).__name__
[docs]def rasterizeCircle(grid: np.ndarray, radius: float, xc: float, yc: float):
"""
Map a circle on a rectangular grid.
Parameters
----------
grid : ndarray
The grid to map the circle onto.
radius : float
Radius of the circle to be mapped.
xc : float
X-index of the circle's center point. The origin of the coordinate system is in the top left corner.
yc : float
Y-index of the circle's center point. The origin of the coordinate system is in the top left corner.
Returns
-------
grid: ndarray
The grid with the circle mapped onto. Each point contained within the circle is marked as 1.
"""
xc_pix = int(round(xc)) # X center in pixel coordinates
x_shift = xc_pix - xc # X shift of the circle center
yc_pix = int(round(yc)) # Y center in pixel coordinates
y_shift = yc_pix - yc # Y shift of the circle center
radius_pix = int(np.ceil(radius)) + 1 # Length of the square containing the pixels to be checked
r2 = radius ** 2 # square of the radius
# Create meshgrid for the x and y range of the circle
dx, dy = np.meshgrid(range(- radius_pix if xc_pix >= radius_pix else - xc_pix,
radius_pix + 1 if grid.shape[1] > (xc_pix + radius_pix + 1) else grid.shape[1] - xc_pix),
range(- radius_pix if yc_pix >= radius_pix else - yc_pix,
radius_pix + 1 if grid.shape[0] > (yc_pix + radius_pix + 1) else grid.shape[0] - yc_pix))
dx2 = (dx + x_shift) ** 2 # Square of the x-component of the current pixels radius
dx_side2 = (dx + x_shift + ((dx < 0) - 0.5)) ** 2 # Square of the x-component of the neighbouring pixels radius
dy2 = (dy + y_shift) ** 2 # Square of the y-component of the current pixels radius
dy_side2 = (dy + y_shift + ((dy < 0) - 0.5)) ** 2 # Square of the y-component of the neighbouring pixels radius
res = np.logical_or(dx_side2 + dy2 <= r2, dx2 + dy_side2 < r2) # Check if pixel is inside or outside
grid[(dy.min() + yc_pix):(dy.max() + yc_pix + 1), (dx.min() + xc_pix):(dx.max() + xc_pix + 1)] = res
grid[yc_pix, xc_pix] = 1 # Set the center pixel by default
# fig, ax = plt.subplots()
# plt.imshow(grid)
# circle = plt.Circle((xc, yc), radius, color='r', fill=False)
# ax.add_artist(circle)
# plt.show()
return grid
[docs]def readCSV(file: str, units: list = None, format_: str = None) -> Table:
"""
Read a CSV file and parse the units in the header
Parameters
----------
file : str
The path to the file to read.
units : list
A list of the default units for the columns.
format_ : str
The format to be used for reading (see also astropy table formats).
Returns
-------
data : Table
The read table as astropy Table object.
"""
# Read the file
data = ascii.read(file, format=format_)
# Check if units are given
if data[data.colnames[0]].unit is None:
# Convert values to float
for i in range(len(data.columns)):
data[data.colnames[i]] = list(map(float, data[data.colnames[i]]))
# Check if units are given in column headers
if all([re.search("\\[.*\\]", x) for x in data.colnames]):
# Extract units from headers and apply them on the columns
# noinspection PyArgumentList
units_header = [u.Unit(re.findall("(?<=\\[).*(?=\\])", x)[0]) for x in data.colnames]
for i in range(len(data.columns)):
data[data.colnames[i]].unit = units_header[i]
if units is not None and len(units) == len(data.columns):
for i in range(len(data.columns)):
if data[data.colnames[i]].unit.is_equivalent(u.Hz) and units[i].is_equivalent(u.m):
data[data.colnames[i]] = data[data.colnames[i]].to(units[i], equivalencies=u.spectral())
else:
try:
data[data.colnames[i]] = data[data.colnames[i]].to(units[i])
except:
data[data.colnames[i]] = data[data.colnames[i]].to(units[i],
equivalencies=u.spectral_density(
u.Quantity(data[data.colnames[0]])))
# Use default units
elif units is not None and len(units) == len(data.columns):
for i in range(len(data.columns)):
data[data.colnames[i]].unit = units[i]
return data