hyperspy._signals.complex_signal2d module

class hyperspy._signals.complex_signal2d.Complex2Dmixin(*args, **kw)

Bases: object

BaseSignal subclass for complex 2-dimensional data.

add_phase_ramp(ramp_x, ramp_y, offset=0)

Add a linear phase ramp to the wave.

Parameters:
  • ramp_x (float) – Slope of the ramp in x-direction.
  • ramp_y (float) – Slope of the ramp in y-direction.
  • offset (float, optional) – Offset of the ramp at the fulcrum.

Notes

The fulcrum of the linear ramp is at the origin and the slopes are given in units of the axis with the according scale taken into account. Both are available via the axes_manager of the signal.

plot(power_spectrum=False, norm='auto', fft_shift=False, colorbar=True, scalebar=True, scalebar_color='white', axes_ticks=None, saturated_pixels=0, vmin=None, vmax=None, no_nans=False, centre_colormap='auto', **kwargs)

Plot the signal at the current coordinates.

For multidimensional datasets an optional figure, the “navigator”, with a cursor to navigate that data is raised. In any case it is possible to navigate the data using the sliders. Currently only signals with signal_dimension equal to 0, 1 and 2 can be plotted.

Parameters:
  • navigator ({"auto", None, "slider", "spectrum", Signal}) – If “auto”, if navigation_dimension > 0, a navigator is provided to explore the data. If navigation_dimension is 1 and the signal is an image the navigator is a spectrum obtained by integrating over the signal axes (the image). If navigation_dimension is 1 and the signal is a spectrum the navigator is an image obtained by stacking horizontally all the spectra in the dataset. If navigation_dimension is > 1, the navigator is an image obtained by integrating the data over the signal axes. Additionaly, if navigation_dimension > 2 a window with one slider per axis is raised to navigate the data. For example, if the dataset consists of 3 navigation axes X, Y, Z and one signal axis, E, the default navigator will be an image obtained by integrating the data over E at the current Z index and a window with sliders for the X, Y and Z axes will be raised. Notice that changing the Z-axis index changes the navigator in this case. If “slider” and the navigation dimension > 0 a window with one slider per axis is raised to navigate the data. If “spectrum” and navigation_dimension > 0 the navigator is always a spectrum obtained by integrating the data over all other axes. If None, no navigator will be provided. Alternatively a Signal instance can be provided. The signal dimension must be 1 (for a spectrum navigator) or 2 (for a image navigator) and navigation_shape must be 0 (for a static navigator) or navigation_shape + signal_shape must be equal to the navigator_shape of the current object (for a dynamic navigator). If the signal dtype is RGB or RGBA this parameters has no effect and is always “slider”.
  • axes_manager ({None, axes_manager}) – If None axes_manager is used.
  • plot_markers (bool, default True) – Plot markers added using s.add_marker(marker, permanent=True). Note, a large number of markers might lead to very slow plotting.
  • norm ({‘auto’, ‘linear’, ‘log’, mpl Normalize instance or subclass},) – default is ‘auto’. Plot the intensity scale on a linear or logarithmic scale. If ‘auto’, plot the intensity on a linear scale except when power_spectrum is True, which can be used only for compatible signal. For Signal2D, a matplotlib Normalize subclass or instance can be provided.
  • colorbar (bool, optional) – If true, a colorbar is plotted for non-RGB images.
  • scalebar (bool, optional) – If True and the units and scale of the x and y axes are the same a scale bar is plotted.
  • scalebar_color (str, optional) – A valid MPL color string; will be used as the scalebar color.
  • axes_ticks ({None, bool}, optional) – If True, plot the axes ticks. If None axes_ticks are only plotted when the scale bar is not plotted. If False the axes ticks are never plotted.
  • saturated_pixels (scalar) – The percentage of pixels that are left out of the bounds. For example, the low and high bounds of a value of 1 are the 0.5% and 99.5% percentiles. It must be in the [0, 100] range.
  • vmax (vmin,) – vmin and vmax are used to normalize luminance data.
  • no_nans (bool, optional) – If True, set nans to zero for plotting.
  • centre_colormap ({"auto", True, False}) – If True the centre of the color scheme is set to zero. This is specially useful when using diverging color schemes. If “auto” (default), diverging color schemes are automatically centred.
  • min_aspect (float) – Set the minimum aspect ratio of the image and the figure. To keep the image in the aspect limit the pixels are made rectangular.
  • power_spectrum (bool, default is False.) – If True, plot the power spectrum instead of the actual signal, if False, plot the real and imaginary parts of the complex signal.
  • representation ({'cartesian' or 'polar'}) – Determines if the real and imaginary part of the complex data is plotted (‘cartesian’, default), or if the amplitude and phase should be used (‘polar’).
  • same_axes (bool, default True) – If True (default) plot the real and imaginary parts (or amplitude and phase) in the same figure if the signal is one-dimensional.
  • fft_shift (bool, default False) – If True, shift the zero-frequency component. See numpy.fft.fftshift for more details.
  • optional (**kwargs,) – Additional key word arguments passed to matplotlib.imshow()
class hyperspy._signals.complex_signal2d.ComplexSignal2D(*args, **kw)

Bases: hyperspy._signals.complex_signal2d.Complex2Dmixin, hyperspy._signals.complex_signal.ComplexSignal, hyperspy._signals.common_signal2d.CommonSignal2D

BaseSignal subclass for complex 2-dimensional data.

class hyperspy._signals.complex_signal2d.LazyComplexSignal2D(*args, **kw)

Bases: hyperspy._signals.complex_signal2d.ComplexSignal2D, hyperspy._signals.complex_signal.LazyComplexSignal

BaseSignal subclass for lazy complex 2-dimensional data.