burstfit.utils.plotter
plot_1d_fit
def plot_1d_fit(xdata, ydata, function, popt, xlabel=None, ylabel=None, title=None, param_names=[], show=True, save=False, outname="1d_fit_res")
Plot the results of 1D fits
Arguments:
xdata
- x value arrayydata
- original data valuesfunction
- function used for fittingpopt
- fit parameters of the functionxlabel
- label of x axisylabel
- label of y axistitle
- title of the plotparam_names
- names of the parameters
Returns:
plot_2d_fit
def plot_2d_fit(sgram, function, popt, tsamp, title=None, show=True, save=False, outname="2d_fit_res", outdir=None)
Plot the result of spectrogram fit
Arguments:
sgram
- input 2D array of spectrogramfunction
- spectrogram function used for fittingpopt
- fit parameterstsamp
- sampling time (s)title
- title of the plot
Returns:
plot_fit_results
def plot_fit_results(sgram, function, popt, tsamp, fstart, foff, mask=None, outsize=None, title=None, show=True, save=False, outname="2d_fit_res", outdir=None, vmin=None, vmax=None)
Arguments:
sgram
- Original spectrogram datafunction
- spectrogram function used for modelingpopt
- parameters for functiontsamp
- sampling time (s)fstart
- start frequency (MHz)foff
- channel bandwidth (MHz)mask
- channel mask arrayoutsize
- resize the 2D plotstitle
- title of the plotshow
- to show the plotsave
- to save the plotoutname
- output name of png fileoutdir
- output directory for the plotvmin
- minimum range of colormapvmax
- maximum range of colormap
Returns:
plot_me
def plot_me(datar, xlabel=None, ylabel=None, title=None)
Generic function to plot 1D or 2D array. Requires SciencePlots.
Arguments:
datar
- data to plotxlabel
- label of x axisylabel
- label of y axistitle
- title of the plot
Returns:
plot_mcmc_results
def plot_mcmc_results(samples, name, param_starts, labels, save=False)
Save corner plot of MCMC results
Arguments:
samples
- MCMC samples to plotname
- output nameparam_starts
- mark the initial parameter guesslabels
- labels for axessave
- to save the corner plot
Returns:
autocorr_plot
def autocorr_plot(n, y, name, save)
Make the autocorrelation plot to visualize convergence of MCMC.
Arguments:
n
- iterationsy
- autocorrelationsname
- outname of plotsave
- to save the plot
Returns: