h5analysis.data_1d.load_1d

h5analysis.data_1d.load_1d(config, file, x_stream, y_stream, *args, norm=False, xoffset=None, xcoffset=None, yoffset=None, ycoffset=None, grid_x=[None, None, None], savgol=None, binsize=None, legend_items={}, twin_y=False, matplotlib_props={})

Internal function to load 1d data

Parameters:

• config (dict) – h5 configuration

• file (string) – file name

• x_stream (string) – key name or alias

• y_stream (string) – key name or alias

• *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)

  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, see keys below

  • linewidth

  • color

  • linestyle

  • marker

  • markersize

  • etc.