Basic plotting with Bokeh.

This example creates a simple plot of a microphone array geometry loaded from an XML file using Acoular and Bokeh.

Note

This example creates a standalone Bokeh document and can be run directly with Python. It does not require a Bokeh server.

First, we import the necessary modules.

from pathlib import Path

import acoular as ac

from bokeh.io import show
from bokeh.models import ColumnDataSource
from bokeh.plotting import figure

Next, we set up the microphone geometry with Acoular’s MicGeom class. For demonstration purposes, we use a 64 channel Vogel’s spiral microphone array geometry stored in an XML file that is part of the Acoular package. To locate the XML directory in the Acoular package, we use the Path object to dynamically construct the path relative to the Acoular package location.

mics = ac.MicGeom(file=Path(ac.__file__).parent / 'xml' / 'tub_vogel64.xml')

The MicGeom class stores the microphone positions in an attribute called pos_total, which is a NumPy array containing the 3D coordinates of each microphone in the array.

Now, let’s create a Bokeh figure to visualize the microphone positions.

figure = figure(
    title='Microphone Geometry',
    tools='hover,zoom_in,zoom_out,reset,lasso_select',
    sizing_mode='stretch_width',
    match_aspect=True,
)

A convenient way to provide data to a Bokeh Plot is to use a ColumnDataSource, which allows us to update the data in the plot easily. Since we create a 2D plot, we only need the x and y coordinates of the microphones.

source = ColumnDataSource(data={'x': mics.pos_total[0], 'y': mics.pos_total[1]})

In addition, we need to decide which glyph to use. Glyphs are the basic building blocks of Bokeh plots and define how the data is visualized. In this case, we use the circle() method to create a Circle that represents the microphones.

figure.circle(
    x='x',
    y='y',
    radius=0.02,
    line_color='black',
    fill_color='#1F77B4',
    fill_alpha=0.4,
    source=source,
)

Finally, we can show the plot using Bokeh’s show() function. This will open a new browser window and display the plot with the microphone positions.

show(figure)  # Show the plot in a new browser window (standalone HTML)