pycrtools.tasks.shower

CoordinateGrid([obstime, ut1_utc, L, phi])	Coordinate grid for images.
Shower([ws, parfile])	Making all sorts of plots to understand the shower.
Task([ws, parfile])	Base class from which all tasks should be derived.

Module documentation

Module author: Anna Nelles <a.nelles@astro.ru.nl>

class pycrtools.tasks.shower.Shower(ws=None, parfile=None, **kwargs)

Making all sorts of plots to understand the shower.

Usage (minimal variables):

LDF = cr.trun(“Shower”,positions=positions, signals=signals, signals_uncertainties=signals_uncertainties, core=core,direction=direction,core_uncertainties=core_uncertainties,direction_uncertainties=direction_uncertainties, ldf_enable=True)

Task can be run without giving uncertainties. The resulting plot will then also not contain any uncertainties.

FOOTPRINT = cr.trun(“Shower”, positions=positions, signals=signals, timelags = timelags, direction=direction, core = core, footprint_enable=True)

SKYPLOT = cr.trun(“Shower”,all_directions=all_directions,all_stations=all_stations,lora_direction=lora_direction)

Input parameters

all_directions [default value: None ]

List of directions, [NStations x [az,el]]

all_stations [default value: None ]

List of stations corresponding to all_directions

azimuth_in_distance_bins_enable [default value: False ]

Making plots for different distance bins

core [default value: None ]

Core position of the shower given in [X,Y,Z], kartesian

core_uncertainties [default value: None ]

Uncertainties of core position of shower in [eX,eY,Cov], kartesian (assuming flat array Z=const)

direction [default value: None ]

Direction of the shower [AZ, EL], AZ is in degrees eastwards from north and EL is in degrees up from horizon.

direction_uncertainties [default value: None ]

Uncertainties on the direction of the shower in [eAZ,eEL,Cov]

eventid [default value: None ]

Give Event ID to be specified in plot title

footprint_color_lora [default value: “#730909” ]

Color used for LORA plots. If set to ‘time’ uses the arrival time

footprint_colormap [default value: “autumn” ]

colormap to use for LOFAR timing

footprint_enable [default value: False ]

Draw footprint of the shower

footprint_lora_enable [default value: True ]

Draw Information from LORA

footprint_lora_point_scaling [default value: 200 ]

Scaling factor for point size in LORA shower

footprint_marker_lofar [default value: “o” ]

Marker for LOFAR stations in footprint

footprint_marker_lora [default value: “p” ]

Marker for LORA stations in footprint

footprint_movie [default value: False ]

Make individual pictures to make a footprint movie

footprint_number_frames [default value: 30 ]

How many images should the movie be split up into

footprint_point_scaling [default value: 70 ]

Scaling factor for point size in LOFAR plot

footprint_polarization_enable [default value: False ]

Draw footprint with polarization arrows

footprint_remove_global_offset [default value: True ]

Subtract minimum timelag to have 0.0 as minimum

footprint_scale [default value: False ]

Scale footprint to display superterp only.

footprint_scale_box [default value: 200 ]

Box around coordinate center which will be plotted

footprint_scale_to_max [default value: “False” ]

Scale circle size of the footprint to subtract minimum occuring value

footprint_shower_color [default value: “#151B8D” ]

Color in which the shower geometry is drawn

footprint_shower_enable [default value: True ]

Draw shower geometry in footprint

footprint_use_background [default value: True ]

Use LOFAR map as background for footprint

footprint_use_title [default value: True ]

Draw title indicating polarizations and event id (if given)

ldf_color_x [default value: “#B30424” ]

color signals x

ldf_color_y [default value: “#68C8F7” ]

color signals y

ldf_color_z [default value: “#FF8C19” ]

color signals z

ldf_enable [default value: False ]

Draw Lateral Distribution Function, signal vs. distance from shower axis

ldf_integrated_signal [default value: False ]

Change labels to match integrated pulse power

ldf_logplot [default value: True ]

Draw LDF with log axis

ldf_marker_x [default value: “s” ]

marker signals x

ldf_marker_y [default value: “o” ]

marker siganls y

ldf_marker_z [default value: “v” ]

marker siganls z

ldf_remove_outliers [default value: True ]

Do not allow values > 1000000 or < 0.001 for signal strength

ldf_scale [default value: True ]

Scale LDF to region around core only

ldf_time_color [default value: False ]

Use timelags as colors in LDF

ldf_total_signal [default value: False ]

draw only one signalstrength

lora_direction [default value: None ]

direction as reconstructed by LORA in [az,el]

lora_positions [default value: None ]

LORA detector positions, given in [Nx3], [NDetectors x (X,Y,Z)], X,Y,Y kartesian

lora_signals [default value: None ]

Signals in LORA, given in [NDetectors]

lora_timelags [default value: None ]

Timelags of signals in LORA detectors, given in nanoseconds [NDetectors]

plot_prefix [default value: “” ]

Prefix for stored plots

plot_type [default value: “png” ]

Plot type (e.g. png, jpeg, pdf)

polarization_angle [default value: None ]

Polarization angle per station [NAntannas x angle] in radians

positions [default value: None ]

Antennas positions given in [Nx3], [NAntennas x (X,Y,Z)], X,Y,Y kartesian

save_plots [default value: False ]

Saving plost instead of showing them.

save_resolution [default value: None ]

Make high resolution png images of the footprint possible, None is matplotlib default.

signals [default value: None ]

Signals in the antennas given in [Nx3], [NAntennas x (pol_x,pol_y,pol_z)]

signals_uncertainties [default value: None ]

Uncertainties on signal in antennas in [Nx3]

skyplot_of_directions_enable [default value: False ]

Plotting all directions of stations on sky

slicing [default value: None ]

Give boundaries for azimuth bins in [a,b,c,d]

timelags [default value: None ]

Timelags of signals given in seconds [NAntennas x (X,Y,Z)] or [NAntennas]

vxb [default value: False ]

Use vxB, vxvxB and v polarization labels.

Output parameters

plotlist [default value: [] ]

List of output plots.

run()

Run the task.