srsinst.rga.plots Package

srsinst.rga.plots.analogscanplot module

class srsinst.rga.plots.analogscanplot.AnalogScanPlot(parent: Task, ax: Axes, scan: Scans, plot_name='', save_to_file=True)

Bases: BaseScanPlot

Class to manage an analog scan plot with data generated from the parent task

Parameters:

  • parent (Task) – It uses resources from the parent task

  • scan (Scans) – an instance of Scans class in an instance of RGA100 class

  • plot_name (str) – name of the plot used as title of the plot and name of the dict for scan data saving

  • save_to_file (bool) – to create a table in the data file

reset()
scan_data_available_callback(index)
scan_finished_callback()
cleanup()

callback functions should be disconnected when task is finished

get_plot_info()
round_float(number)
save_scan_data(data_list)
set_conversion_factor(factor=0.1, unit='fA')
set_x_axis(x_axis)

srsinst.rga.plots.histogramscanplot module

class srsinst.rga.plots.histogramscanplot.HistogramScanPlot(parent: Task, ax: Axes, scan: Scans, plot_name='', save_to_file=True)

Bases: BaseScanPlot

Class to manage an histogram scan bar graph with data generated from the parent task

Parameters:

  • parent (Task) – It uses resources from the parent task

  • scan (Scans) – an instance of Scans class in an instance of RGA100 class

  • plot_name (str) – name of the plot used as title of the plot and name of the dict for scan data saving

  • save_to_file (bool) – to create a table in the data file

reset()
update_callback(index)
scan_started_callback()
scan_finished_callback()
cleanup()

callback functions should be disconnected when task is finished

get_plot_info()
round_float(number)
save_scan_data(data_list)
set_conversion_factor(factor=0.1, unit='fA')
set_x_axis(x_axis)

srsinst.rga.plots.timeplot module

class srsinst.rga.plots.timeplot.TimePlot(parent: Task, ax: Axes, plot_name='', data_names=('Y',), save_to_file=True, use_datetime=True, plot_options=None)

Bases: object

Class to manage a plot for multiple time-series data generated in the parent task

Parameters:

  • parent (Task) – It uses resources from the parent task

  • ax (Axes) – Matplotlib Axes on which it makes a plot

  • data_names (tuple or list) – list of names of time series data. It specifies the number of data sets, too.

  • save_to_file (bool) – Allow To create a table in the data file

  • use_datetime (bool) – To use datetime format for x axis, otherwise it uses the elapsed time in seconds

  • plot_options (list of dict) – each element of the list with the matching element in data_names will be passed to Matplotlib Axes.plot as **kwarg, if exists.

on_xlim_changed(event_ax)
on_pick(event)

Toggle a line from the line corresponding in the legend

https://matplotlib.org/stable/gallery/event_handling/legend_picking.html

get_buffer_size()
set_buffer_size(size=10000000)
set_conversion_factor(factor=0.1, unit='fA')
add_data(data_list=(0,), update_figure=False)
save_data(timestamp, data_list)
round_float(number)
get_plot_info()
update_plot()
cleanup()

srsinst.rga.plots.basescanplot module

class srsinst.rga.plots.basescanplot.BaseScanPlot(parent: Task, ax: Axes, plot_name='', save_to_file=False)

Bases: object

Base class for scan plots

set_conversion_factor(factor=0.1, unit='fA')
set_x_axis(x_axis)
save_scan_data(data_list)
round_float(number)
get_plot_info()
cleanup()

srsinst.rga.plots.analysis module

srsinst.rga.plots.analysis.calculate_baseline(y, ratio=1e-06, lam=10000.0, niter=20, full_output=False)

Calculate baseline of a spectrum based on Asymmetrically reweighted penalized least square (ARPLS)

Original paper: https://pubs.rsc.org/en/content/articlelanding/2015/AN/C4AN01061B#!divAbstract

Python implementation: https://stackoverflow.com/questions/29156532/python-baseline-correction-library

Parameters:

  • y (Numpy array) – Intensity array

  • ratio (float) – improvement ratio to reach before stopping iteration

  • lam (float) – fit parameter lambda

  • niter (int) – maximum iteration

  • full_output (bool, optional) – generate detailed output

Returns:

  • Numpy array – baseline array, if full_output == False

  • tuple – (baseline array, baseline-subtracted intensity array, termination information in dict format), if full_output == True

srsinst.rga.plots.analysis.get_peak_from_analog_scan(x, y, mass, fit=False)

Calculate the intensity of a peak in an analog scan spectrum

Parameters:

  • x (Numpy array) – mass axis values

  • y (Numpy array) – intensity array

  • mass (float) – peak position within the range of x

  • fit (bool, optional) – The default is False, if False, return the maximum value around mass. If True , it fits the data around x with a parabola, and calculate the maximum of the parabola.

Returns:

peak intensity

Return type:

float