8.2.4. The Ramping Extension

Summary of the main classes of the Ramping extension.

8.2.4.1. The Extension

RampExtension(parent, dashboard)
RampingWorker(ramper[, parent])

class pymodaq.extensions.ramping.ramping.RampExtension(parent, dashboard)

Attributes:

actuator

actuators_name

duration_units

Methods

connect_things()	Connect actions and/or other widgets signal to methods
do_things_after_experiment_set(experiment_name)
do_things_after_ui_setup()
populate_status_bar()
setup_actions()	Method where to create actions to be subclassed.
setup_docks_and_widgets()	Mandatory method to be subclassed to setup the docks layout
setup_menus_and_toolbars([menubar])	Non mandatory method to be subclassed in order to create a menubar
value_changed(param)	Update the dependent settings when one of the settings is changed from the user interface

display_control_modules
get_ramp
q_from_param
update_duration
update_n_steps
update_ramp_settings
update_velocity

connect_things()

Connect actions and/or other widgets signal to methods

setup_actions()

Method where to create actions to be subclassed. Mandatory

See also

ActionManager.add_action

setup_docks_and_widgets()

Mandatory method to be subclassed to setup the docks layout

setup_menus_and_toolbars(menubar=None)

Non mandatory method to be subclassed in order to create a menubar

value_changed(param)

Update the dependent settings when one of the settings is changed from the user interface

Recomputes the number of steps and the duration or velocity of the ramp, and updates the units and the lists of modules when the ramping actuator is changed.

Parameters:

param ((Parameter) the parameter whose value just changed)

class pymodaq.extensions.ramping.ramping.RampingWorker(ramper, parent=None)

Attributes:

actuator

actuators

app

detectors

h5_browser

histo_settings

processor_worker

ramp

status_manager

Methods

connect_modules
disconnect_modules
go_to_ini_ramp
ini_things
run_plot_timer
run_ramp
send_data_to_saver
start_modules
stop_modules
update_histogramer
update_histogramer_settings
update_ramp

8.2.4.2. Ramp and data saving

class pymodaq.extensions.ramping.utilities.ramp_generator.RampGenerator(start, end, duration=Quantity(5.0, 'second'))

Methods

__call__(elapsed_time)

update

class pymodaq.extensions.ramping.utilities.module_saver.RampSaver(*args, **kwargs)

Implementation of the ModuleSaver class dedicated to Ramping module

Parameters:

• h5saver

• module

8.2.4.3. Histogram

H5Histogramming(h5_manager, viewer[, parent])
HistogramProcessor(h5saver[, parent])
InfoForHistogram(node_path, xaxis_name, ...)

class pymodaq.extensions.ramping.utilities.histograming.H5Histogramming(h5_manager, viewer, parent=None)

Attributes:

data_loader

histogram_processor

live

True while ramping: the histogram is computed by the ramping worker, not from here

Methods

check_min_axis_size()	Look at the arrays under current node for the minimal navigation size
get_selection(modules_type, available)	Get the itemselect value of the detectors or actuators to plot, keeping the current selection
update_settings_from_file(file_path)	Offline mode.
value_changed(param)

get_actuator_dwa
get_actuators
get_data
get_detector_dte
get_detectors
get_main_nodes
get_set_bounds
update_control_modules
update_histogramer

check_min_axis_size()

Look at the arrays under current node for the minimal navigation size

Return type:

int | None

get_selection(modules_type, available)

Get the itemselect value of the detectors or actuators to plot, keeping the current selection

Parameters:

• modules_type (str) – either ‘detectors’ or ‘actuators’

• available (list[str]) – the names of the modules having data

Return type:

dict

Returns:

• dict (all_items are the available modules, selected the ones already selected and still available, plus the)

• ones that were not listed before (all of them the first time)

update_settings_from_file(file_path)

Offline mode. Means ramping is not in progress and the h5file was closed and has been opened for here

property live: bool

the histogram is computed by the ramping worker, not from here

Type:

True while ramping

class pymodaq.extensions.ramping.utilities.histograming.HistogramProcessor(h5saver, parent=None)

Methods

average_data_over_indexes(data, indexes[, ...])	Return the average of data over the indexes
do_process_data(info)

compute_histogram
nbins_signal

static average_data_over_indexes(data, indexes, index_max=None)

Return the average of data over the indexes

See: https://stackoverflow.com/questions/71329884/python-numpy-get-average-of-array-based-on-index

Return type:

ndarray[float]

class pymodaq.extensions.ramping.utilities.histograming.InfoForHistogram(node_path, xaxis_name, start, stop, other_names=<factory>, bins='auto')