Alignment Plotting

systematic generation of alignment-related plots

hps_align.plot.default(p: Plotter)
hps_align.plot.generate_legend_names(input_files)

Generate legend names from input file names

hps_align.plot.plot(plots: ~typing.List[~hps_align.plot.PlotOpt] = <typer.models.ArgumentInfo object>, plot_list: str = <typer.models.OptionInfo object>, input_files: ~typing.List[str] = <typer.models.OptionInfo object>, legend: ~typing.List[str] = <typer.models.OptionInfo object>, out_dir: str = <typer.models.OptionInfo object>, html: bool = <typer.models.OptionInfo object>, is2016: bool = <typer.models.OptionInfo object>, ext: str = <typer.models.OptionInfo object>, config: str = <typer.models.OptionInfo object>)

create comparison plots across different detector iterations of alignment-related variables

Plotters

The hps_align.plot submodule is broken up into various “plotters” so that users can choose which plots to generate from the input files.

hps_align.plot.vertex.multi_vtx(p)

plot multi-vertex distributions

input ROOT files have to contain the ‘/MultiEventVtx/’ directory

hps_align.plot.derivatives.all(p: Plotter)

Plot all the derivatives in the plot listing

hps_align.plot.derivatives.single_derivative(p: Plotter, name: str)

Make a single derivative plot

This is here instead of in the Plotter class since it is so specialized. We assume that the ‘gbl_derivatives’ directory exists in all the input ROOT files.

Parameters:

  • p (Plotter) – plotter instance with package of input files to compare

  • name (str) – name of derivative to plot

hps_align.plot.kinks.Lambda(p: Plotter)

Create lambda-kink summary plots

Unfortunately, we have to break name convention since ‘lambda’ is a reserved word in Python.

hps_align.plot.kinks.phi(p: Plotter)

Create and save the phi kink summary plots

hps_align.plot.residual.one_dim(p: Plotter)

Plot the 1D residuals for the sensors in the plot listing

hps_align.plot.residual.single_residual_plot(p: Plotter, histo_name, title='')

Plot a single 1D residual plot for the input sensor

hps_align.plot.residual.summary(p: Plotter)

! Plot the summary of residuals for all sensors

@param out_dir_ext extension of the output directory, has to end in /

hps_align.plot.residual.vs_u(p: Plotter)

Plot the residuals for the sensors agains u

hps_align.plot.residual.vs_v(p: Plotter)

Plot the residuals for the sensors agains u

hps_align.plot.tracks.eop(p: Plotter)

EoP plots require the EoP directory in the ROOT files

hps_align.plot.tracks.fee(p: Plotter)
hps_align.plot.tracks.p_vs_phi(p: Plotter)
hps_align.plot.tracks.profiles(p: Plotter)
hps_align.plot.tracks.tracks(p: Plotter)
hps_align.plot.tanL.tanL(p: Plotter)
hps_align.plot.tanL.z0_vs_tanL_fit(p: Plotter, name: str)

! Plot z0 vs tanL and fit it

root file has to contain directory “trk_params/”

@param name name of the histogram

Advanced Usage

The main way we achieve this auto-registration of the different plotters is by using a “decorator”. This decorator is a class member of the object that is passed to each plotting function and is used to uniformly interact with the input files.

Plotter object which is passed into plotting functions

class hps_align.plot._plotter.Plotter(legend_names=[], infile_names=[], outdir='', do_HTML=False, oFext='.png', is2016=False, plot_list_file=None)

Bases: object

class for plotting alignment results

This class contains the basic functionality and setup for plotting alignment results. It is intended to be inherited by other classes that implement specific plotting.

The class is initialized with the following arguments: - input_file_list: list of file names containing the alignment results - outdir: directory where the plots will be saved - legend_names: list of names for the legend entries - do_html: if True, an index page with links to the plots will be created - oFext: extension of the output files

This class holds the open TFiles and is then passed to future plotting functions in order to provide access to the histograms within the files being held.

Parameters:

  • legend_names (List[str]) – list of legend names aligned with the input files

  • infile_names (List[str]) – list of ROOT files to open

  • outdir (str) – path to output directory to dump plots

  • do_HTML (bool) – whether to write html file or not

  • oFext (str) – extension to use for writing plots (‘.png’ or ‘.pdf’)

  • indir (str) – directory inside ROOT files to access plots from

__registry__

Dictionary of registered plotters

Type:

dict

colors

list of ROOT colors to iterate through as we plot

Type:

List[int]

markers

list of ROOT markers to iterate through as we plot in parallel with colors

Type:

List[int]

binLabels

list of bin labels for kink and ures summary plots

Type:

List[str]

input_files

list of ROOT files we are going to pull histograms from

Type:

List[TFile]

do_legend(histos, legend_names, location=1, plot_properties=[], leg_location=[])

Create legend

Parameters:

  • histos (List[TH1]) – of histograms to do legend for

  • legend_names (List[str]) – names for the histograms in the legend

  • location (int) – location short ID

  • plot_properties (List[str]) – list of properties to include along with legend entries

  • leg_location (List[float]) – more precise legend location, overwriting predefined one

Returns:

created TLegend ready to Draw at your convenience

Return type:

TLegend

get(hist_name, indir='')

Get a histogram from each ROOT file

Parameters:

  • hist_name (str) – name of histogram to get

  • indir (str, optional) – optional ROOT directory histogram is contained in

Returns:

list of histograms, one from each file

Return type:

List[TH1]

Raises:

KeyError – if hist_name is not found in any of the files

make_1D_plots(histolist, out_name='output', xtitle='', ytitle='', yrange=[], logy=False, RebinFactor=0)

! Make 1D plots

@param histolist List of histograms to plot @param out_name Name of the plot @param xtitle X-axis title @param ytitle Y-axis title @param yrange Y-axis range @param logy Set the Y-axis to log scale @param RebinFactor Rebin factor

make_1D_plots_with_fit(histopath, xtitle='', ytitle='', fit=True, scale_histos=False)

Plot the histograms with an iterative gaussian fit

Parameters:

  • histopath (str) – path to the histogram in the ROOT files

  • fit (bool or dict, optional) – do the iterative gaussing fit and plot the result if dictionary, use those settings as keyword arguments to make_fit

  • xtitle (str) – title of x-axis

  • ytitle (str) – title of y-axis

  • scale_histos (bool) – scale the histograms to unity

See also

alignment_utils.make_fit

for how fitting of histograms is done

make_2D_plots(histolist, out_name='output', xtitle='', ytitle='', ztitle='', zrange=[])

! Make combined 2D scatter plots from histograms in histolist

@param histolist list of histograms to plot @param out_name name of output file @param xtitle x axis title @param ytitle y axis title @param ztitle z axis title @param zrange z axis range

plot_2D_colormesh(name, indir='res/', xtitle=None, ytitle=None, ztitle=None, logz=True)

plot a 2D colormesh for _each_ histogram in the list _separately_

Parameters:

  • name (str) – name of histogram to plot for each loaded file

  • indir (str, optional) – directory in which histogram resides in ROOT file

  • out_name (str, optional) – out name prefix, it is a prefix since we will be printing multiplt plots

  • xtitle (str, optional) – title of x axis

  • ytitle (str, optional) – title of y axis

  • ztitle (str, optional) – title of z axis

  • logz (bool, optional) – whether to have color scale be logarithmic or not (default yes)

plot_list(name=None)

Get the plot listing

If a name is not provided, the full plot listing is returned. If a name is provided, only that category of plots is returned and if that category of plots is separated by year, we only return the group of plots from that category for the configured year.

Parameter

namestr, optional

optional name of plot category to pull

returns:

plot listing

rtype:

dict

plot_profileY(name, indir='res/', xtitle='hit position [mm]', ytitle='<ures> [mm]', rangeX=[], rangeY=[], do_fit=False, fitrange=[-200000.0, 200000.0], fit='[0]*x + [1]', num_bins=1, rebin=1, do_sigma_profile=False)

! Plot y profile of distribution

@param name name of the histogram @param xtitle x axis title @param ytitle y axis title @param rangeX x axis range @param rangeY y axis range @param do_fit if true, fit is performed @param fitrange range for fit @param fit fit function @param num_bins number of bins for profile @param rebin rebinning factor @param do_sigma_profile if true, sigma profile plots are added

set_histo_style(histo, ihisto, marker_size=4, line_width=5, label_size=0.05)

Set histo properties.

Parameters:

  • histo (r.TH1) – histogram to style

  • ihisto (int) – index of histogram in list of histograms, sets the style

  • marker_size (int) – size of marker in ROOT units

  • line_width (int) – with of line in ROOT units

  • label_size (float) – size of label in ROOT units

user()

decorator for registering plotters

This is the wackiest python thing in this package and is used to allow the CLI to have a list of all plotters in submodules. In order for this to function, a plotting function needs…

  1. to be in a module imported in __init__.py. This is required so that the function is imported when the parent module is imported

  2. to be decorated by the ‘plotter’ decorator below.

Examples

Register a plotter:

@Plotter.user
def my_hist_plotter(d) :
    # d will be a Plotter object