tlpipe.timestream.ps_fit.PsFit

class tlpipe.timestream.ps_fit.PsFit(parameter_file_or_dict=None, feedback=2)

Calibration by strong point source fitting.

This works by minimize

\[\chi^2 = \| V_{ij}^{\text{obs}}(t + \Delta t) - G_{ij} V_{ij}^{\text{sim}}(t) \|^2\]

Its solution is

\[G_{ij} = \frac{V_{ij}^{\text{sim} \dagger} V_{ij}^{\text{obs}}}{V_{ij}^{\text{sim} \dagger} V_{ij}^{\text{sim}}}\]

Attributes

cacheable	Override to return True if caching results is implemented.
embarrassingly_parallelizable	Override to return True if next() is trivially parallelizeable.
history	History that will be added to the output file.
iteration	Current iteration when iterable is True, None else.
params_init
prefix

__init__(parameter_file_or_dict=None, feedback=2)

Methods

cast_input(input)	Override to support accepting pipeline inputs of various types.
copy_input(tod)	Return a copy of tod, so the original tod would not be changed.
data_select(tod)	Data select.
finish()	Final analysis stage of pipeline task.
next([input])	Should not need to override.
process(ts)
read_input()	Method for reading time ordered data input.
read_output(filenames)	Override to implement reading outputs from disk.
read_process_write(tod)	Reads input, executes any processing and writes output.
restart_iteration()	Re-start the iteration.
setup([requires])	First analysis stage of pipeline task.
show_params()	Show all parameters that can be set and their default values of this task.
stop_iteration([force_stop])	Determine whether to stop the iteration.
subset_select(tod)	Data subset select.
write_output(output)	Method for writing time ordered data output.