h5analysis.MathData.Object3dHistogramTransform

class h5analysis.MathData.Object3dHistogramTransform

Bases: LoadHistogram3d

Apply transformations to a 3d image stack

Methods

add(config, file, x_stream, y_stream, ...[, ...])	Adds 3d stacks of images with identical scales
background_2d(config, file, x_stream, ...)	Subtracts the defined data from all loaded data
background_3d(config, file, x_stream, ...[, ...])	Subtracts the defined data from all loaded data
baseline(algorithm[, smooth, subtract])	Add baseline from the pybaselines module
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.
load(config, file, x_stream, y_stream, ...)	Load (x,y,z) stream data to histogram
movie(filename[, framerate, aspect, xlim, ...])	Export Stack image as movie
plot([title, xlabel, ylabel, zlabel, ...])	Plot all data assosciated with class instance/object.
subtract(config, file, x_stream, y_stream, ...)	Subtracts 3d stacks of images with identical scales

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

Adds 3d stacks of images with identical scales

Parameters:

• See Load3d function.

• Adds all scans specified in *args.

background_2d(config, file, x_stream, detector, *args, **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

• detector (string) – alias of the MCA detector

• *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

  binsize_x: int

  puts data in bins of specified size in the horizontal direction

  binsize: int

  puts data in bins of specified size in the vertical direction

background_3d(config, file, x_stream, y_stream, z_stream, *args, tempclass=None, **kwargs)

Subtracts the defined data from all loaded data

Parameters:

See LoadHistogram3d function

baseline(algorithm, smooth=None, subtract=True, **kwargs)

Add baseline from the pybaselines module

Parameters:

• algorithm (str) – name of the algorithm

• smooth (tuple) – Sets Savitsky-Golay filter properties: (window length, polynomial order)

• subtract (Boolean) – Whether the baseline is subtracted from the data or replaces the existing data stream

• kwargs (dict) – Key-word arguments for tuning of baseline algorithm

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:

• f (string.IO object) – Motor and Detector Scales. Pandas Data Series. 1) Rewind memory with f.seek(0) 2) Load with pandas.read_csv(f,skiprows=3)

• g (string.IO object) – Actual gridded detector image. 1) Rewind memory with g.seek(0) 2) Load with numpy.genfromtxt(g,skip_header=4)

• raw_data (list) – List of lists with series data, series header, and matrix_data

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

Load (x,y,z) stream data to histogram

Parameters:

• config (dict) – h5 configuration

• file (string) – file name

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

• y_stream (string) – key name or alias of 1d stream

• z_stream (string) – key name or alias of 2d stream

• *args (ints) – scan numbers, 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)

  binsize_x: int

  puts x-data in bins of specified size

  binsize_y: int

  puts y-data in bins of specified size

  binsize_z: int

  puts z-data in bins of specified size (along scale direction)

movie(filename, framerate=20, aspect=1, xlim=None, ylim=None, filetype='gif', **kwargs)

Export Stack image as movie

Parameters:

• filename (string)

• framerate (int) – number of frames per second

• aspect (float) – aspect ratio

• xlim (None, tuple)

• ylim (None, tuple)

• filetype (string) – Use: “gif” or “mp4”

• kwargs – all matplotlib figure key-word arguments

plot(title=None, xlabel=None, ylabel=None, zlabel=None, plot_height=600, plot_width=600, vmin=None, vmax=None, colormap='linear', norm=False, xprec=None, yprec=None, **kwargs)

Plot all data assosciated with class instance/object.

Parameters:

• title (string, optional)

• xlabel (string, optional)

• ylabel (string, optional)

• zlabel (string, optional)

• plot_height (int, optional)

• plot_width (int, optional)

• vmin (float, optional)

• vmax (float, optional)

• colormap (string) – Use: “linear” or “log”

• norm (boolean) – Normalizes to the maximum z-value across all images in the stack

• 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

subtract(config, file, x_stream, y_stream, z_stream, minuend, subtrahend, tempclass=None, **kwargs)

Subtracts 3d stacks of images with identical scales

Parameters:

• See LoadHistogram3d function, but

• minuend (list) – adds all images in list, generates minuend

• subtrahend (list) – adds all images in list, generates subtrahend