km3modules.plot

A collection of plotting functions and modules.

Module Contents

Classes

IntraDOMCalibrationPlotter

The module which can be attached to the pipeline

Functions

plot_dom_parameters(data, detector, filename, label, title)	Creates a plot in the classical monitoring.km3net.de style.
make_dom_map(pmt_directions, values[, nside, d, smoothing])	Create a mollweide projection of a DOM with given PMTs.
ztplot(hits[, filename, title, max_z, figsize, n_dus, ...])	Creates a ztplot like shown in the online monitoring
trim_axes(axes, n)	little helper to massage the axes list to have correct length...
cumulative_run_livetime(qtable[, kind])	Create a figure which plots the cumulative livetime of runs

km3modules.plot.plot_dom_parameters(data, detector, filename, label, title, vmin=0.0, vmax=10.0, cmap='cividis', under='deepskyblue', over='deeppink', underfactor=1.0, overfactor=1.0, missing='lightgray', hide_limits=False)

Creates a plot in the classical monitoring.km3net.de style.

Parameters:

data: dict((du, floor) -> value)

detector: km3pipe.hardware.Detector() instance

filename: filename or filepath

label: str

title: str

underfactor: a scale factor for the points used for underflow values

overfactor: a scale factor for the points used for overflow values

hide_limits: do not show under/overflows in the plot

km3modules.plot.make_dom_map(pmt_directions, values, nside=512, d=0.2, smoothing=0.1)

Create a mollweide projection of a DOM with given PMTs.

The output can be used to call the healpy.mollview function.

class km3modules.plot.IntraDOMCalibrationPlotter(name=None, **parameters)

The module which can be attached to the pipeline

configure()

Configure module, like instance variables etc.

process(blob)

Knead the blob and return it

create_plot(calibration)

save_hdf5(calibration)

km3modules.plot.ztplot(hits, filename=None, title=None, max_z=None, figsize=(16, 8), n_dus=4, ytick_distance=200, max_multiplicity_entries=10, grid_lines=[])

Creates a ztplot like shown in the online monitoring

km3modules.plot.trim_axes(axes, n)

little helper to massage the axes list to have correct length…

km3modules.plot.cumulative_run_livetime(qtable, kind='runs')

Create a figure which plots the cumulative livetime of runs

Parameters:

qtable: pandas.DataFrame

A table which has the run number as index and columns for ‘livetime_s’, ‘timestamp’ and ‘datetime’ (pandas datetime).

kind: str

‘runs’ to plot for each run or ‘timeline’ to plot based on the actual run time.

Returns:

matplotlib.Figure