pysdkit.plot#

Created on Sat Mar 4 21:31:05 2024 @author: Whenxuan Wang @email: wwhenxuan@gmail.com Some auxiliary function modules for data visualization in the PySDKit library

`pysdkit.plot._plot_imfs`	Created on Sat Mar 4 11:59:21 2024 @author: Whenxuan Wang @email: wwhenxuan@gmail.com
`pysdkit.plot._fourier_spectra`	Created on 2024/6/2 21:12 @author: Whenxuan Wang @email: wwhenxuan@gmail.com
`pysdkit.plot._plot_images`	Created on 2025/02/02 16:47:10 @author: Whenxuan Wang @email: wwhenxuan@gmail.com
`pysdkit.plot._plot_signal`	Created on 2025/02/11 21:42:45 @author: Whenxuan Wang @email: wwhenxuan@gmail.com

plot.plot_imfs#

Created on Sat Mar 4 11:59:21 2024 @author: Whenxuan Wang @email: wwhenxuan@gmail.com

可视化图像的函数需要再专门去写几个就不同可视化信号的放在一起了

对分解后的频谱进行可视化

Visualizes the numpy array of intrinsic mode functions derived from the decomposition of a signal. Can be used as a generic interface for plotting.

You can choose to visualize on a 2D plane or in 3D space.

The 2D plane visualization is more intuitive, while the 3D visualization can better reflect the size relationship between the decomposed modes.

Parameters:

signal – The input original signal
IMFs – The intrinsic mode functions obtained after signal decomposition
max_imfs – The number of decomposition modes to be plotted
view – The view of the figure, choice [“2d”, “3d”]
colors – List of color strings for plotting
save_figure – Whether to save the figure as an image
return_figure – Whether to return the figure object
dpi – The resolution of the saved image
spine_width – The width of the visible axes spines
labelpad – Controls the filling distance of the y-axis coordinate
save_name – The name of the saved image file

Returns:

The figure object for the plot

plot.fourier_spectra#

Created on 2024/6/2 21:12 @author: Whenxuan Wang @email: wwhenxuan@gmail.com

pysdkit.plot._fourier_spectra.plot_IMFs_amplitude_spectra(IMFs: ndarray, norm: bool | None = True, smooth: str | None = None, colors: List | None = None, figsize: Tuple | None = None, save_figure: bool = False, return_figure: bool = False, dpi: int = 500, fontsize: float = 14, save_name: str | None = None) → figure[source]#

Plot amplitude spectra of Intrinsic Mode Functions (IMFs) obtained from signal decomposition

Parameters:

IMFs – Input Intrinsic Mode Functions
norm – Whether to normalize the Fourier transform results
smooth – Whether to smooth the amplitude spectra, and the method to use
colors – List of colors to use for plotting
figsize – Size of the figure (default is (12, 5))
save_figure – Whether to save the plotted figure
return_figure – Whether to return the figure object
dpi – Resolution of the created figure (default is 500)
fontsize – Font size for the labels and title (default is 14)
save_name – Name to save the figure

Returns:

Figure object (if return_figure is True)

plot.plot_images#

Created on 2025/02/02 16:47:10 @author: Whenxuan Wang @email: wwhenxuan@gmail.com

pysdkit.plot._plot_images.plot_grayscale_image(img: ndarray, figsize: Tuple | None = (5, 5), dpi: int | None = 100, cmap: str | None = 'coolwarm') → Tuple[Figure, Axes][source]#

Visualize a 2D grayscale image.

Parameters:

img – The input 2D ndarray matrix from numpy.
figsize – The size of the figure.
dpi – The resolution used, default is 100.
cmap – The colormap used.

Returns:

Figure and Axes from matplotlib.

pysdkit.plot._plot_images.plot_grayscale_spectrum(img: ndarray, figsize: Tuple | None = (5, 5), dpi: int | None = 100, cmap: str | None = 'coolwarm') → Tuple[Figure, Axes][source]#

Plot the spectrum distribution of a 2D grayscale image.

Parameters:

img – The input 2D ndarray matrix from numpy.
figsize – The size of the figure.
dpi – The resolution used, default is 100.
cmap – The colormap used.

Returns:

Figure and Axes from matplotlib.

Visualize univariate and multivariate 2D images. It is a packaged general interface. The input data img is a univariate image [height, width] or a multivariate image [n_vars, height, width] The spectrum variable controls whether to visualize the time domain The colorbar variable controls whether to add a color bar

Parameters:

img – The input images,which shape are [height, width]或[n_vars, height, width]
spectrum – bool, Whether to draw the spectrum image of fast Fourier transform at the same time
dpi – The resolution at which the image is drawn
cmap – The colormap to use, defaults is colorwarm
colorbar – bool, whether to add a color bar to the drawn image
save_figure – Whether to save the figure as an image
save_name – The name of the saved image file
return_figure – Whether to return the figure object

Returns:

The plotting Figure from matplotlib

plot.plot_signal#

Created on 2025/02/11 21:42:45 @author: Whenxuan Wang @email: wwhenxuan@gmail.com

pysdkit.plot._plot_signal.plot_signal(time: array, signal: array, spectrum: bool | None = False, color: str = 'royalblue', save: bool = False, dpi: int = 128, fontsize: int = 12) → figure[source]#

Plot and optionally save an amplitude modulated (AM) signal with time on the x-axis and amplitude on the y-axis.

Parameters:

time – Array of time points corresponding to the signal.
signal – Array containing the signal data to be plotted.
spectrum – bool, Whether to draw the spectrum signal of fast Fourier transform at the same time
color – Color of the plot line.
save – Boolean flag to indicate whether the plot should be saved to a file.
dpi – Dots per inch (resolution) of the figure, if saved.
fontsize – Font size of the axis labels.

Returns:

The figure object containing the plot.