Fix AudioFrameV3Wrapper::get_data() to return correct float32 audio data

[ichux]

Problem

AudioFrameV3Wrapper::get_data() wraps NDI's float32 planar audio data as a uint8 numpy array with incorrect strides, making all audio received via framesync_capture_audio_v2() unusable in Python.

Specifically:

• The returned numpy array has dtype=uint8 and shape (channels, samples)
• tobytes() returns only 1/4 of the actual audio data (1024 bytes instead of 4096 for a 1024-sample mono frame)
• The array's internal buffer is a COPY that is too small; reading past it via ctypes returns garbage (uninitialized memory)
• All samples appear as NaN or silent corruption

Root Cause

AudioFrameV3Wrapper::get_data() uses sizeof(uint8_t) as the element size and format_descriptor<uint8_t> as the numpy format, but the underlying NDI audio data is always FLTP (float planar, 32-bit).

Meanwhile, AudioFrameV2Wrapper::get_data() correctly uses sizeof(float) and format_descriptor: V3 is a copy-paste error.

The Fix

Change AudioFrameV3Wrapper::get_data() to match AudioFrameV2Wrapper:

Before (buggy):
size = sizeof(uint8_t)
format_descriptor<uint8_t>
stride: {col * size * 4, size} // col * 4 bytes, 1 byte

After (fixed):
size = sizeof(float)
format_descriptor
stride: {col * size, size} // col * 4 bytes, 4 bytes

This changes the numpy array dtype from uint8 to float32 and fixes the stride calculation so the full audio data is accessible.

Why This Is Correct

1. NDI SDK guarantees FLTP format: the FourCC field on AudioFrameV3 is always FOURCC_AUDIO_TYPE_FLTP (float planar). There are no other audio FourCC types in the current SDK.

2. Matches AudioFrameV2Wrapper: the V2 wrapper already handles this correctly. V3 should match.

3. Matches DistroAV (OBS NDI plugin): DistroAV's C++ code accesses p_data directly as float* with channel_stride_in_bytes offsets: confirming the data is float32.

4. Verified on real hardware: tested with NDI Camera Android app sending mono 48kHz audio. After the fix, framesync_capture_audio_v2() returns clean float32 data with shape (channels, samples), dtype=float32, no NaN values, and correct amplitude range.

Reproduction

Before fix:
import NDIlib as ndi
import numpy as np
ndi.initialize()
recv = ndi.recv_create_v3()

... connect to source ...

fs = ndi.framesync_create(recv)
af = ndi.framesync_capture_audio_v2(fs, 0, 0, 1024)
print(af.data.dtype) # uint8 (WRONG)
print(af.data.shape) # (1, 1024) — misleading, only 256 float32 samples fit
print(af.data.nbytes) # 1024 (WRONG, should be 4096)
print(np.any(np.isnan(af.data))) # True (WRONG)

After fix:
print(af.data.dtype) # float32 (CORRECT)
print(af.data.shape) # (1, 1024)
print(af.data.nbytes) # 4096 (CORRECT)
print(np.any(np.isnan(af.data))) # False (CORRECT)
print(af.data.max()) # ~0.002 (real audio from phone mic)

Impact

• Breaking change: No. The array shape stays (channels, samples). Only the dtype changes from uint8 to float32, which is the correct representation of the data.
• Backward compatibility: Code that treated the array as raw bytes via tobytes() will get different output, but that was already broken (only returned 1/4 of the data).
• Performance: No change. Same memory allocation, same data copy.