dataset.TimeResSpecPlotter¶
- class dataset.TimeResSpecPlotter(dataset: TimeResSpec, disp_freq_unit='nm')[source]¶
Class which can Plot a
TimeResSpec
using matplotlib.- Parameters:
dataset (TimeResSpec) – The TimeResSpec to work with.
disp_freq_unit ({'nm', 'cm'} (optional)) – The default unit of the plots. To change the unit afterwards, set the attribute directly.
- __init__(dataset: TimeResSpec, disp_freq_unit='nm')[source]¶
Class which can Plot a
TimeResSpec
using matplotlib.- Parameters:
dataset (TimeResSpec) – The TimeResSpec to work with.
disp_freq_unit ({'nm', 'cm'} (optional)) – The default unit of the plots. To change the unit afterwards, set the attribute directly.
Methods
__init__
(dataset[, disp_freq_unit])Class which can Plot a
TimeResSpec
using matplotlib.das
([first_comp, ax, add_legend])Plot a DAS, if available.
edas
([ax, legend])Plot a EDAS, if expontial fit is available.
interactive
()Generates a jupyter widgets UI for exploring a spectra.
lbl_spec
([ax, add_legend])map
([symlog, equal_limits, plot_con, ...])Plot a colormap of the dataset with optional contour lines.
overview
()Plots an overview figure.
plot_disp_result
(result)Visualize the result of a dispersion correction, creates a figure
spec
(*args[, norm, ax, n_average, upsample, ...])Plot spectra at given times.
svd
([n])Plot the SVD-components of the dataset.
trans
(*args[, symlog, norm, ax, freq_unit, ...])Plot the nearest transients for given frequencies.
trans_fit
(*args[, symlog, freq_unit, ...])Plot the nearest transients for given frequencies.
trans_integrals
(*args[, symlog, norm, ax])Plot the transients of integrated region.
univariate_spline
(y)upsample_spec
(y[, kind, factor])Attributes
x