### Install QDax Dependencies

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/examples.md

Install QDax for examples demonstrating integration with Quality Diversity algorithms in JAX.

```bash
pip install qdax
```

--------------------------------

### Complete Plugin Processing Example

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/plugin_processor.md

A comprehensive example demonstrating engine initialization, synth and reverb processor creation, state saving, automation setup, MIDI note addition, graph loading, rendering, audio saving, and MIDI saving.

```python
import dawdreamer as daw
import numpy as np
from scipy.io import wavfile

SAMPLE_RATE = 44100
BUFFER_SIZE = 128
PPQN = 960
SYNTH_PLUGIN = "/path/to/synth.dll"
REVERB_PLUGIN = "/path/to/reverb.dll"

engine = daw.RenderEngine(SAMPLE_RATE, BUFFER_SIZE)

# Create synth
synth = engine.make_plugin_processor("synth", SYNTH_PLUGIN)

# Edit and save state
synth.open_editor()
synth.save_state('/path/to/state1')

# Setup automation
synth.record_automation = True
duration = 10
automation = 0.5 + 0.5 * np.sin(np.linspace(0, 4*np.pi, int(duration * SAMPLE_RATE)))
synth.set_automation(1, automation)

# Add MIDI
synth.add_midi_note(60, 100, 0.0, 2.0)
synth.add_midi_note(64, 100, 2.0, 2.0)
synth.add_midi_note(67, 100, 4.0, 2.0)

# Create effect
reverb = engine.make_plugin_processor("reverb", REVERB_PLUGIN)

# Build graph
graph = [
    (synth, []),
    (reverb, ["synth"])
]

engine.load_graph(graph)
engine.set_bpm(120.)
engine.render(10.)

# Save audio
audio = engine.get_audio()
wavfile.write('plugin_output.wav', SAMPLE_RATE, audio.transpose())

# Get automation data
recorded_automation = synth.get_automation()

# Save MIDI
synth.save_midi('output.mid')
```

--------------------------------

### Complete PlaybackWarpProcessor Example

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/playback_warp.md

A comprehensive example demonstrating the setup of the RenderEngine, loading audio, creating a PlaybackWarpProcessor, loading Ableton warp markers, and configuring loop properties.

```python
import dawdreamer as daw
import librosa
from scipy.io import wavfile

SAMPLE_RATE = 44100
BUFFER_SIZE = 512

engine = daw.RenderEngine(SAMPLE_RATE, BUFFER_SIZE)
engine.set_bpm(130.)

# Load audio
audio, _ = librosa.load("drum_loop.wav", sr=SAMPLE_RATE, mono=False)

# Create processor
playback = engine.make_playbackwarp_processor("drums", audio)

# Load Ableton warp markers
playback.set_clip_file("drum_loop.wav.asd")

# Adjust clip properties
playback.loop_on = True
playback.loop_start = 0.0
playback.loop_end = 4.0
```

--------------------------------

### Movie Generation Setup (Optional)

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/mashup_generator/mashup_generator.ipynb

This section is for generating a movie from the audio. It requires ImageMagick to be installed and the 'magick.exe' environment variable to be set.

```python
# This optional section is for making a movie.
# You must install imagemagick and set an environment variable to magick.exe. See the MoviePy installation instructions.
```

--------------------------------

### Install JAX/Flax Dependencies

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/examples.md

Install JAX and Flax for examples involving differentiable audio processing and machine learning.

```bash
pip install jax flax
```

--------------------------------

### Launch Jupyter Notebook

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/examples.md

Navigate to the examples directory and launch Jupyter Notebook to run the interactive examples.

```bash
cd examples/
jupyter notebook
```

--------------------------------

### Build VST3 Examples on Windows with CMake

Source: https://github.com/dbraun/dawdreamer/blob/main/JuceLibraryCode/modules/juce_audio_processors/format_types/VST3_SDK/README.md

Commands to generate Visual Studio projects and build VST3 examples on Windows using CMake. Includes options for specifying the generator, architecture, and VST3 installation path.

```bash
mkdir build
cd build
```

```bash
cmake.exe -G "Visual Studio 17 2022" -A x64 ..\vst3sdk
```

```bash
cmake.exe -G "Visual Studio 17 2022" -A x64 ..\vst3sdk -DSMTG_CREATE_PLUGIN_LINK=0
```

```bash
cmake.exe -G "Visual Studio 17 2022" -A x64 -DSMTG_PLUGIN_TARGET_USER_PROGRAM_FILES_COMMON=1
```

```bash
msbuild.exe vstsdk.sln
```

```bash
cmake --build . --config Release
```

--------------------------------

### Complete Mixer Example

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/other_processors.md

A full example demonstrating loading audio, creating playback processors, instantiating an AddProcessor, building the audio graph, and rendering.

```python
import dawdreamer as daw
import librosa

engine = daw.RenderEngine(44100, 512)

# Load audio files
vocals = engine.make_playback_processor("vocals", librosa.load("vocals.wav", sr=44100, mono=False)[0])
piano = engine.make_playback_processor("piano", librosa.load("piano.wav", sr=44100, mono=False)[0])
guitar = engine.make_playback_processor("guitar", librosa.load("guitar.wav", sr=44100, mono=False)[0])

# Create mixer
mixer = engine.make_add_processor("mixer", [0.4, 0.4, 0.4])

# Build graph
graph = [
    (vocals, []),
    (piano, []),
    (guitar, []),
    (mixer, ["vocals", "piano", "guitar"])
]

engine.load_graph(graph)
engine.render(10.0)
mixed = engine.get_audio()
```

--------------------------------

### Windows Installation

Source: https://github.com/dbraun/dawdreamer/blob/main/CLAUDE.md

Sets environment variables for Python version, builds the Visual Studio solution, and installs the package in develop mode.

```cmd
set PYTHONMAJOR=3.11 && set pythonLocation=C:\Python311
msbuild Builds/VisualStudio2022/DawDreamer.sln /property:Configuration=Release
python setup.py develop
```

--------------------------------

### Run Standalone Python Script Example

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/examples.md

Execute standalone Python script examples directly from their respective directories.

```bash
cd examples/dj_mixing/
python dj_mixing.py
```

--------------------------------

### Complete DawDreamer Audio Playback Example

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/playback.md

A comprehensive example showing how to load multiple audio files (vocals, drums, bass), create PlaybackProcessors for each, mix them using an AddProcessor, build the graph, render the audio, and save the final mix to a WAV file.

```python
import dawdreamer as daw
import librosa
from scipy.io import wavfile

SAMPLE_RATE = 44100
engine = daw.RenderEngine(SAMPLE_RATE, 512)

# Load multiple audio files
vocals, _ = librosa.load("vocals.wav", sr=SAMPLE_RATE, mono=False)
drums, _ = librosa.load("drums.wav", sr=SAMPLE_RATE, mono=False)
bass, _ = librosa.load("bass.wav", sr=SAMPLE_RATE, mono=False)

# Create playback processors
vocals_pb = engine.make_playback_processor("vocals", vocals)
drums_pb = engine.make_playback_processor("drums", drums)
bass_pb = engine.make_playback_processor("bass", bass)

# Create mixer
mixer = engine.make_add_processor("mixer", [0.4, 0.4, 0.4])

# Build graph
graph = [
    (vocals_pb, []),
    (drums_pb, []),
    (bass_pb, []),
    (mixer, ["vocals", "drums", "bass"])
]

engine.load_graph(graph)

# Render
duration = max(vocals.shape[1], drums.shape[1], bass.shape[1]) / SAMPLE_RATE
engine.render(duration)

# Save result
audio = engine.get_audio()
wavfile.write('mix.wav', SAMPLE_RATE, audio.transpose())
```

--------------------------------

### Install Dependencies

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Box_API/Faust_Box_API.ipynb

Installs necessary Python libraries for DawDreamer and audio processing if running in Google Colab.

```python
if 'google.colab' in str(get_ipython()):
    !pip install numpy librosa scipy ipython
```

--------------------------------

### Compressor Processor Setup

Source: https://github.com/dbraun/dawdreamer/wiki/Other-Processors

Details the creation and configuration of a compressor processor, including parameters for threshold, ratio, attack, and release times.

```python
threshold = 0. # dB level of threshold
ratio = 2. # greater than or equal to 1.
attack = 2. # attack of compressor in milliseconds
release = 50. # release of compressor in milliseconds

compressor_processor = engine.make_compressor_processor("my_compressor", threshold, ratio, attack, release)
# CompressorProcessor has getters/setters
compressor_processor.threshold = threshold
compressor_processor.ratio = ratio
compressor_processor.attack = attack
compressor_processor.release = release

```

--------------------------------

### Verify DawDreamer Installation

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/installation.md

Run a simple Python script to import DawDreamer and initialize the RenderEngine. A success message indicates the installation was successful.

```python
import dawdreamer as daw
engine = daw.RenderEngine(44100, 512)
print("DawDreamer installed successfully!")
```

--------------------------------

### Install Brax and Jumanji

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Faust_to_QDax/Faust_to_QDax.ipynb

Installs the Brax and Jumanji libraries. The `|tail -n 1` is used to display only the last line of the pip installation output.

```python
try:
    pass
except:
    !pip install brax==0.9.2 |tail -n 1

try:
    pass
except:
    !pip install jumanji==0.3.1
```

--------------------------------

### Stereo Reverb Example with Faust Processor

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/faust_processor.md

A complete example demonstrating loading a Faust DSP reverb, setting parameters, loading an input audio file, and rendering the processed audio to a WAV file.

```python
import dawdreamer as daw
from scipy.io import wavfile
import librosa

DSP_PATH = "/absolute/path/to/faust_reverb.dsp"
INPUT_AUDIO_PATH = "/path/to/piano.wav"
DURATION = 10.
SAMPLE_RATE = 44100

engine = daw.RenderEngine(SAMPLE_RATE, 512)
faust_processor = engine.make_faust_processor("faust")
faust_processor.set_dsp(DSP_PATH)

# Compile early to catch errors
faust_processor.compile()

print(faust_processor.get_parameters_description())

# Set parameters
faust_processor.set_parameter("/Zita_Light/Dry/Wet_Mix", 1.)

# Load input audio
audio, _ = librosa.load(INPUT_AUDIO_PATH, sr=SAMPLE_RATE, mono=False)
playback = engine.make_playback_processor("piano", audio)

# Build graph
graph = [
    (playback, []),
    (faust_processor, ["piano"])
]

engine.load_graph(graph)
engine.render(DURATION)

output_audio = engine.get_audio()
wavfile.write('reverb_output.wav', SAMPLE_RATE, output_audio.transpose())
```

--------------------------------

### Basic Faust Sine Wave Example

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/index.md

A basic example demonstrating how to create a Faust processor for a sine wave, load it into the render engine, and render audio. Requires numpy.

```python
import dawdreamer as daw
import numpy as np

# Create engine
engine = daw.RenderEngine(44100, 512)

# Add a Faust processor
faust = engine.make_faust_processor("synth")
faust.set_dsp_string("process = os.osc(440) * 0.1;")

# Load graph and render
engine.load_graph([(faust, [])])
engine.render(2.0)  # 2 seconds

# Get audio
audio = engine.get_audio()  # shape: (channels, samples)
```

--------------------------------

### Build VST3 Examples on macOS with CMake

Source: https://github.com/dbraun/dawdreamer/blob/main/JuceLibraryCode/modules/juce_audio_processors/format_types/VST3_SDK/README.md

Commands to generate Xcode projects and build VST3 examples on macOS using CMake. Includes options for specifying the build type.

```bash
mkdir build
cd build
```

```bash
cmake -GXcode ../vst3sdk
```

```bash
cmake -DCMAKE_BUILD_TYPE=Debug ../
```

```bash
xcodebuild
```

```bash
cmake --build . --config Release
```

--------------------------------

### Install QDax from GitHub

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Faust_to_QDax/Faust_to_QDax.ipynb

Installs the QDax library directly from its development branch on GitHub. The `--no-deps` flag prevents reinstallation of dependencies, and `|tail -n 1` filters the output.

```python
try:
    pass
except:
    !pip install --no-deps git+https://github.com/adaptive-intelligent-robotics/QDax@develop |tail -n 1
```

--------------------------------

### Install Build and Wheel Modules

Source: https://github.com/dbraun/dawdreamer/wiki/Developer's-Guide

Install the 'build' and 'wheel' Python packages using pip. These are necessary for creating Python distribution packages.

```bash
python -m pip install build wheel
```

--------------------------------

### Basic Faust Sine Tone Example

Source: https://github.com/dbraun/dawdreamer/blob/main/README.md

This example demonstrates how to create a stereo sine tone using Faust within DawDreamer. It covers initializing the render engine, defining a Faust DSP string, setting parameters, rendering audio, and saving it to a WAV file. The example also shows how to change parameters and re-render.

```python
import dawdreamer as daw
from scipy.io import wavfile
SAMPLE_RATE = 44100
engine = daw.RenderEngine(SAMPLE_RATE, 512)  # 512 block size
faust_processor = engine.make_faust_processor("faust")
faust_processor.set_dsp_string(
    """
    declare name "MySine";
    freq = hslider("freq", 440, 0, 20000, 0);
    gain = hslider("vol[unit:dB]", 0, -120, 20, 0) : ba.db2linear;
    process = freq : os.osc : _*gain <: si.bus(2);
    """
    )
print(faust_processor.get_parameters_description())
engine.load_graph([
                   (faust_processor, [])
])
faust_processor.set_parameter("/MySine/freq", 440.)  # 440 Hz
faust_processor.set_parameter("/MySine/vol", -6.)  # -6 dB volume

engine.set_bpm(120.)
engine.render(4., beats=True)  # render 4 beats.
audio = engine.get_audio()  # shaped (2, N samples)
wavfile.write("sine_demo.wav", SAMPLE_RATE, audio.T)

# Change settings and re-render
faust_processor.set_parameter("/MySine/freq", 880.)  # 880 Hz
engine.render(4., beats=True)

```

--------------------------------

### macOS Installation

Source: https://github.com/dbraun/dawdreamer/blob/main/CLAUDE.md

Sets environment variables for Python version and architecture, builds the project using a macOS specific script, and installs in develop mode.

```bash
export PYTHONMAJOR=3.11 ARCHS=arm64
export pythonLocation=/Library/Frameworks/Python.framework/Versions/3.11
./build_macos.sh && ARCHS=$ARCHS python3.11 setup.py develop
```

--------------------------------

### Print Initial Model Parameters

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Faust_to_JAX/Faust_to_JAX.ipynb

Prints the initial parameters for both the hidden model and the training model to observe their starting states.

```python
print("hidden params:", hidden_params)
print("train params:", train_params)
```

--------------------------------

### Install DawDreamer and Dependencies

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/examples.md

Install DawDreamer and common dependencies using pip. Some examples may require additional libraries like JAX, Flax, or QDax.

```bash
pip install dawdreamer
pip install librosa scipy numpy matplotlib jupyter
```

--------------------------------

### Audio-Rate and PPQN-Rate Automation

Source: https://context7.com/dbraun/dawdreamer/llms.txt

This example demonstrates advanced parameter automation using `processor.set_automation`. It shows how to automate parameters at audio-rate (per sample) and PPQN-rate (musically synced) for dynamic synth control. It also covers recording automation during rendering and retrieving it afterwards.

```python
import dawdreamer as daw
import numpy as np
from scipy.io import wavfile

SAMPLE_RATE = 44100
PPQN = 960
engine = daw.RenderEngine(SAMPLE_RATE, 128)  # small buffer for smooth automation

faust = engine.make_faust_processor("synth")
faust.set_dsp_string("""
    declare name "MySynth";
    freq  = hslider("freq",  440, 20, 20000, 1);
    cutoff = hslider("cutoff", 5000, 20, 20000, 1);
    process = freq : os.osc : fi.lowpass(4, cutoff) <: _, _;
""")

duration = 8.0
num_samples = int(duration * SAMPLE_RATE)

# Audio-rate: glide freq from 220 to 880 Hz
freq_glide = np.linspace(220.0, 880.0, num_samples, dtype=np.float32)
faust.set_automation("/MySynth/freq", freq_glide)

# PPQN-rate: cutoff filter opens on the beat (4 beats)
beats = 4
pulses = beats * PPQN
cutoff_values = np.linspace(500.0, 12000.0, pulses, dtype=np.float32)
faust.set_automation("/MySynth/cutoff", cutoff_values, ppqn=PPQN)

# Record all parameter automation after render
faust.record_automation = True

engine.load_graph([(faust, [])])
engine.set_bpm(120.0)
engine.render(beats, beats=True)

audio = engine.get_audio()
wavfile.write("automated_synth.wav", SAMPLE_RATE, audio.T)

# Retrieve recorded parameter automation as dict of arrays
all_automation = faust.get_automation()
# e.g. {'/MySynth/freq': np.array([...]), '/MySynth/cutoff': np.array([...])}
print({k: v.shape for k, v in all_automation.items()})
```

--------------------------------

### Initialize Dawdreamer Engine and Load Plugins

Source: https://github.com/dbraun/dawdreamer/wiki/Plugin-Processor

Sets up the audio engine and creates instances of VST/AU plugins. Ensure plugin paths are correct and supported extensions are used.

```python
BUFFER_SIZE = 128
PPQN = 960
SYNTH_PLUGIN = "C:/path/to/synth.dll"
REVERB_PLUGIN = "C:/path/to/reverb.dll"
MIDI_PATH = "C:/path/to/song.mid"

engine = daw.RenderEngine(SAMPLE_RATE, BUFFER_SIZE)

synth = engine.make_plugin_processor("my_synth", SYNTH_PLUGIN)
assert synth.get_name() == "my_synth"

```

--------------------------------

### Install DawDreamer with PyPI

Source: https://github.com/dbraun/dawdreamer/blob/main/README.md

Install the DawDreamer library using pip. Ensure you have a compatible Python version installed.

```bash
pip install dawdreamer
```

--------------------------------

### Install and Verify DawDreamer

Source: https://github.com/dbraun/dawdreamer/blob/main/CLAUDE.md

Install the DawDreamer package in editable mode and verify the installation by creating a RenderEngine instance.

```bash
pip install -e .

# Verify
python3 -c "import dawdreamer; dawdreamer.RenderEngine(44100, 512)"
```

--------------------------------

### Linux Prerequisites and Installation

Source: https://github.com/dbraun/dawdreamer/blob/main/CLAUDE.md

Installs necessary dependencies for DawDreamer on Linux, updates submodules, downloads Faust libraries, and then installs the package.

```bash
# Install dependencies
sudo apt-get install -yq build-essential clang cmake git python3-dev \
  libboost-all-dev libfreetype6-dev libncurses-dev \
  libx11-dev libxrandr-dev libasound2-dev libxcomposite-dev

# Submodules and Faust
git submodule update --init --recursive
cd thirdparty/libfaust && python3 download_libfaust.py && cd ../..

# Build and install (builds C++, copies .so, installs package)
pip install -e .
```

--------------------------------

### Complete Audio Rendering Workflow in Python

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/render_engine.md

Demonstrates setting up a render engine, creating Faust processors, loading a graph, and rendering audio with both static and dynamic BPM. Ensure necessary libraries like dawdreamer and numpy are installed.

```python
import dawdreamer as daw
import numpy as np
from scipy.io import wavfile

# Setup
SAMPLE_RATE = 44100
BUFFER_SIZE = 512
engine = daw.RenderEngine(SAMPLE_RATE, BUFFER_SIZE)

# Create processors
synth = engine.make_faust_processor("synth")
synth.set_dsp_string("process = os.osc(440) * 0.1;")

# Load graph
engine.load_graph([(synth, [])])

# Render with static BPM
engine.set_bpm(120.)
engine.render(4., beats=True)
audio1 = engine.get_audio()

# Render with dynamic BPM
ppqn = 960
bpm_ramp = np.linspace(120, 180, 4 * ppqn)
engine.set_bpm(bpm_ramp, ppqn=ppqn)
engine.render(4., beats=True)
audio2 = engine.get_audio()

# Save outputs
wavfile.write('static_bpm.wav', SAMPLE_RATE, audio1.transpose())
wavfile.write('dynamic_bpm.wav', SAMPLE_RATE, audio2.transpose())
```

--------------------------------

### Install DawDreamer Wheel

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/installation.md

Install the generated DawDreamer wheel package using pip. This command installs the package from the local 'dist' directory.

```bash
python -m pip install dist/dawdreamer-*.whl
```

--------------------------------

### Query and Set Plugin Parameters

Source: https://context7.com/dbraun/dawdreamer/llms.txt

Demonstrates how to query parameter ranges, set parameters by index, and load/save plugin states. Use `open_editor()` for interactive tweaking.

```python
par_range = synth.get_parameter_range(10, search_steps=1000, convert=False)
print(par_range)
synth.set_parameter(7, 0.1234)
```

```python
synth.load_state("/path/to/my_synth_state")
synth.load_preset("/path/to/preset.fxp")       # VST2 FXP
synth.load_vst3_preset("/path/to/p.vstpreset")  # VST3
```

--------------------------------

### Install DawDreamer

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Box_API/Faust_Box_API.ipynb

Installs the DawDreamer library if it's not already found.

```python
try:
    import dawdreamer
except ModuleNotFoundError:
    !pip install dawdreamer
```

--------------------------------

### JAX Model Inference Setup

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Faust_to_QDax/Faust_to_QDax.ipynb

This code prepares a JAX model for inference by JIT-compiling the `apply` method and setting up input tensors for frequency, gain, and gate.

```python
jit_inference_fn = jax.jit(model.apply, static_argnums=[2])

# 2 seconds
T = int(SAMPLE_RATE * 2.0)

# Hold for 1 second
hold_length = int(SAMPLE_RATE * 1.0)

# Play the synth as 440 Hz.
freq = jnp.full((T,), 440.0)

```

--------------------------------

### Initialize RenderEngine

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/quickstart.md

Create an instance of the RenderEngine with the desired sample rate and block size.

```python
engine = daw.RenderEngine(sample_rate=44100, block_size=512)
```

--------------------------------

### Install DawDreamer Wheel

Source: https://github.com/dbraun/dawdreamer/wiki/Developer's-Guide

Install the built DawDreamer Python wheel. Replace 'dist/dawdreamer.whl' with the correct path to your wheel file.

```bash
python -m pip install dist/dawdreamer.whl
```

--------------------------------

### Verify DawDreamer Installation

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/installation.md

Verify that DawDreamer is installed correctly by importing the library and creating a RenderEngine instance. This confirms the build was successful.

```python
python3 -c "import dawdreamer as daw; engine = daw.RenderEngine(44100, 512); print('Success!')"
```

--------------------------------

### Initialize RenderEngine and Set BPM

Source: https://context7.com/dbraun/dawdreamer/llms.txt

Demonstrates initializing the RenderEngine with sample rate and block size, and setting static or dynamic BPM values. Dynamic BPM can be set using a NumPy array for tempo automation.

```python
import dawdreamer as daw
import numpy as np
from scipy.io import wavfile

SAMPLE_RATE = 44100
BUFFER_SIZE = 512  # smaller = finer automation, higher CPU

engine = daw.RenderEngine(SAMPLE_RATE, BUFFER_SIZE)

# Static BPM (default 120)
engine.set_bpm(130.0)

# Dynamic BPM via PPQN-rate NumPy array (tempo automation)
PPQN = 960
duration = 8.0  # seconds
bpm_array = np.linspace(120.0, 160.0, int(duration * PPQN / 60), dtype=np.float32)
# Note: array length = beats * PPQN; each element is one BPM value per pulse
engine.set_bpm(bpm_array, ppqn=PPQN)

# Render by seconds
engine.render(4.0)                  # 4 seconds
audio = engine.get_audio()          # shape: (channels, num_samples), dtype: float32

# Render by beats (uses current BPM)
engine.set_bpm(120.0)
engine.render(8.0, beats=True)      # 8 beats = 4 seconds at 120 BPM
audio = engine.get_audio()          # shape: (2, 176400)

# Retrieve audio from a specific processor by name (requires processor.record = True)
intermediate = engine.get_audio("my_processor_name")

# Save to WAV
wavfile.write("output.wav", SAMPLE_RATE, audio.T)
```

--------------------------------

### Reverb Processor Initialization

Source: https://github.com/dbraun/dawdreamer/wiki/Other-Processors

Explains how to instantiate a basic reverb processor from JUCE, setting parameters such as room size, damping, wet/dry levels, and width.

```python
# Basic reverb processor from JUCE.
room_size = 0.5
damping = 0.5
wet_level = 0.33
dry_level = 0.4
width = 1.
reverb_processor = engine.make_reverb_processor("my_reverb", room_size, damping, wet_level, dry_level, width)
# ReverbProcessor has getters/setters
reverb_processor.room_size = room_size
reverb_processor.damping = damping
reverb_processor.wet_level = wet_level
reverb_processor.dry_level = dry_level
reverb_processor.width = width

```

--------------------------------

### Run CLI Example for Parallel Sound Generation

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/xml_synth_sound_rendering/README.md

Use this command to generate many sounds in parallel with the TAL-U-NO-LX VST plugin using multiprocessing. Adjust the plugin and preset directory paths as needed.

```bash
python main.py --plugin "path/to/TAL-U-NO-LX-V2.vst3" --preset-dir "path/to/TAL-U-NO-LX_presets"
```

--------------------------------

### Install DawDreamer on macOS using setup.py

Source: https://github.com/dbraun/dawdreamer/blob/main/DEVELOPER.md

Installs the DawDreamer Python package in editable mode on macOS, using the specified Python version.

```bash
ARCHS=$ARCHS python3.11 setup.py develop
```

--------------------------------

### Prepare for Loss Landscape Analysis

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Faust_to_JAX/Faust_to_JAX.ipynb

Selects a single input example and its corresponding ground truth output to prepare for analyzing the loss landscape. This involves holding all parameters constant except for one that will be varied.

```python
# Pick a single example
x = noises[0:1]
y = hidden_model.apply({"params": hidden_params}, x, T)

# Pick the first param to be the varying parameter.
```

--------------------------------

### Delay Processor Setup

Source: https://github.com/dbraun/dawdreamer/wiki/Other-Processors

Illustrates the creation of a delay processor, specifying delay time in milliseconds and the wet/dry mix. Currently, only the linear delay rule is supported.

```python
delay_rule = "linear" # only linear is supported right now
delay_ms = 200. # delay in milliseconds
delay_wet = .3 # 0 means use all of original signal and none of the "wet" delayed signal. 1. is the opposite.
delay_processor = engine.make_delay_processor("my_delay", delay_rule, delay_ms, delay_wet)
# delay_processor.rule = "linear" # modifying the rule is not supported yet.
delay_processor.delay = delay_ms
delay_processor.wet = delay_wet

```

--------------------------------

### Add and Playback Processors

Source: https://github.com/dbraun/dawdreamer/wiki/Other-Processors

Demonstrates creating and configuring add and playback processors, loading audio files, setting up a Faust effect, defining an audio graph, and rendering audio. Playback processors can have their data updated between renders.

```python
add_processor = engine.make_add_processor("added")
# or start with gain values
add_processor = engine.make_add_processor("added", [0.25, 0.42, 0.30])
add_processor.gain_levels = [0.26, 0.41, 0.31] # Adjust gain levels whenever you want.

import librosa

def load_audio_file(file_path, duration=None):
  sig, rate = librosa.load(file_path, duration=duration, mono=False, sr=SAMPLE_RATE)
  assert(rate == SAMPLE_RATE)
  return sig

# load stereo wav files into playback
vocals = engine.make_playback_processor("vocals", load_audio_file("vocals.wav"))
piano = engine.make_playback_processor("piano", load_audio_file("piano.wav"))
guitar = engine.make_playback_processor("guitar", load_audio_file("guitar.wav"))

faust_effect = engine.make_faust_processor("faust")
faust_effect.set_dsp_string("process = sp.stereoize( fi.lowpass(2, 5000.) );")
faust_effect.record = True

# A graph is a meaningfully ordered list of tuples.
# In each tuple, the first item is an audio processor.
# The second item is this audio processor's list of input processors by their unique names.
# Note that you can use either hard-coded strings or `get_name()` to make this list.
# The audio from the last tuple's processor will be accessed automatically later by engine.get_audio()
graph = [
  (vocals, []), # Playback has no inputs.
  (piano, []), # Playback has no inputs.
  (guitar, []),  # Playback has no inputs
  (faust_effect, ["guitar"])
  (add_processor, ["vocals", "piano", "faust"])
]

engine.load_graph(graph)
engine.render(5.)

# You can get the audio of any processor whose recording was enabled.
filtered_guitar = faust_effect.get_audio()
# Or get audio according to the processor's unique name
filtered_guitar = engine.get_audio("faust")

# You can set playback data in between rendering.
vocals.set_data(load_audio_file("other_vocals.wav"))

```

--------------------------------

### Install Linux Dependencies

Source: https://github.com/dbraun/dawdreamer/wiki/Developer's-Guide

Install essential development packages on Ubuntu systems. This includes build tools, compilers, and libraries required for DawDreamer.

```bash
apt-get install -yq --no-install-recommends \
ca-certificates \
build-essential \
clang \
pkg-config \
libboost-all-dev \
libboost-python-dev \
libfreetype6-dev \
libx11-dev \
libxinerama-dev \
libxrandr-dev \
libxcursor-dev \
mesa-common-dev \
libasound2-dev \
freeglut3-dev \
libxcomposite-dev \
libcurl4-gnutls-dev \
git \
cmake \
python3 \
python3.10-dev
```

--------------------------------

### Install Matplotlib and IPyMPL for Colab

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Faust_to_QDax/Faust_to_QDax.ipynb

Installs `ipympl`, `librosa`, and `matplotlib` if running in a Google Colab environment. Otherwise, it sets up matplotlib for inline plotting.

```python
if "google.colab" in str(get_ipython()):
    !pip install ipympl librosa matplotlib |tail -n 1
else:
    %matplotlib inline
```

--------------------------------

### Streamlined DawDreamer Installation for Automation

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/installation.md

A streamlined command for installing DawDreamer with minimal output, suitable for automated builds or LLM interactions. Includes verification.

```bash
# Quick install if C++ library already exists (minimal output)
python3 setup.py develop --quiet 2>&1 | grep -E '(Successfully|ERROR|Failed)' || \
  (echo "Installing (1-2 min on WSL2)..." && \
   python3 setup.py develop --quiet && \
   echo "✓ Installed successfully")

# Verify silently
python3 -c "import dawdreamer; dawdreamer.RenderEngine(44100, 512)" && \
  echo "✓ Working" || echo "✗ Failed"
```

--------------------------------

### Argument Parser Setup

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Faust_to_JAX/Faust_to_JAX.ipynb

Configures command-line arguments for the DSP model testing script, including sample rate, duration, input/output files, and random seed.

```python
if __name__ == '__main__':
	import argparse
	parser = argparse.ArgumentParser(description='Run a JAX/Flax model converted from Faust code')
	parser.add_argument('-sr', '--sample-rate', type=int, default=44100, help='Sample rate (such as 44100)')
	parser.add_argument('-d', '--duration', type=float, default=None, help='Output duration in seconds')
	parser.add_argument('--random', action='store_true',
		help="Whether the default audio is random. By default it's an impulse.")
	parser.add_argument('--seed', default=0, type=int, help="Seed for random number generator (default: 0)")
	parser.add_argument('-i', '--input', type=str, default=None, help='Filepath for input audio WAV')
```

--------------------------------

### Install Linux Dependencies

Source: https://github.com/dbraun/dawdreamer/blob/main/DEVELOPER.md

Installs all necessary packages for building DawDreamer on Ubuntu/Debian systems. Ensure you have sufficient disk space and a stable internet connection.

```bash
apt-get install -yq --no-install-recommends \
  ca-certificates build-essential clang pkg-config \
  libboost-all-dev libboost-python-dev libfreetype6-dev \
  libx11-dev libxinerama-dev libxrandr-dev libxcursor-dev \
  mesa-common-dev libasound2-dev freeglut3-dev \
  libxcomposite-dev libcurl4-gnutls-dev libncurses-dev \
  git cmake python3 python3-dev
```

--------------------------------

### Create and Load Audio Processing Graph

Source: https://github.com/dbraun/dawdreamer/blob/main/DEVELOPER.md

Demonstrates creating Faust and plugin processors, defining their connections in a graph, loading the graph into the engine, and rendering audio. Ensure processor names are unique for graph connectivity.

```python
synth = engine.make_faust_processor("synth")
synth.set_dsp_string("process = os.osc(440) : *(0.1);")

effect = engine.make_plugin_processor("reverb", "path/to/plugin.dll")

# Build graph
graph = [
    (synth, []),           # synth takes no input
    (effect, ["synth"])
]
engine.load_graph(graph)

# Render
engine.set_bpm(120)
engine.render(4., beats=True)  # 4 beats

# Get audio
audio = engine.get_audio()  # shape (channels, samples)
```

--------------------------------

### Create RenderEngine in Python

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/index.md

Initializes the audio rendering engine with a specified sample rate and buffer size.

```python
import dawdreamer as daw
engine = daw.RenderEngine(44100, 512)
```

--------------------------------

### Install Dependencies

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Faust_to_JAX/Faust_to_JAX.ipynb

Installs necessary Python packages including numpy, scipy, librosa, jax, flax, and optax. This is typically run in a Google Colab environment.

```python
if "google.colab" in str(get_ipython()):
    !pip install numpy scipy librosa jax flax optax
```

--------------------------------

### Install Pre-commit Hooks

Source: https://github.com/dbraun/dawdreamer/blob/main/DEVELOPER.md

Installs and enables pre-commit hooks for code quality checks. These hooks automatically format code and check for common issues before commits.

```bash
pip install pre-commit
pre-commit install
```

--------------------------------

### Create RenderEngine Instance

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/render_engine.md

Instantiate the RenderEngine with a specified sample rate and block size. The block size affects parameter automation granularity.

```python
import dawdreamer as daw

SAMPLE_RATE = 44100
BUFFER_SIZE = 128  # Parameters will undergo automation at this block size

# Make an engine. We typically only need one.
engine = daw.RenderEngine(SAMPLE_RATE, BUFFER_SIZE)
```

--------------------------------

### Set Up JAX Training State and Step Function

Source: https://github.com/dbraun/dawdreamer/blob/main/examples/Faust_to_JAX/Faust_to_JAX.ipynb

This snippet configures the Optax optimizer, creates a 'TrainState' for managing model parameters and optimizer state, and defines a JAX-jitted 'train_step' function for a single training iteration, including loss calculation and gradient application.

```python
learning_rate = 2e-1  # @param {type: 'number'}
momentum = 0.95  # @param {type: 'number'}

# Create Train state
tx = optax.sgd(learning_rate, momentum)
state = train_state.TrainState.create(apply_fn=train_model.apply, params=train_params, tx=tx)


@jax.jit
def train_step(state, x, y):
    """Train for a single step."""

    def loss_fn(params):
        pred = train_model.apply({"params": params}, x, T)
        # L1 time-domain loss
        loss = (jnp.abs(pred - y)).mean()
        return loss, pred

    grad_fn = jax.value_and_grad(loss_fn, has_aux=True)
    (loss, pred), grads = grad_fn(state.params)
    state = state.apply_gradients(grads=grads)
    return state, loss


losses = []
cutoffs = []

train_steps = 600
steps_per_eval = 40

pbar = tqdm(range(train_steps))

jit_hidden_model = jax.jit(hidden_model.apply, static_argnums=[2])
```

--------------------------------

### Install DawDreamer Python Package

Source: https://github.com/dbraun/dawdreamer/blob/main/DEVELOPER.md

Installs the DawDreamer Python package in editable mode. This command also handles the C++ build process via setup.py.

```bash
pip install -e .
```

--------------------------------

### Install DawDreamer Python Package (Editable Mode)

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/installation.md

Install the DawDreamer Python package in editable mode using setup.py. This is typically done after building from source.

```bash
python3 setup.py develop
```

--------------------------------

### Add and Render MIDI Notes

Source: https://context7.com/dbraun/dawdreamer/llms.txt

Illustrates how to add individual MIDI notes with velocity, start time, and duration, and then render the audio. MIDI can also be loaded from files.

```python
synth.add_midi_note(60, 100, 0.0, 2.0)
synth.add_midi_note(64, 100, 2.0, 2.0)
synth.add_midi_note(67, 100, 4.0, 2.0)
```

```python
# synth.load_midi("/path/to/song.mid", clear_previous=True, beats=False, all_events=True)
```

--------------------------------

### Install Linux Dependencies

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/installation.md

Install the required system dependencies for building DawDreamer on Debian/Ubuntu-based Linux distributions. This includes build tools, libraries, and Python development headers.

```bash
apt-get install -yq --no-install-recommends \
  ca-certificates \
  build-essential \
  clang \
  pkg-config \
  libboost-all-dev \
  libboost-python-dev \
  libfreetype6-dev \
  libx11-dev \
  libxinerama-dev \
  libxrandr-dev \
  libxcursor-dev \
  mesa-common-dev \
  libasound2-dev \
  freeglut3-dev \
  libxcomposite-dev \
  libcurl4-gnutls-dev \
  libncurses-dev \
  git \
  cmake \
  python3 \
  python3-dev
```

--------------------------------

### Place Clip Twice and Render

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/playback_warp.md

Demonstrates how to set clip positions for repeated patterns, configure Rubber Band options for time-stretching quality, and render the audio. Ensure the engine BPM is set to the target tempo for accurate beat-matching.

```python
playback.set_clip_positions([
    [0., 4., 0.],    # First loop
    [4., 8., 0.]     # Second loop
])

# Set Rubber Band options
playback.set_options(
    daw.PlaybackWarpProcessor.option.OptionTransientsCrisp |
    daw.PlaybackWarpProcessor.option.OptionPitchHighQuality
)

# Render
engine.load_graph([(playback, [])])
engine.render(8., beats=True)

# Save
audio_out = engine.get_audio()
wavfile.write('warped_drums.wav', SAMPLE_RATE, audio_out.transpose())
```

--------------------------------

### Get Plugin Parameters Description

Source: https://github.com/dbraun/dawdreamer/blob/main/docs/user_guide/plugin_processor.md

Retrieves a list of dictionaries, where each dictionary describes an available parameter of the plugin. You can also get a specific parameter's name by its index.

```python
# Returns a list of dictionaries
params = synth.get_parameters_description()
print(params)

# Get specific parameter name by index
param_name = synth.get_parameter_name(1)
print(param_name)  # Example: "A Pan" for Serum oscillator A panning
```

--------------------------------

### Initialize Render Engine

Source: https://github.com/dbraun/dawdreamer/wiki/Render-Engine-and-BPM

Create an instance of the RenderEngine with specified sample rate and buffer size. This is the primary object for audio rendering.

```python
import dawdreamer as daw

SAMPLE_RATE = 44100
BUFFER_SIZE = 128 # Parameters will undergo automation at this buffer/block size.

# Make an engine. We typically only need one.
engine = daw.RenderEngine(SAMPLE_RATE, BUFFER_SIZE)
```