superphot_pipeline.fake_image package

Class Inheritance Diagram

Module for simulating fake night sky observations.

class superphot_pipeline.fake_image.FakeRawImage(full_resolution, image_area, gain=1.0)

Bases: object

Create fake raw images with all bells and whistles.

Currently implemented:

• sky & stars
• bias, dark and flat instrumental effects
• bias and/or dark overscan areas
• hot pixels (simply set high dark current)
• discretization noise
• poisson noise

Examples

>>> from superphot_pipeline.fake_image import FakeRawImage
>>> import numpy

>>> #Create a 1044x1024 image with the first 10 pixels in x being a bias
>>> #area and the next 10 being a dark area.
>>> image = FakeRawImage(full_resolution=dict(x=1044, y=1024),
>>>                      image_area=dict(xmin=20,
>>>                                      xmax=1044,
>>>                                      ymin=0,
>>>                                      ymax=1024))

>>> #Bias level is 12.5 ADU
>>> image.add_bias(12.5)

>>> #Dark current is 2.3 ADU/s except for a hot column at x=100 with 10x
>>> #the dark current.
>>> dark = numpy.full((1044, 1024), 12.5)
>>> dark[:, 100] = 125.0
>>> image.set_dark(
>>>     rate=dark,
>>>     areas=[dict(xmin=10, xmax=20, ymin=0, ymax=1024)]
>>> )

>>> #Define a flat field which is a quadratic function in both x and y.
>>> x, y = numpy.meshgrid(numpy.arange(1024), numpy.arange(1024))
>>> flat = (2.0 - ((x - 512.0) / 512.0)**2) / 2.0
>>> image.set_flat_field(flat)

>>> #Add simple stars
>>> star = numpy.array([[0.25, 0.50, 0.25],
>>>                     [0.50, 1.00, 0.50],
>>>                     [0.25, 0.50, 0.25]])
>>> sky_flux = numpy.zeros((1024, 1024))
>>> for star_x in numpy.arange(50.0, 1024.0 - 50.0, 50.0):
>>>     for star_y in numpy.arange(50.0, 1024.0 - 50.0, 50.0):
>>>         sky_flux[star_y - 1 : star_y + 2,
>>>                  star_x - 1 : star_x + 2] = star
>>> image.set_sky(sky_flux)

>>> #Get image with the given parameters with 30s exposure
>>> exp1 = image(5)

__call__(exposure)

Simulate an exposure of the given duration.

Parameters:exposure – The amount of time to expose for in units consistent with the units used for the rates specified. Returns:

A 2-D numpy array containing the simulated exposure image

sprinkled with random poisson noise if gain is finite.

Return type:image

__init__(full_resolution, image_area, gain=1.0)

Start creating a fake image with the given parameters.

Parameters:

• full_resolution – The full resolution of the image to create, including the light sensitive area, but also overscan areas etc. Should be dict(x=<int>, y=<int>).
• image_area – The light sensitivy part of the image. The format is: dict(xmin = <int>, xmax = <int>, ymin = <int>, ymax = <int>)
• gain – The gain to assume for the A to D converter in electrons per ADU. Setting a non-finite value (+-infinity or NaN) disables poisson noise.

add_bias(bias, units='ADU')

Add a bias level to the full image.

Parameters:

• bias – The noiseless bias level to add. Should be a single value, a single row or column matching or a 2-D image with the y index being first. The row, column or the image should matchthe full reselotion of the fake image, not just the image area.
• units – Is the bias level specified in ‘electrons’ or in amplifier units (‘ADU’).

Returns:

None

set_dark(rate, areas, units='ADU')

Define the rate at which dark current accumulates.

Parameters:

• rate – The noiseless rate per unit time at which dark current accumulates. See bias argument of add_bias for details on the possible formats.
• areas – List of areas specified using the same format as the image_area argument of __init__ specifying the areas which accumulate dark current but no light.
• units – Is the dark rate specified in ‘ADU’ or ‘electrons’ per unit time.

Returns:

None

set_flat_field(flat)

Define the sensitivity map of the fake imaging system.

Parameters:flat – The noiseless map of the throughput of the system times the sensitivy of each pixel. Should have the same resolution as the image area (not the full image). Returns:None

set_sky(sky_flux, units='ADU')

Define the flux arriving from the sky (with or without stars).

Parameters:

• sky_flux – The image that a perfect imaging system (no bias, dark of flat) would see. Should only cover the imaging area.
• units – Is the sky flux specified in ‘ADU’ or ‘electrons’ per unit time.

Returns:

None

Submodules

• superphot_pipeline.fake_image.raw module
  • Class Inheritance Diagram