Python Scripts
There are several Python (the scripting language) scripts written to prepare input for and analyse the output of python (the C code).
Some of the more useful scripts/modules are documented below. Alternatively, you can generate documentation
for all the scripts by navigating to docs/pydocs and running write_docs.py. The resulting output file can be found here.
Todo
Finish adding modules below.
py_read_output
- Synopsis:
This program enables one to read outputs from the Python radiative transfer code. Where possible, we use the astropy.io module to read outputs. There are also a number of routines for processing and reshaping various data formats
see https://github.com/agnwinds/python/wiki/Useful-python-commands-for-reading-and-processing-outputs for usage
Usage:
Arguments:
- py_read_output.read_convergence(root)
check convergence in a diag file
- py_read_output.read_emissivity(root)
Read macro atom emissivities from a root diag file. Returns two arrays, kpkt_emiss and matom_emiss.
- py_read_output.read_pf(root)
reads a Python .pf file and returns a dictionary
- Parameters
- rootfile or str
File, filename to read.
- new:
True means the Created column exists in the file
- Returns
- pf_dict
Dictionary object containing parameters in pf file
- py_read_output.read_pywind(filename, return_inwind=False, mode='2d', complete=True)
read a py_wind output file using np array reshaping and manipulation
- Parameters
- filenamefile or str
File, filename to read, e.g. root.ne.dat
- return_inwind: Bool
return the array which tells you whether you are partly, fully or not inwind.
- mode: string
can be used to control different coord systems
- Returns
- x, z, value: masked arrays
value is the quantity you are concerned with, e.g. ne
- py_read_output.read_pywind_summary(filename, return_inwind=False, mode='2d')
read a py_wind output file using np array reshaping and manipulation
- Parameters
- filenamefile or str
File, filename to read, e.g. root.ne.dat
- return_inwind: Bool
return the array which tells you whether you are partly, fully or not inwind.
- mode: string
can be used to control different coord systems
- Returns
- d: astropy.Table.table.table object
value is the quantity you are concerned with, e.g. ne
- py_read_output.read_spectrum(filename)
Load data from a spectrum output file from the radiative transfer code Python
- Parameters:
filename : file or str
File, filename, or generator to read. If the filename extension is
.gzor.bz2, the file is first decompressed. Note that generators should return byte strings for Python 3k.- Returns
Success: spectrum returns a Table of class astropy.table.table.Table
Failure returns 1
- py_read_output.read_spectrum_to_class(filename, new=True)
reads a Python .spec file and places in specclass array, which is returned
- Parameters
- filenamefile or str
File, filename to read.
- new:
True means the Created column exists in the file
- Returns
Success: spectrum returns a spectrum class cls.specclass
Failure returns 1
- py_read_output.setpars()
set some standard parameters for plotting
- py_read_output.thinshell_read(root)
Read py_wind output filename for thin shell models with one cell
- py_read_output.write_pf(root, pf_dict)
writes a Python .pf file from a dictionary
- Parameters
- rootfile or str
File, filename to write.
- pf_dict:
dictionary to write
- Returns
- pf_dict
Dictionary object containing parameters in pf file
py_plot_output
- Synopsis:
various plotting routines for making standard plots from Python outputs
- Usage:
Either import as a module in a python session e.g. import py_plot_output as p
or run from the command line e.g.
py_plot_output root mode [roots to compare]
- Arguments:
- root
root filename to analyse
- mode
mode of plotting wind plot of common wind quantites ions plot of common ions spec spectrum for different viewing angles spec_comps components contributing to total spectrum e.g. disk, wind compare compare the root to other roots to compare all make all the above plots
- py_plot_output.make_spec_comparison_plot(s_array, labels, fname='comparison', smooth_factor=10, angles=True, components=False)
make a spectrum comparison plot from array of astropy.table.table.Table objects. Saves output as “spectrum_%s.png” % (fname)
- Parameters:
- s_array: array-like of astropy.table.table.Table objects
table containing spectrum data outputted from Python
- labels: array-like
strings of labels for each spectrum
- fname: str
filename to save as e.g. sv
- smooth_factor: int
factor you would like to smooth by, default 10
- angles: Bool
Would you like to plot the viewing angle spectra?
- components: Bool
would you like to plot the individual components e.g. Disk Wind
- Returns:
Success returns 0 Failure returns 1
- py_plot_output.make_spec_plot(s, fname, smooth_factor=10, angles=True, components=False, with_composite=False)
make a spectrum plot from astropy.table.table.Table object. Saves output as “spectrum_%s.png” % (fname)
- Parameters:
- s: astropy.table.table.Table
table containing spectrum data outputted from Python
- fname: str
filename to save as e.g. sv
- smooth_factor: int
factor you would like to smooth by, default 10
- angles: Bool
Would you like to plot the viewing angle spectra?
- components: Bool
would you like to plot the individual components e.g. Disk Wind
- Returns:
Success returns 0 Failure returns 1
- py_plot_output.make_spec_plot_from_class(s, fname, smooth_factor=10, angles=True, components=False)
make a spectrum plot from py_classes.specclass object. Saves output as “spectrum_%s.png” % (fname)
- Parameters:
- s: specclass object
table containing spectrum data outputted from Python
- fname: str
filename to save as e.g. sv
- smooth_factor: int
factor you would like to smooth by, default 10
- angles: Bool
Would you like to plot the viewing angle spectra?
- components: Bool
would you like to plot the individual components e.g. Disk Wind
- Returns:
Success returns 0 Failure returns 1
- py_plot_output.make_wind_plot(d, fname, var=None, shape=(4, 2), axes='log', den_or_frac=0, fname_prefix='wind', lims=None)
make a wind plot from astropy.table.table.Table object. Saves output as “spectrum_%s.png” % (fname)
- Parameters:
- d: astropy.table.table.Table
table containing wind data outputted from Python if == None then this routine will get the data for you
- fname: str
filename to save as e.g. sv
- var: array type
array of string colnames to plot
- angles: Bool
Would you like to plot the viewing angle spectra?
- components: Bool
would you like to plot the individual components e.g. Disk Wind
- axes: str
lin or log axes
- den_or_frac: int
0 calculate ion densities 1 calculate ion fractions
- lims: array-like
limits of plot, specified as ((xmin,xmax), (ymin, tmax)) can be array or tuple. Default is Nonetype.
- Returns:
Success returns 0 Failure returns 1
py_plot_util
- Synopsis:
various utilities for processing Python outputs and plotting spectra and wind properties
Usage:
Arguments:
- py_plot_util.get_flux_at_wavelength(lambda_array, flux_array, w)
Find the flux at wavelength w
- Parameters:
- lambda_array: array-like
array of wavelengths in angstroms. 1d
- flux_array: array-like
array of fluxes same shape as lambda_array
- w: float
wavelength in angstroms to find
- Returns:
- f: float
flux at point w
- py_plot_util.get_pywind_summary(fname, vers='', den_or_frac=0)
run version vers of py_wind on file fname.wind_save and generate the complete wind summary as output
produce the output fname.complete to read
if den_or_frac is 1, return fractions, otherwise densities
- py_plot_util.parse_rcparams(fname='params.rc')
parse the file params.rc and set values in matplotlib.rcparams
file should be of format
font.family : serif mathtext.fontset : custom
- py_plot_util.read_pywind_smart(filename, return_inwind=False)
read a py_wind file using np array reshaping and manipulation
DEPRECATED
- py_plot_util.run_py_wind(fname, vers='', cmds=None, ilv=None)
run version vers of py_wind on file fname.wind_save
- py_plot_util.smooth(x, window_len=20, window='hanning')
smooth data x by a factor with window of length window_len
- py_plot_util.wind_to_masked(d, value_string, return_inwind=False, mode='2d')
turn a table, one of whose colnames is value_string, into a masked array based on values of inwind
- Parameters:
- d: astropy.table.table.Table object
data, probably read from .complete wind data
- value_string: str
the variable you want in the array, e.g. “ne”
- return_inwind: Bool
return the array which tells you whether you are partly, fully or not inwind.
- Returns:
- x, z, value: Floats
value is the quantity you are concerned with, e.g. ne
run_check
- Synopsis:
Sumarize a model run with python, ultimately generating an html file with various plots, etc.
- Command line usage (if any):
run_check.py root1 [root2 …]
run_check.py root1.pf [root2.pf …]
run_check -all
run_check -h
- Description:
This routine performs basic checks on one or more python runs and creates an html file for each that is intended to provide a quick summary of a run.
The user can enter the runs to be tested from the command line, either in the form of a set of root names or .pf names. Wildcarding, e.g
*.pfcan be used.*.out.pffiles will be ignored.Alternatively to process all of the files in a directory, one can use the switch -all (which supercedes anything else).
In all cases the routine checks to see if the appropriate wind_save file exists before attempting to run.
-h delivers this documentation
- Primary routines:
doit - processes a single file steer - processes the command line and calls doit for each file.
Notes:
- run_check.check_completion(root)
Verify that the run actually completed and provide information about the timeing, from the .sig file
- run_check.doit(root='ixvel', outputfile='out.txt')
Create a summary of a Python run, which will enough information that one can assess whether the run was successful
Description:
Notes:
History:
- run_check.how_many_dimensions(filename)
Check whether a windsave file is one or two dimenaions
- run_check.make_html(root, converge_plot, te_plot, tr_plot, spec_tot_plot, spec_plot, nspectra=3, complete_message=['test'], errors=['test', 'test2'])
Make an html file that collates all the results
- run_check.plot_converged(root, converged, converging, t_r, t_e, hc)
Make a plot of the convergence statistics in the diag directroy
- run_check.py_error(root)
Run py_error.py and capture the output to the screen
- Note:
py_error could be refactored so that it did not need to be run from the command line, but this is the simplest way to capture the outputs at present
- run_check.read_diag(root)
Get convergence and possibly other information from the diag file
- run_check.steer(argv)
Process the command line
- run_check.windsave2table(root)
Run windsave2table
import_cyl
- Synopsis:
Read the master file produced by windsave2table for a model created in cylindrical coordinates and produce a file which can be imported into Python and run
- Command line usage (if any):
import_cyl.py rootnamewhere rootname is the rootname of the mastertable or windsave file- Description:
This operates on the mastertable produced by windsavetable
- Primary routines:
doit
Notes:
- import_cyl.doit(root='cv', outputfile='')
Read a master.txt file for models in cylindrical coordinates and produce a file which can be read in to python
Description:
Notes:
History:
- import_cyl.read_file(filename, char='')
Read a file and split it into words, eliminating comments
char is an optional parameter used as the delimiter for splitting lines into words. Otherwise white space is assumed.
- import_cyl.read_table(filename='foo.txt', format='')
Read a file using astropy.io.ascii and return this
Description:
Notes:
History: