Command Comparison: Sherpa 3.4 vs. Sherpa 4.4

The table below provides the Sherpa 4.4 (Python) translation for a list of commonly used Sherpa 3.4 commands, to assist with your transition to the new syntax. See the Sherpa ahelp pages for detailed information on each Sherpa 4.4 function.

To view complete Sherpa 3.4 and 4.4 Python scripts side-by-side for various 1-D and 2-D plotting and fitting scenarios, visit the Sherpa Gallery of Examples, which includes eighteen common Sherpa use cases.

The CXC is committed to helping Sherpa users transition to new the syntax as smoothly as possible. If you have existing Sherpa scripts or save files, submit them to us via the CXC Helpdesk and we will provide the Sherpa 4.4 syntax to you.

Sherpa 3.4 Sherpa 4.4

ANALYSIS

set_analysis([id], quantity, [type, factor])

Assuming data set with given ID contains PHA data:

quantity - "energy", "wavelength", "channel", or "bin"
type - "rate", "counts"
factor - 0, 1, 2, ..., n

BACK load_bkg([id], arg, [use_errors, bkg_id])

Assuming data set with given ID contains PHA data:

arg - filename and path | PHACrate obj | PyFITS HDUList obj

BACKERRORS | BERRORS | BSTATERRORS get_staterror([id, filter, bkg_id])
get_error([id, filter, bkg_id])

BACKGROUND | BG set_bkg_model([id], model, [bkg_id])

BDCOUNTS calc_data_sum([lo, hi, id, bkg_id])

BEFLUX calc_energy_flux([lo, hi, id, bkg_id])

BGROUP group([id, bkg_id])

BMCOUNTS calc_model_sum([lo, hi, id, bkg_id])

BSYSERRORS Assuming data set with given ID contains PHA data: get_syserror([id, filter, bkg_id])

BUNGROUP ungroup([id, bkg_id])

BYE | EXIT | QUIT Ctrl-D, exit

CLOSE TBD

COORD set_coord([id], coord)

COVARIANCE covar([id, otherids ... , pars])

CPLOT contour_data([id])
contour_model([id])
contour_fit([id])
contour_resid([id])
contour_ratio([id])
contour_psf([id])
contour_fit_resid([id])
contour_kernel([id]) or
contour(arg1, [id], arg2, [id], ...])

where arg* is one of "data", "model", "fit", "psf", "resid", or "ratio"

CREATE abs1 = xsphabs.abs1 or abs1 = create_model_component("xsphabs", "abs1")

DATA arg - filename and path | PHACrate obj | PyFITS HDUList obj

load_arf([id], arg, [resp_id, bkg_id])
load_ascii([id], arg, [ncols, colkeys, dstype, sep, comment])
load_data([id], filename, [...])
load_image([id], arg, [coord])
load_pha([id], arg, [use_errors])
load_rmf([id], arf, [resp_id, bkg_id])
load_table([id], arg, [ncols, colkeys, dstype])
load_filter([id], filename, [bkg_id])
load_grouping([id], filename, [bkg_id])
load_quality([id], filename, [bkg_id])
load_staterror([id], filename, [bkg_id], [options])
load_syserror([id], filename, [bkg_id], [options])

DATASPACE dataspace1d(start, stop, [step, numbins, id, bkg_id, dstype])
dataspace2d(dims, [id, dstype])

dstype - Data1DInt, Data2D, Data2DInt, DataARF, DataIMG, DataPHA, or DataRMF

DCOUNTS calc_data_sum([lo, hi, id, bkg_id])

ECHO For Python users, IPython's logging mechanism is an option. %logstart ... %logstop

EFLUX calc_energy_flux([lo, hi, id, bkg_id])

EQWIDTH eqwidth(cont, cont+eline, [lo, hi], [id], [bkg_id])

ERASE clean()

ERRORS get_error([id, filter, bkg_id])

FAKEIT fake_pha(id, arf, rmf, exposure, [backscal, areascal, grouping, grouped, quality, bkg])

FEFFILE Not available

FEFPLOT Not available

FIT | RUN fit([id, otherids ..., outfile, clobber]) fit_bkg([id, otherids ..., outfile, clobber])

FLUX calc_photon_flux([lo, hi, id, bkg_id])

FREEZE freeze(list params or models)

FTEST calc_ftest(dof_1, stat_1, dof_2, stat_2)

GETX TBD

GETY TBD

GOODNESS calc_stat_info() / get_stat_info()

get_fit_results()

get_fit_results().statval
get_fit_results().numpoints
get_fit_results().dof
get_fit_results().qval
get_fit_results().rstat
get_fit_results().nfev
get_fit_results().modelvals
get_fit_results().parnames
get_fit_results().parvals

GROUP group([id, bkg_id])
group_bins([id,] num [,bkg_id])
group_counts([id,] num [,bkg_id])
group_snr([id,] snr [,bkg_id])
group_adapt([id,] min [,bkg_id])
group_adapt_snr([id,] min [,bkg_id])
group_width([id,] num [,bkg_id])

IGNORE

Apply to all data sets:

Python	CIAO 3.4
`ignore(3, 5)`	`IGNORE FILTER 3:5`
`ignore(3)`	`IGNORE FILTER 3:`
`ignore(None, 5)`	`IGNORE FILTER :5`
`ignore("4,8:,1:3")`	`IGNORE FILTER 4, 8:, 1:3`
`ignore()`	`IGNORE ALL`

Apply to one data set:

Python	CIAO 3.4
`ignore_id(id, 3, 5)`	`IGNORE id FILTER 3:5`
`ignore_id(id, 3)`	`IGNORE id FILTER 3:`
`ignore_id(id, None, 5)`	`IGNORE id FILTER :5`
`ignore_id(id, "4,8:,1:3")`	`IGNORE id FILTER 4, 8:, 1:3`
`ignore_id(id)`	`IGNORE id ALL`

IMAGE image_data()
image_model()
image_model_component() / get_model_component_image()
image_source_component() / get_source_component_image()
image_fit()
image_psf()
image_ratio()
image_resid()
image_source()
image_kernel()

INSTRUMENT | RESPONSE load_rmf() load_arf() load_psf() set_full_model()

INTEGRATE abs1 = atten.abs1 abs1.integrate = True abs1.integrate = False

INTERVAL-PROJECTION | INT-PROJ int_proj(param, [id, otherids, replot, min, max, nloop, delv, fac, log, overplot])

Print reg_proj parameters

print(get_int_proj())

INTERVAL-UNCERTAINTY | INT-UNC int_unc(param, [id, otherids, replot, min, max, nloop, delv, fac, log, overplot])

Print reg_unc parameters

print(get_int_unc())

JOURNAL

IPython's history mechanism is an option:

!cat ~/.ipython-ciao/history-sherpa

LINK link()

LPLOT plot_arf([id, resp_id, replot, overplot])
plot_bkg([id, bkg_id, replot, overplot])
plot_bkg_chisqr([id, bkg_id, replot, overplot])
plot_bkg_delchi([id, bkg_id, replot, overplot])
plot_bkg_fit([id, bkg_id, replot, overplot])
plot_bkg_fit_delchi([id, bkg_id, replot, overplot])
plot_bkg_fit_resid([id, bkg_id, replot, overplot])
plot_bkg_model([id, bkg_id, replot, overplot])
plot_bkg_ratio([id, bkg_id, replot, overplot])
plot_bkg_resid([id, bkg_id, replot, overplot])
plot_bkg_source([id, lo, hi, bkg_id, replot, overplot])
plot_chisqr([id, replot, overplot])
plot_data([id, replot, overplot])
plot_delchi([id, replot, overplot])
plot_fit([id, replot, overplot])
plot_fit_delchi([id, replot, overplot])
plot_fit_resid([id, replot, overplot])
plot_model([id, replot, overplot])
plot_model_component([id], name [,replot, overplot])
plot_source_component([id], name [,replot, overplot])
plot_ratio([id, replot, overplot])
plot_resid([id, replot, overplot])
plot_source([id, lo, hi, replot, overplot])
plot_kernel([id, replot, overplot]) or

plot(arg1, [id], arg2, [id], ...)

where arg* is one of "arf","bkg","bkgchisqr", "bkgdelchi","bkgfit","bkgmodel","bkgratio", "bkgresid","bkgsource","chisqr","data","delchi", "fit","model","psf","ratio","resid","source"

MCOUNTS calc_model_sum([lo, hi, id, bkg_id])

METHOD | SEARCHMETHOD set_method(method_name)

MLR calc_mlr(delta_dof, delta_stat)

NOTICE

Apply to all data sets:

Python	CIAO 3.4
`notice(3, 5)`	`NOTICE FILTER 3:5`
`notice(3)`	`NOTICE FILTER 3:`
`notice(None, 5)`	`NOTICE FILTER :5`
`notice("4,8:,1:3")`	`NOTICE FILTER 4, 8:, 1:3`
`notice()`	`NOTICE ALL`

Apply to one data set:

Python	CIAO 3.4
`notice_id(id, 3, 5)`	`NOTICE id FILTER 3:5`
`notice_id(id, 3)`	`NOTICE id FILTER 3:`
`notice_id(id, None, 5)`	`NOTICE id FILTER :5`
`notice_id(id, "4,8:,1:3")`	`NOTICE id FILTER 4, 8:, 1:3`
`notice_id(id)`	`NOTICE id ALL`

OPEN image_open()

OPLOT plot_data(overplot=True)

PARAMPROMPT paramprompt()

PLOTY TBD

PROJECTION

proj([id, otherids ..., param])

Also see the conf command, new in CIAO 4.2:

conf([id, otherids ..., param])

PROMPT Not available

READ arg - filename and path | PHACrate obj | PyFITS HDUList obj

load_arf([id], arg, [resp_id, bkg_id])
load_ascii([id], arg, [ncols, colkeys, dstype, sep, comment])
load_data([id], filename, [...])
load_image([id], arg, [coord])
load_pha([id], arg, [use_errors])
load_rmf([id], arf, [resp_id, bkg_id])
load_table([id], arg, [ncols, colkeys, dstype])

RECORD fit(outfile=<filename>, clobber=True)

REGION-PROJECTION | REG-PROJ reg_proj(param_1, param_2, [id, otherids, replot, min, max, nloop, delv, fac, log, sigma, levels, overplot])

Print reg_proj parameters

print(get_reg_proj())

REGION-UNCERTAINTY | REG-UNC reg_unc(param_1, param_2, [id, otherids, replot, min, max, nloop, delv, fac, log, sigma, levels, overplot])

Print reg_unc parameters

print(get_reg_unc())

RENAME modelb = gauss1d.modelb

modelB = modelb

RESET reset(get_model())

reset(p1)

RESPONSE | INSTRUMENT load_rmf()
load_arf()
load_psf()

SAVE save([filename]) --> produces binary file
restore([filename])

save_all([outfile, clobber]) --> produces text file
execfile(filename)

script([filename, clobber]) --> produces text (log) file
execfile(filename)

SEARCHMETHOD | METHOD set_method(method_name)

SETBACK Assuming data set with given ID contains PHA data:

set_counts([id], val, [bkg_id])
set_exposure([id], exptime, [bkg_id])
set_backscal([id], backscale, [bkg_id])
set_areascal([id], area, [bkg_id])

SETDATA Assuming data set with given ID contains PHA data:

set_counts([id], val, [bkg_id])
set_exposure([id], exptime, [bkg_id])
set_backscal([id], backscale, [bkg_id])
set_areascal([id], area, [bkg_id])

SHOW Show session objects

show_all([id, outfile, clobber])
show_data([id, outfile, clobber])
show_covar([outfile, clobber])
show_filter([id, outfile, clobber])
show_method([outfile, clobber])
show_model([id, outfile, clobber])
show_proj([outfile, clobber])
show_source([id, outfile, clobber])
show_stat([outfile, clobber])
show_psf([id, outfile, clobber])
show_kernel([id, outfile, clobber])
show_bkg([id, bkg_id, outfile, clobber])
show_bkg_source([id, bkg_id, outfile, clobber])
show_bkg_model([id, bkg_id, outfile, clobber])

List session state info

list_bkg_ids()
list_data_ids()
list_methods()
list_model_components()
list_model_ids()
list_models()
list_response_ids()
list_stats()

SOURCE | SRC set_source(expression) set_full_model(experession)

SPLOT Not available

STATISTIC set_stat(stat_name)

calc_stat([id, otherids ...])
calc_chisqr([id, otherids ...])

SUBTRACT subtract([id])

STATERRORS get_staterror([id, filter, bkg_id]) set_staterror([id], val, [fractional,] [bkg_id])

SYSERRORS get_syserror([id, filter, bkg_id]) set_syserror([id], val, [fractional,] [bkg_id])

THAW thaw(list params or model)

TRUNCATE TBD

UNCERTAINTY

Not available. Try covariance or conf.

UNGROUP ungroup([id, bkg_id])

UNLINK unlink(param)

UNSUBTRACT unsubtract([id])

USE Execute a script:
execfile(filename)

Restore a previous Sherpa session
restore([filename])

VERSION import sherpa sherpa.__version__

WRITE save_arrays(filename, args, [fields,ascii,clobber])
save_delchi([id], filename, [bkg_id,ascii,clobber])
save_error([id], filename, [bkg_id,ascii,clobber])
save_filter([id], filename, [bkg_id,ascii,clobber])
save_grouping([id], filename, [bkg_id,ascii,clobber])
save_model([id], filename, [bkg_id,ascii,clobber])
save_quality([id], filename, [bkg_id,ascii,clobber])
save_resid([id], filename, [bkg_id,ascii,clobber])
save_source([id], filename, [bkg_id,ascii,clobber])

XSPEC ABUNDAN set_xsabund(name) get_xsabund()

XSPEC XSECT set_xsxsect(name) get_xsxsect()