imcascade.results
Module Contents
Classes
A class used for collating imcascade results and performing analysis |
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A Class to analyze and combine multiple ImcascadeResults classes using evidence weighting |
Functions
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- imcascade.results.calc_flux_input(weights, sig, cutoff=None)
- imcascade.results.r_root_func(r, f_L, weights, sig, cutoff)
- class imcascade.results.ImcascadeResults(Obj, thin_posterior=1)
A class used for collating imcascade results and performing analysis
- Parameters
Obj (imcascade.fitter.Fitter class, dictionary or str) – Object which contains the data to be analyzed. Can be a Fitter object once the run_(ls_min,dynesty, emcee) has been ran. If it is a dictionay needs to contain, at bare minmum the variables sig, Ndof, Ndof_sky, Ndof_gauss, log_weight_scale and either min_param or posterior. If a string is passed it will be interreted as a file locations with an ASDF file containing the neccesary information.
thin_posterior (int (optional)) – Factor by which to thin the posterior distribution by. While one wants to ensure the posterior is large enough, some of this analysis can take time if you have >10^6 samples so this is one way to speed up this task but use with caution.
- calc_flux(cutoff=None)
Calculate flux of given results
- Parameters
cutoff (float (optional)) – Radius out to which to consider the profile. Generally this should be around the half-width of the image or the largest gaussian width use
- Returns
Flux – Total flux of best fit model
- Return type
float or Array
- _min_calc_rX(X, cutoff=None)
Old and slow Function to calculate the radius containing X percent of the light
- Parameters
X (float) – Fractional radius of intrest to calculate. if X < 1 will take as a fraction, else will interpret as percent and divide X by 100. i.e. to calculate the radius containing 20% of the light, once can either pass X = 20 or 0.2
cutoff (float (optional)) – Radius out to which to consider the profile. Generally this should be around the half-width of the image or the largest gaussian width used
- Returns
r_X – The radius containg X percent of the light
- Return type
float or Array
- calc_rX(X, cutoff=None)
Function to calculate the radius containing X percent of the light
- Parameters
X (float) – Fractional radius of intrest to calculate. if X < 1 will take as a fraction, else will interpret as percent and divide X by 100. i.e. to calculate the radius containing 20% of the light, once can either pass X = 20 or 0.2
cutoff (float (optional)) – Radius out to which to consider the profile. Generally this should be around the half-width of the image or the largest gaussian width used
- Returns
r_X – The radius containg X percent of the light
- Return type
float or Array
- calc_r90(cutoff=None)
Wrapper function to calculate the radius containing 90% of the light
- Parameters
cutoff (float (optional)) – Radius out to which to consider the profile. Generally this should be around the half-width of the image or the largest gaussian width use
- Returns
r_90 – The radius containg 90 percent of the light
- Return type
float or Array
- calc_r80(cutoff=None)
Wrapper function to calculate the radius containing 80% of the light
- Parameters
cutoff (float (optional)) – Radius out to which to consider the profile. Generally this should be around the half-width of the image or the largest gaussian width use
- Returns
r_80 – The radius containg 80 percent of the light
- Return type
float or Array
- calc_r50(cutoff=None)
Wrapper function to calculate the radius containing 50% of the light, or the effective radius
- Parameters
cutoff (float (optional)) – Radius out to which to consider the profile. Generally this should be around the half-width of the image or the largest gaussian width use
- Returns
r_50 – The radius containg 50 percent of the light
- Return type
float or Array
- calc_r20(cutoff=None)
Wrapper function to calculate the radius containing 20% of the light
- Parameters
cutoff (float (optional)) – Radius out to which to consider the profile. Generally this should be around the half-width of the image or the largest gaussian width use
- Returns
r_20 – The radius containg 20 percent of the light
- Return type
float or Array
- calc_sbp(r, return_ind=False)
Function to calculate surface brightness profiles for the given results
- Parameters
r (float or array) – Radii (in pixels) at which to evaluate the surface brightness profile
return_ind (bool (optional)) – If False will only return the sum of all gaussian, i.e. the best fit profile. If true will return an array with +1 dimensions containing the profiles of each individual gaussian component
- Returns
SBP – Surface brightness profiles evaluated at ‘r’. If ‘return_ind = True’, returns the profile of each individual gaussian component
- Return type
array
- calc_obs_sbp(r, return_ind=False)
Function to calculate the observed surface brightness profiles, i.e. convolved with the PSF for the given results
- Parameters
r (float or array) – Radii (in pixels) at which to evaluate the surface brightness profile
return_ind (bool (optional)) – If False will only return the sum of all gaussian, i.e. the best fit profile. If true will return an array with +1 dimensions containing the profiles of each individual gaussian component
- Returns
obsereved SBP – Observed surface brightness profiles evaluated at ‘r’. If ‘return_ind = True’, returns the profile of each individual gaussian component
- Return type
array
- calc_cog(r, return_ind=False, norm=False, cutoff=None)
Function to calculate curves-of-growth for the given results
- Parameters
r (float or array) – Radii (in pixels) at which to evaluate the surface brightness profile
return_ind (bool (optional)) – If False will only return the sum of all gaussian, i.e. the best fit profile. If true will return an array with +1 dimensions containing the profiles of each individual gaussian component
norm (Bool (optional)) – Wether to normalize curves-of-growth to total flux, calculated using ‘self.calc_flux’. Does nothing if ‘return_ind = True’
cutoff (Float (optional)) – Cutoff radius used in ‘self.calc_flux’, only is used if ‘norm’ is True
- Returns
COG – curves-of-growth evaluated at ‘r’. If ‘return_ind = True’, returns the profile of each individual gaussian component
- Return type
array
- calc_obs_cog(r, return_ind=False, norm=False, cutoff=None)
Function to calculate the observed curve of growth, i.e. convolved with the PSF for the given results
- Parameters
r (float or array) – Radii (in pixels) at which to evaluate the surface brightness profile
return_ind (bool (optional)) – If False will only return the sum of all gaussian, i.e. the best fit profile. If true will return an array with +1 dimensions containing the profiles of each individual gaussian component
norm (Bool (optional)) – Wether to normalize curves-of-growth to total flux, calculated using ‘self.calc_flux’. Does nothing if ‘return_ind = True’
cutoff (Float (optional)) – Cutoff radius used in ‘self.calc_flux’, only is used if ‘norm’ is True
- Returns
observed COG – curves-of-growth evaluated at ‘r’. If ‘return_ind = True’, returns the profile of each individual gaussian component
- Return type
array
- run_basic_analysis(zpt=None, cutoff=None, errp_lo=16, errp_hi=84, save_results=False, save_file='./imcascade_results.asdf')
Function to calculate a set of common variables and save the save the results
- Parameters
zpt (float (optional)) – photometric zeropoint for the data. if not ‘None’, will also calculate magnitude
cutoff (float (optional)) – Radius out to which to consider the profile. Generally this should be around the half-width of the image or the largest gaussian width use
errp_(lo,hi) (float (optional)) – percentiles to be used to calculate the lower and upper error bars from the posterior distribution. Default is 16 and 84, corresponding to 1-sigma for a guassian distribtuion
save_results (bool (optional)) – If true will save results to file. If input is a file, will add to given file, else will save to file denoted by ‘save_file’ (see below)
save_file (str) – String to describe where to save file, only applicaple if the input is not a file.
- Returns
res_dict – Dictionary contining the results of the analysis
- Return type
dictionary
- calc_iso_r(I, zpt=None, pix_scale=None)
Function to calculate the isophotal radius
- Parameters
I (float) – Surface brightness target to define the isophotal radii. By defualt this shoud be in image units unless both zpt and pix_scale are given, then I is interpreted as mag per arcsec^2.
zpt (float (optional)) – zeropoint magnitude of image, used to convert I to mag per arcsec^2
pix_scale (float (optional)) – pixel scale in units of arcseconds/pixel, used to convert I to mag per arcsec^2
- Returns
r_I – The radius, in pixel units, where the surface brightness profile matches I
- Return type
float or Array
- calc_petro_r(P_ratio=0.2, r_fac_min=0.8, r_fac_max=1.25)
Function to calculate the petrosian radii of a galaxy
- Parameters
P_ratio (float (optional)) – The Petrosian ratio which defines the Petrosian radii, default is 0.2
r_fac_min (float (optional)) – lower multiplicative factor which is used to integrate flux, default 0.8
r_fac_max (float (optional)) – higher multiplicative factor which is used to inegrate flux, default 1.25
- Returns
r_I – The radius, in pixel units, where the surface brightness profile matches I
- Return type
float or Array
- make_diagnostic_fig()
Function which generates a diagnostic figure to assess fit
- Returns
fig – matplotlib figure object
- Return type
matplotlib figure
- class imcascade.results.MultiResults(lofr)
A Class to analyze and combine multiple ImcascadeResults classes using evidence weighting
- calc_cog(r, num=1000)
- calc_obs_cog(r, num=1000)
- calc_sbp(r, num=1000)
- calc_obs_sbp(r, num=1000)
- calc_flux(cutoff=None, num=1000)
- calc_rX(X, cutoff=None, num=1000)