sherpa.astro.ui.load_ascii_with_errors(id, filename=None, colkeys=None, sep=' ', comment='#', func=<function average>, delta=False)

Load an ASCII file with asymmetric errors as a data set.

Parameters: id (int or str, optional) – The identifier for the data set to use. If not given then the default identifier is used, as returned by get_default_id. filename (str) – The name of the file to read in. Selection of the relevant column depends on the I/O library in use (Crates or AstroPy). sep (str, optional) – The separator character. The default is ' '. comment (str, optional) – The comment character. The default is '#'. func (python function, optional) – The function used to combine the lo and hi values to estimate an error. The function should take two arguments (lo, hi) and return a single NumPy array, giving the per-bin error. The default function used is numpy.average. delta (boolean, optional) – The flag is used to indicate if the asymmetric errors for the third and fourth columns are delta values from the second (y) column or not. The default value is False

load_ascii()
Load an ASCII file as a data set.
load_arrays()
Create a data set from array values.
load_table()
Load a FITS binary file as a data set.
load_image()
Load an image as a data set.
resample_data()
Resample data with asymmetric error bars.
set_data()
Set a data set.
unpack_ascii()
Unpack an ASCII file into a data structure.

Notes

The function does not follow the normal Python standards for parameter use, since it is designed for easy interactive use. When called with a single un-named argument, it is taken to be the filename parameter. If given two un-named arguments, then they are interpreted as the id and filename parameters, respectively. The remaining parameters are expected to be given as named arguments.

The column order for the different data types are as follows, where x indicates an independent axis, y the dependent axis, the asymmetric errors elo and ehi.

Data1DAsymmetricErrs x, y, elo, ehi

Examples

Read in the first four columns of the file, as the independent (X), dependent (Y), error low (ELO) and error high (EHI) columns of the default data set:

>>> load_ascii_with_errors('sources.dat')


Read in the first four columns (x, y, elo, ehi) where elo and ehi are of the form y - delta_lo and y + delta_hi, respectively.

>>> load_ascii_with_errors('sources.dat', delta=True)


Read in the first four columns (x, y, elo, ehi) where elo and ehi are of the form delta_lo and delta_hi, respectively.

>>> def rms(lo, hi):
...     return numpy.sqrt(lo * lo + hi * hi)
...