Companion Python library for plotting configurations and filters for CamillaDSP. It is also used by the web interface.
Download the library, either by git clone or by downloading a zip file of the code. Then unpack the files, go to the folder containing the setup.py file and run:
pip install .Note that on some systems the command is pip3 instead of pip.
This library requires Python 3.6 or newer. For plotting configurations with the commandline tool plotcamillaconf, it also requires numpy and matplotlib. These are not required for using only with the web interface.
These are the names of the packages needed:
| Distribution | python | numpy (optional) | matplotlib (optional) |
|---|---|---|---|
| Fedora | python3 | python3-numpy | python3-matplotlib |
| Debian/Raspbian | python3 | python3-numpy | python3-matplotlib |
| Arch | python | python-numpy | python-matplotlib |
| pip | - | numpy | matplotlib |
| Anaconda | - | numpy | matplotlib |
Most linux distributions have Python 3.6 or newer installed by default. Use the normal package manager to install the packages.
Use Anaconda: https://www.anaconda.com/products/individual. Then use Anaconda Navigator to install the dependencies.
On macOS use either Anaconda or Homebrew. The Anaconda procedure is the same as for Windows.
For Homebrew, install Python with brew install python, after which you can install the needed packages with pip, pip3 install numpy etc.
This library provides the console command plotcamillaconf. Once the library is installed, togehter with the optional dependencies numpy and matplotlib, the command should be available in your terminal.
To use it type:
plotcamillaconf /path/to/some/config.ymlThis will plot the frequency response of all the defined filters, and show a block diagram of the pipeline.
To plot the frequency response of a filter, use the function plot_filter. This is mostly meant for internal use by the plotcamillaconf command.
plot_filter(filterconf, name=None, samplerate=44100, npoints=1000, toimage=False)This will plot using PyPlot. The filter configuration filterconf must be provided. The samplerate defaults to 44100 if not given. The filter name is used for labels. The number of points in the plot is set with npoints. If toimage is set to True, then it will instead return the plot as an svg image.
It's also possible to plot the combined frequency response of a Filter step in the pipeline.
plot_filterstep(conf, pipelineindex, name="filterstep", npoints=1000, toimage=False)This command takes a full configuration as conf. It will then plot the step with index pipelineindex in the pipeline where 0 is the first step. The name is used for the plot title. The number of points in the plot is set with npoints. If toimage is set to True, then it will instead return the plot as an svg image.
To plot a block diagram of the pipeline, use the function plot_pipeline. This is mostly meant for internal use by the plotcamillaconf command.
plot_pipeline(conf, toimage=False)This takes a full CamillaDSP configuration, conf. It will then plot the pipeline using PyPlot. If toimage is set to True, then it will instead return the plot as an svg image.
To evaluate the frequency response of a filter, use the function eval_filter. This is mostly meant for internal use by the plotcamillaconf command as well as the web gui.
eval_filter(filterconf, name=None, samplerate=44100, npoints=1000)This will evaluate the filter and return the result as a dictionary. The filter configuration filterconf must be provided. The samplerate defaults to 44100 if not given. The filter name is used for labels. The number of points in the plot is set with npoints. The contents of the returned dictionary depends on the filter type. A Biquad returns name, samplerate, f, magnitude and phase. A Conv filter additionally return the impulse response in time and impulse.
It's also possible to evaluate the combined frequency response of a Filter step in the pipeline.
eval_filterstep(conf, pipelineindex, name="filterstep", npoints=1000)This command takes a full configuration as conf. It will evaluate the step with index pipelineindex in the pipeline where 0 is the first step. As for eval_filter, the result is returned as a dictionary with the same fields as for a Biquad.