import matplotlib.colors as mpl_colors
import numpy as np
from pylbo.utilities.toolbox import add_pickradius_to_item
from pylbo.visualisation.continua import ContinuaHandler
from pylbo.visualisation.eigenfunctions.eigfunc_handler import EigenfunctionHandler
from pylbo.visualisation.spectra.spectrum_figure import SpectrumFigure
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class SingleSpectrumPlot(SpectrumFigure):
"""
Creates a plot of a single spectrum based on a given dataset.
Parameters
----------
dataset : ~pylbo.data_containers.LegolasDataSet
The dataset used to create the spectrum.
figsize : tuple
Figure size used when creating a window, analogous to matplotlib.
custom_figure : tuple
The custom figure to use in the form (fig, axes).
use_residuals : bool
If `True`, colors the spectrum points based on the residuals.
Attributes
----------
dataset : ~pylbo.data_containers.LegolasDataSet
The dataset passed as parameter
w_real : numpy.ndarray(dtype=float, ndim=1)
Real part of the eigenvalues as a numpy array.
w_imag : numpy.ndarray(dtype=float, ndim=1)
Imaginary part of the eigenvalues as a numpy array.
marker : ~matplotlib.markers
The marker used to draw the points.
markersize : int, float
Size of the marker.
alpha : int, float
Alpha value of the points.
"""
def __init__(self, dataset, figsize, custom_figure, use_residuals, **kwargs):
super().__init__(
custom_figure=custom_figure, figlabel="single-spectrum", figsize=figsize
)
super()._set_plot_properties(kwargs)
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self._use_residuals = use_residuals
(self._nonzero_w_idxs,) = np.where(abs(dataset.eigenvalues) > 1e-12)
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def add_spectrum(self):
"""Adds the spectrum to the plot, makes the points pickable."""
spectrum_points = self.ax.scatter(
self.dataset.eigenvalues[self._nonzero_w_idxs].real * self.x_scaling,
self.dataset.eigenvalues[self._nonzero_w_idxs].imag * self.y_scaling,
marker=self.marker,
c=self._get_colors(),
s=10 * self.markersize,
alpha=self.alpha,
linestyle="None",
norm=mpl_colors.LogNorm() if self._use_residuals else None,
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cmap=self.plot_props.pop("cmap", "jet") if self._use_residuals else None,
**self.plot_props,
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# set dataset associated with this line of points
setattr(spectrum_points, "dataset", self.dataset)
add_pickradius_to_item(item=spectrum_points, pickradius=10)
if self._use_residuals:
self.cbar = self.fig.colorbar(spectrum_points, ax=self.ax, label="Residual")
self.ax.axhline(y=0, linestyle="dotted", color="grey", alpha=0.3)
self.ax.axvline(x=0, linestyle="dotted", color="grey", alpha=0.3)
self.ax.set_xlabel(r"Re($\omega$)")
self.ax.set_ylabel(r"Im($\omega$)")
self.ax.set_title(self.dataset.eq_type)
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def add_continua(self, interactive=True):
"""
Adds the continua to the spectrum.
Parameters
----------
interactive : bool
If `True`, makes the legend pickable.
Returns
-------
c_handler : ~pylbo.continua.ContinuaHandler
The legendhandler used to plot the continua.
"""
if not self.has_valid_continua(self.dataset):
return
if self._c_handler is None:
self._c_handler = ContinuaHandler(interactive=interactive)
for key, color in zip(
self._c_handler.continua_names, self._c_handler.continua_colors
):
continuum = self.dataset.continua[key]
if np.allclose(continuum, 0, atol=1e-12):
continue
# removes duplicates
continuum = np.array(list(set(continuum)), dtype=complex)
item = self.ax.scatter(
continuum.real * self.x_scaling,
continuum.imag * self.y_scaling,
marker=self._c_handler.marker,
linewidth=self._c_handler.markersize,
c=color,
alpha=self._c_handler.alpha_point,
label=key,
)
self._c_handler.add(item)
self._c_handler.legend = self.ax.legend(**self._c_handler.legend_properties)
if interactive:
super().make_legend_interactive(self._c_handler)
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def add_eigenfunctions(self):
"""Adds the eigenfunctions to the plot, sets the eigenfunction handler."""
if self._ef_ax is None:
self._ef_ax = super().add_subplot_axes(self.ax, loc="right")
if self._ef_handler is None:
self._ef_handler = EigenfunctionHandler(self.dataset, self._ef_ax, self.ax)
super().add_eigenfunction_interface(efhandler=self._ef_handler)
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def draw_resonances(self):
"""
In case the (derived) eigenfunctions are added to the plot, the locations
of resonance with the continua will also be drawn.
Does nothing if the (derived) eigenfunctions are not shown.
"""
if self._ef_handler is not None:
self._ef_handler._draw_resonances = True
self._ef_handler.update_plot()
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def _get_colors(self) -> np.ndarray:
"""Returns the colors for the spectrum points."""
if self._use_residuals:
return self.dataset.get_residuals()[self._nonzero_w_idxs]
return self.color