h5analysis.MathData.Object1dStitch

class h5analysis.MathData.Object1dStitch

Bases: Load1d

Apply stitching on loader objects

Methods

add(config, file, x_stream, y_stream, *args)	Add specified scans for selected streams.
background(config, file, x_stream, y_stream, ...)	Subtracts the defined data from all loaded data
evaluate([average, adjust_scale, filename, ...])	Evaluate the request
export(filename[, split_files])	Export and write data to specified file.
exportWidgetStep()	Helper function for exporter widget.
exporter()	Interactive exporter widget.
get_data()	Make data available in memory as exported to file.
hline(pos, **kwargs)	Draw a horizontal line in the plot.
label(pos_x, pos_y, text, **kwargs)	Draw a text box in the plot.
load(config, file, x_stream, y_stream, ...)	Load one or multiple specific scan(s) for selected streams.
loadObj(obj, line)	Loads data previously specified in a loader
plot([linewidth, title, xlabel, ylabel, ...])	Plot all data assosciated with class instance/object.
plot_legend(pos)	Overwrite default legend position.
save_plot(fname, **kwargs)	Create a matplotlib plot window
show_fluorescence(element, siegbahn_symbol)	Draw a line in the plot for the requested fluorescence line.
stitch(obj, line, scan)	Loader objects to be added
subtract(config, file, x_stream, y_stream, ...)	Subtract specified scans for selected streams.
vline(pos, **kwargs)	Draw a vertical line in the plot.
xlim(lower, upper)	Set x-axis limits applied to data stream.
ylim(lower, upper)	Set y-axis limits applied to data stream.

add(config, file, x_stream, y_stream, *args, legend_item=None, twin_y=False, matplotlib_props={}, tempclass=None, **kwargs)

Add specified scans for selected streams.

Parameters:

• See loader function.

• Adds all scans specified in *args.

background(config, file, x_stream, y_stream, *args, tempclass=None, **kwargs)

Subtracts the defined data from all loaded data

Parameters:

• config (dict) – h5 configuration

• file (string) – file name

• x_stream (string) – h5 key or alias of 1d stream

• y_stream (string) – h5 key or alias of 1d, 2d, or 3d stream

• *args (int) – scans

• **kwargs –

  norm: boolean

  normalizes to [0,1]

  xoffset: list

  fitting offset (x-stream)

  xcoffset: float

  constant offset (x-stream)

  yoffset: list

  fitting offset (y-stream)

  ycoffset: float

  constant offset (y-stream)

  grid_x: list

  grid data evenly with [start,stop,delta]

  savgol: tuple

  (window length, polynomial order, derivative)

  binsize: int

  puts data in bins of specified size

  legend_items: dict

  dict[scan number] = description for legend

evaluate(average=True, adjust_scale=False, filename=None, legend_item=None, twin_y=False, matplotlib_props={})

Evaluate the request

Parameters:

kwargs –

average: Boolean

For overlap, whether the first scan takes precedence (False) or if overlap is averaged (True)

adjust_scale: Boolean

Adjusts the intensity of consecutive scans to match the precessors intensity in the overlap Automatically sets average True

filename: str

Name of the data file

legend_item: str

Text to appear in legend

twin_y: Boolean

Switch to display data on second y axis

matplotlib_props: dict

Dictionary for matplotlib properties

export(filename, split_files=False)

Export and write data to specified file.

Parameters:

• filename (string)

• split_files (Boolean) – Sets whether scans are exported appended to one file (False), or separately (True)

exportWidgetStep()

Helper function for exporter widget.

exporter()

Interactive exporter widget.

get_data()

Make data available in memory as exported to file.

Returns:

• dfT (pandas DataFrame) – All loaded data.

• files (list) – List of all loaded files.

hline(pos, **kwargs)

Draw a horizontal line in the plot.

Parameters:

• pos (float)

• **kwargs (dict, optional) – See bokeh manual for available options.

label(pos_x, pos_y, text, **kwargs)

Draw a text box in the plot.

Parameters:

• pos_x (float)

• pos_y (float)

• text (string)

• **kwargs (dict, optional) – See bokeh manual for available options.

load(config, file, x_stream, y_stream, *args, **kwargs)

Load one or multiple specific scan(s) for selected streams.

Parameters:

• config (dict) – h5 configuration

• file (string) – file name

• x_stream (string) – h5 key or alias of 1d stream

• y_stream (string) – h5 key or alias of 1d, 2d, or 3d stream

• *args (ints) – scans, comma separated

• **kwargs –

  norm: boolean

  normalizes to [0,1]

  xoffset: list

  fitting offset (x-stream)

  xcoffset: float

  constant offset (x-stream)

  yoffset: list

  fitting offset (y-stream)

  ycoffset: float

  constant offset (y-stream)

  grid_x: list

  grid data evenly with [start,stop,delta]

  savgol: tuple

  (window length, polynomial order, derivative)

  binsize: int

  puts data in bins of specified size

  legend_items: dict

  dict[scan number] = description for legend

  twin_y: boolean

  supports a second y-axis on the right-hand side

  matplotlib_props: dict

  dict[scan number] = dict with props that takes keys:

  • linewidth

  • color

  • linestyle

  • marker

  • markersize

  • etc.

loadObj(obj, line)

Loads data previously specified in a loader

Parameters:

• obj (object) – name of the Loader object

• line (int) – Number of the load, add, subtract line (start indexing with 0)

plot(linewidth=4, title=None, xlabel=None, ylabel=None, ylabel_right=None, plot_height=450, plot_width=700, norm=False, waterfall=None, xprec=None, yprec=None, **kwargs)

Plot all data assosciated with class instance/object.

Parameters:

• linewidth (int, optional)

• title (string, optional)

• xlabel (string, optional)

• ylabel (string, optional)

• ylabel_right (string, optional)

• plot_height (int, optional)

• plot_width (int, optional)

• norm (boolean, optional) – Normalized plot output to [0,1]

• waterfall (float) – Normalizes plot output to [0,1] and applies offset specified

• xprec (int, optional) – Specifies the forced floating point X precision of the hover tool

• yprec (int, optional) – Specifies the forced floating point Y precision of the hover tool

• kwargs – all bokeh figure key-word arguments

plot_legend(pos)

Overwrite default legend position.

Parameters:

pos (string) – See bokeh manual for available options.

save_plot(fname, **kwargs)

Create a matplotlib plot window

fname: string

path and file name of the exported file

kwargs:

figsize: tuple

determines size of plot

x_minor_ticks: float

distance between minor ticks on primary axis

x_major_ticks: float

distance between major ticks on primary axis

y_minor_ticks: float

distance between minor ticks on secondary axis

y_major_ticks: float

distance between major ticks on secondary axis

top: Boolean

Display ticks on top of the plot

right: Boolean

Display ticks on the right of the plot

fontsize_axes: string or int

Set the fontsize of the axes ticks

fontsize_labels: string or int

Set fontsize of the axis labels

fontsize_title: string or int

Set fontsize of the title

title_pad: int

Padding between title and the top of the plot

xlabel: string

Label of the primary axis

ylabel: string

Label of the secondary axis

title: string

Title displayed at the top of the plot

xlim: tuple

Limits the visible x-range

ylim: tuple

Limits the visible y-range

legend: Boolean

Show/Hide plot legend

fontsize_legend: int

Fontsize of the legend entries

data_format: string, [pdf,svg,png]

Sets the output data format and matplotlib backend used

show_fluorescence(element, siegbahn_symbol, orientation='v', **kwargs)

Draw a line in the plot for the requested fluorescence line.

Parameters:

• element (string) – IUPAC element abbreviation

• siegbahn_symbol (string) – Siegbahn symbol for requested energy transition

• orientation ([‘v’,’h’]) – Determines if a vertical or horizontal line is drawn

• **kwargs (dict, optional) – See bokeh manual for available options.

stitch(obj, line, scan)

Loader objects to be added

Parameters:

• obj (object) – Loader object

• line (int) – load, add, subtract line of object (indexing with 0)

• scan (int) – number of the scan to be accessed

subtract(config, file, x_stream, y_stream, minuend, subtrahend, legend_item=None, twin_y=False, tempclass=None, matplotlib_props={}, **kwargs)

Subtract specified scans for selected streams.

Parameters:

• See loader function.

• Subtracts two scans. May add scans by specifying list of scans as first/second arg.

vline(pos, **kwargs)

Draw a vertical line in the plot.

Parameters:

• pos (float)

• **kwargs (dict, optional) – See bokeh manual for available options.

xlim(lower, upper)

Set x-axis limits applied to data stream.

Parameters:

• lower (float)

• upper (float)

ylim(lower, upper)

Set y-axis limits applied to data stream.

Parameters:

• lower (float)

• upper (float)