From 20f2e30df280238fbbd1d4c19382140ff8684e21 Mon Sep 17 00:00:00 2001
From: "Salvador E. Tropea" <salvador@inti.gob.ar>
Date: Wed, 16 Jul 2025 08:55:26 -0300
Subject: [PATCH] [Added][Audio Join][Audio Split] New nodes with test and
 example

---
 README.md                             |  28 ++++++
 example_workflows/join_and_split.jpg  | Bin 0 -> 10713 bytes
 example_workflows/join_and_split.json |   1 +
 source/nodes/nodes_audio.py           | 115 +++++++++++++++++++++++
 source/tests/test_audio_join_split.py | 126 ++++++++++++++++++++++++++
 5 files changed, 270 insertions(+)
 create mode 100644 example_workflows/join_and_split.jpg
 create mode 100644 example_workflows/join_and_split.json
 create mode 100644 source/tests/test_audio_join_split.py

diff --git a/README.md b/README.md
index 0099c69..38400d4 100644
--- a/README.md
+++ b/README.md
@@ -18,6 +18,8 @@ workflows, especially when dealing with multiple audio inputs or outputs.
   - [9. Audio Blend](#9-audio-blend)
   - [10. Audio Test Signal Generator](#10-audio-test-signal-generator)
   - [11. Audio Musical Note](#11-audio-musical-note)
+  - [12. Audio Join 2 Channels](#12-audio-join-2-channels)
+  - [13. Audio Split 2 Channels](#13-audio-split-2-channels)
 - [&#x0001F680; Installation](#-installation)
 - [&#x0001F4E6; Dependencies](#-dependencies)
 - [&#x0001F5BC;&#xFE0F; Examples](#&#xFE0F;-examples)
@@ -195,6 +197,32 @@ workflows, especially when dealing with multiple audio inputs or outputs.
    - **Output:**
      - `frequency` (FLOAT): The calculated frequency of the note in Hz.
 
+### 12. Audio Join 2 Channels
+   - **Display Name:** `Audio Join 2 Channels`
+   - **Internal Name:** `SET_AudioJoin2Channels`
+   - **Category:** `audio/manipulation`
+   - **Description:** Combines two separate audio inputs into a single stereo audio output, treating the first input as the left channel and the second as the right. It intelligently handles misaligned inputs.
+   - **Inputs:**
+     - `audio_left` (AUDIO): The audio signal for the left channel. If it's stereo or multi-channel, it will be automatically converted to mono before being used.
+     - `audio_right` (AUDIO): The audio signal for the right channel. Will also be converted to mono.
+   - **Output:**
+     - `audio_out` (AUDIO): A stereo audio signal.
+   - **Behavior Details:**
+     - **Channel Conversion:** Both `audio_left` and `audio_right` are first forced into mono to ensure they each represent a single channel stream.
+     - **Alignment:** The two mono signals are then aligned to have the same sample rate and length, using the same logic as the "Batch Audios" node (resamples to match `audio_left`'s SR, pads to match the longest duration).
+     - **Batch Handling:** If the inputs have different batch sizes, the last item of the shorter batch is repeated to match the length of the longer batch.
+
+### 13. Audio Split 2 Channels
+   - **Display Name:** `Audio Split 2 Channels`
+   - **Internal Name:** `SET_AudioSplit2Channels`
+   - **Category:** `audio/manipulation`
+   - **Description:** Takes a stereo audio input and separates it into two mono audio outputs, one for the left channel and one for the right.
+   - **Inputs:**
+     - `audio` (AUDIO): The stereo audio signal to be split. **The node will raise an error if the input is not 2-channel stereo.**
+   - **Outputs:**
+     - `audio_left` (AUDIO): A mono audio signal containing only the left channel data.
+     - `audio_right` (AUDIO): A mono audio signal containing only the right channel data.
+
 ## &#x0001F680; Installation
 
 You can install the nodes from the ComfyUI nodes manager, the name is *Audio Batch*, or just do it manually:
diff --git a/example_workflows/join_and_split.jpg b/example_workflows/join_and_split.jpg
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diff --git a/example_workflows/join_and_split.json b/example_workflows/join_and_split.json
new file mode 100644
index 0000000..b398141
--- /dev/null
+++ b/example_workflows/join_and_split.json
@@ -0,0 +1 @@
+{"id":"7a6f4421-11da-41f5-aa24-226ec984ac27","revision":0,"last_node_id":11,"last_link_id":7,"nodes":[{"id":2,"type":"SET_AudioTestSignalGenerator","pos":[1173.3482666015625,1591.795654296875],"size":[275.0025329589844,322],"flags":{},"order":0,"mode":0,"inputs":[{"localized_name":"waveform_type","name":"waveform_type","type":"COMBO","widget":{"name":"waveform_type"},"link":null},{"localized_name":"frequency","name":"frequency","type":"FLOAT","widget":{"name":"frequency"},"link":null},{"localized_name":"frequency_end","name":"frequency_end","type":"FLOAT","widget":{"name":"frequency_end"},"link":null},{"localized_name":"amplitude","name":"amplitude","type":"FLOAT","widget":{"name":"amplitude"},"link":null},{"localized_name":"dc_offset","name":"dc_offset","type":"FLOAT","widget":{"name":"dc_offset"},"link":null},{"localized_name":"phase","name":"phase","type":"FLOAT","widget":{"name":"phase"},"link":null},{"localized_name":"duration","name":"duration","type":"STRING","widget":{"name":"duration"},"link":null},{"localized_name":"sample_rate","name":"sample_rate","type":"INT","widget":{"name":"sample_rate"},"link":null},{"localized_name":"batch_size","name":"batch_size","type":"INT","widget":{"name":"batch_size"},"link":null},{"localized_name":"channels","name":"channels","type":"INT","widget":{"name":"channels"},"link":null},{"localized_name":"seed","name":"seed","shape":7,"type":"INT","widget":{"name":"seed"},"link":null}],"outputs":[{"localized_name":"audio_out","name":"audio_out","type":"AUDIO","links":[3]}],"properties":{"aux_id":"set-soft/ComfyUI-AudioBatch","ver":"c5e110e58b6bb0f5c777084a1edcadb7b86eb5b7","Node name for S&R":"SET_AudioTestSignalGenerator"},"widgets_values":["sweep",880,440,0.5,0,0,"3.0",44100,1,1,735791842302287,"randomize"],"color":"#232","bgcolor":"#353"},{"id":5,"type":"MarkdownNote","pos":[908.039794921875,1221.835693359375],"size":[233.68882751464844,106.25144958496094],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["# A tone going up in frequency for the left channel"],"color":"#432","bgcolor":"#653"},{"id":6,"type":"MarkdownNote","pos":[918.7133178710938,1593.033203125],"size":[233.68882751464844,106.25144958496094],"flags":{},"order":2,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["# A tone going down in frequency for the right channel"],"color":"#432","bgcolor":"#653"},{"id":1,"type":"SET_AudioTestSignalGenerator","pos":[1171.8756103515625,1218.4552001953125],"size":[275.0025329589844,322],"flags":{},"order":3,"mode":0,"inputs":[{"localized_name":"waveform_type","name":"waveform_type","type":"COMBO","widget":{"name":"waveform_type"},"link":null},{"localized_name":"frequency","name":"frequency","type":"FLOAT","widget":{"name":"frequency"},"link":null},{"localized_name":"frequency_end","name":"frequency_end","type":"FLOAT","widget":{"name":"frequency_end"},"link":null},{"localized_name":"amplitude","name":"amplitude","type":"FLOAT","widget":{"name":"amplitude"},"link":null},{"localized_name":"dc_offset","name":"dc_offset","type":"FLOAT","widget":{"name":"dc_offset"},"link":null},{"localized_name":"phase","name":"phase","type":"FLOAT","widget":{"name":"phase"},"link":null},{"localized_name":"duration","name":"duration","type":"STRING","widget":{"name":"duration"},"link":null},{"localized_name":"sample_rate","name":"sample_rate","type":"INT","widget":{"name":"sample_rate"},"link":null},{"localized_name":"batch_size","name":"batch_size","type":"INT","widget":{"name":"batch_size"},"link":null},{"localized_name":"channels","name":"channels","type":"INT","widget":{"name":"channels"},"link":null},{"localized_name":"seed","name":"seed","shape":7,"type":"INT","widget":{"name":"seed"},"link":null}],"outputs":[{"localized_name":"audio_out","name":"audio_out","type":"AUDIO","links":[2]}],"properties":{"aux_id":"set-soft/ComfyUI-AudioBatch","ver":"c5e110e58b6bb0f5c777084a1edcadb7b86eb5b7","Node name for S&R":"SET_AudioTestSignalGenerator"},"widgets_values":["sweep",440,880,0.5,0,0,"3.0",44100,1,1,811796107259925,"randomize"],"color":"#232","bgcolor":"#353"},{"id":4,"type":"SET_AudioJoin2Channels","pos":[1534.503662109375,1465.3570556640625],"size":[179.99569702148438,46],"flags":{},"order":6,"mode":0,"inputs":[{"localized_name":"audio_left","name":"audio_left","type":"AUDIO","link":2},{"localized_name":"audio_right","name":"audio_right","type":"AUDIO","link":3}],"outputs":[{"localized_name":"audio_out","name":"audio_out","type":"AUDIO","links":[4,5]}],"properties":{"aux_id":"set-soft/ComfyUI-AudioBatch","ver":"c5e110e58b6bb0f5c777084a1edcadb7b86eb5b7","Node name for S&R":"SET_AudioJoin2Channels"},"color":"#323","bgcolor":"#535"},{"id":3,"type":"PreviewAudio","pos":[1804.0137939453125,1533.0361328125],"size":[270,88],"flags":{},"order":7,"mode":0,"inputs":[{"localized_name":"audio","name":"audio","type":"AUDIO","link":4},{"localized_name":"audioUI","name":"audioUI","type":"AUDIO_UI","widget":{"name":"audioUI"},"link":null}],"outputs":[],"properties":{"cnr_id":"comfy-core","ver":"0.3.43","Node name for S&R":"PreviewAudio"},"widgets_values":[],"color":"#222","bgcolor":"#000"},{"id":8,"type":"SET_AudioSplit2Channels","pos":[1885.25048828125,1428.18798828125],"size":[181.54745483398438,46],"flags":{},"order":8,"mode":0,"inputs":[{"localized_name":"audio","name":"audio","type":"AUDIO","link":5}],"outputs":[{"localized_name":"audio_left","name":"audio_left","type":"AUDIO","links":[6]},{"localized_name":"audio_right","name":"audio_right","type":"AUDIO","links":[7]}],"properties":{"aux_id":"set-soft/ComfyUI-AudioBatch","ver":"c5e110e58b6bb0f5c777084a1edcadb7b86eb5b7","Node name for S&R":"SET_AudioSplit2Channels"},"color":"#323","bgcolor":"#535"},{"id":9,"type":"PreviewAudio","pos":[2175.8046875,1371.262451171875],"size":[270,88],"flags":{},"order":9,"mode":0,"inputs":[{"localized_name":"audio","name":"audio","type":"AUDIO","link":6},{"localized_name":"audioUI","name":"audioUI","type":"AUDIO_UI","widget":{"name":"audioUI"},"link":null}],"outputs":[],"properties":{"cnr_id":"comfy-core","ver":"0.3.43","Node name for S&R":"PreviewAudio"},"widgets_values":[],"color":"#222","bgcolor":"#000"},{"id":10,"type":"PreviewAudio","pos":[2176.989501953125,1520.69091796875],"size":[270,88],"flags":{},"order":10,"mode":0,"inputs":[{"localized_name":"audio","name":"audio","type":"AUDIO","link":7},{"localized_name":"audioUI","name":"audioUI","type":"AUDIO_UI","widget":{"name":"audioUI"},"link":null}],"outputs":[],"properties":{"cnr_id":"comfy-core","ver":"0.3.43","Node name for S&R":"PreviewAudio"},"widgets_values":[],"color":"#222","bgcolor":"#000"},{"id":7,"type":"MarkdownNote","pos":[1523.5401611328125,1565.7567138671875],"size":[214.71388244628906,88],"flags":{},"order":4,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["# Join both signals"],"color":"#432","bgcolor":"#653"},{"id":11,"type":"MarkdownNote","pos":[1876.94873046875,1281.13232421875],"size":[214.71388244628906,88],"flags":{},"order":5,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["# Split them"],"color":"#432","bgcolor":"#653"}],"links":[[2,1,0,4,0,"AUDIO"],[3,2,0,4,1,"AUDIO"],[4,4,0,3,0,"AUDIO"],[5,4,0,8,0,"AUDIO"],[6,8,0,9,0,"AUDIO"],[7,8,1,10,0,"AUDIO"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.8432169278238191,"offset":[-795.3761557698062,-955.0005895799211]}},"version":0.4}
\ No newline at end of file
diff --git a/source/nodes/nodes_audio.py b/source/nodes/nodes_audio.py
index f273ee6..3dc1119 100644
--- a/source/nodes/nodes_audio.py
+++ b/source/nodes/nodes_audio.py
@@ -659,3 +659,118 @@ class AudioMusicalNote:
             # A UI warning could also be sent if this were a generator.
             logger.error(f"Error parsing note: {e}. Defaulting to 440.0 Hz.")
             return (440.0,)
+
+
+class AudioJoin2Channels:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "audio_left": ("AUDIO", {"tooltip": "The audio signal for the left channel. Will be converted to mono."}),
+                "audio_right": ("AUDIO", {"tooltip": "The audio signal for the right channel. Will be converted to mono."}),
+            },
+        }
+
+    RETURN_TYPES = ("AUDIO",)
+    RETURN_NAMES = ("audio_out",)
+    FUNCTION = "join_channels"
+    CATEGORY = BASE_CATEGORY + "/" + MANIPULATION_CATEGORY
+    DESCRIPTION = "Joins two audio signals (L/R) into a single stereo audio signal."
+    UNIQUE_NAME = "SET_AudioJoin2Channels"
+    DISPLAY_NAME = "Audio Join 2 Channels"
+
+    def join_channels(self, audio_left: dict, audio_right: dict):
+        # 1. Force both inputs to be mono to ensure they represent single channels.
+        # We reuse the logic from AudioChannelConverter.
+        channel_converter = AudioChannelConverter()
+        (mono_left_audio,) = channel_converter.convert_channels(audio_left, "force_mono")
+        (mono_right_audio,) = channel_converter.convert_channels(audio_right, "force_mono")
+
+        # 2. Align the two mono signals in terms of sample rate and length.
+        # This reuses the robust logic from AudioBatchAligner.
+        # The output of the aligner will have channels=1 since both inputs are mono.
+        aligner = AudioBatchAligner(mono_left_audio, mono_right_audio)
+        aligned_left_wf, aligned_right_wf, target_sr = aligner.get_aligned_waveforms()
+
+        # aligned_left_wf is (B_left, 1, N), aligned_right_wf is (B_right, 1, N)
+
+        # 3. Handle mismatched batch sizes.
+        b_left, b_right = aligned_left_wf.shape[0], aligned_right_wf.shape[0]
+        target_batch_size = max(b_left, b_right)
+
+        # Create final waveforms with the target batch size, repeating the last item if needed.
+        final_left_wf = aligned_left_wf
+        if b_left < target_batch_size:
+            last_left_item = aligned_left_wf[-1:, :, :]  # (1, 1, N)
+            repeats_needed = target_batch_size - b_left
+            final_left_wf = torch.cat([aligned_left_wf, last_left_item.repeat(repeats_needed, 1, 1)], dim=0)
+
+        final_right_wf = aligned_right_wf
+        if b_right < target_batch_size:
+            last_right_item = aligned_right_wf[-1:, :, :]  # (1, 1, N)
+            repeats_needed = target_batch_size - b_right
+            final_right_wf = torch.cat([aligned_right_wf, last_right_item.repeat(repeats_needed, 1, 1)], dim=0)
+
+        # At this point, final_left_wf and final_right_wf are both (target_batch_size, 1, N)
+
+        # 4. Concatenate the mono channels into a stereo signal.
+        # `torch.cat` along the channel dimension (dim=1).
+        stereo_waveform = torch.cat((final_left_wf, final_right_wf), dim=1)  # (B, 2, N)
+
+        logger.info(f"Joined L/R channels into stereo audio. Final shape: {stereo_waveform.shape}, SR: {target_sr}")
+
+        output_audio = {
+            "waveform": stereo_waveform,
+            "sample_rate": target_sr
+        }
+        return (output_audio,)
+
+
+class AudioSplit2Channels:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "audio": ("AUDIO", {"tooltip": "A stereo audio signal to split into separate channels."}),
+            },
+        }
+
+    RETURN_TYPES = ("AUDIO", "AUDIO")
+    RETURN_NAMES = ("audio_left", "audio_right")
+    FUNCTION = "split_channels"
+    CATEGORY = BASE_CATEGORY + "/" + MANIPULATION_CATEGORY
+    DESCRIPTION = "Splits a stereo audio signal into two separate mono audio signals (L/R)."
+    UNIQUE_NAME = "SET_AudioSplit2Channels"
+    DISPLAY_NAME = "Audio Split 2 Channels"
+
+    def split_channels(self, audio: dict):
+        waveform = audio['waveform']  # (B, C, N)
+        sample_rate = audio['sample_rate']
+
+        num_channels = waveform.shape[1]
+
+        # 1. Validate that the input is stereo.
+        if num_channels != 2:
+            msg = f"Input audio must be stereo (2 channels) to be split. Got {num_channels} channels."
+            logger.error(msg)
+            # This is a hard requirement, so raising an error is appropriate.
+            raise ValueError(msg)
+
+        # 2. Slice the tensor along the channel dimension.
+        # Slicing with [:, 0:1, :] keeps the channel dimension as 1, so the output is (B, 1, N)
+        left_channel_wf = waveform[:, 0:1, :]
+        right_channel_wf = waveform[:, 1:2, :]
+
+        logger.info(f"Split stereo audio into L/R channels. Output shape for each: {left_channel_wf.shape}")
+
+        # 3. Package each channel into its own ComfyUI AUDIO dict.
+        audio_left = {
+            "waveform": left_channel_wf,
+            "sample_rate": sample_rate
+        }
+        audio_right = {
+            "waveform": right_channel_wf,
+            "sample_rate": sample_rate
+        }
+
+        return (audio_left, audio_right)
diff --git a/source/tests/test_audio_join_split.py b/source/tests/test_audio_join_split.py
new file mode 100644
index 0000000..8d3f71f
--- /dev/null
+++ b/source/tests/test_audio_join_split.py
@@ -0,0 +1,126 @@
+"""
+Regression tests for the AudioJoin2Channels and AudioSplit2Channels nodes in ComfyUI-AudioBatch.
+"""
+
+import bootstrap  # noqa: F401
+import torch
+import pytest
+from nodes.nodes_audio import AudioJoin2Channels, AudioSplit2Channels
+
+
+# Helper function
+def create_dummy_audio(batch_size, channels, samples, sr, device='cpu'):
+    waveform = torch.randn(batch_size, channels, samples, device=device, dtype=torch.float32)
+    return {"waveform": waveform, "sample_rate": sr}
+
+
+@pytest.fixture
+def join_node():
+    return AudioJoin2Channels()
+
+
+@pytest.fixture
+def split_node():
+    return AudioSplit2Channels()
+
+
+# --- Tests for AudioJoin2Channels ---
+
+def test_join_simple(join_node):
+    """Tests joining two perfectly matched mono signals."""
+    sr = 44100
+    samples = 1000
+    left_audio = create_dummy_audio(1, 1, samples, sr)
+    right_audio = create_dummy_audio(1, 1, samples, sr)
+
+    (stereo_audio,) = join_node.join_channels(left_audio, right_audio)
+
+    assert stereo_audio['waveform'].shape == (1, 2, samples)
+    # Check if L/R channels match the original mono inputs
+    assert torch.allclose(stereo_audio['waveform'][:, 0:1, :], left_audio['waveform'])
+    assert torch.allclose(stereo_audio['waveform'][:, 1:2, :], right_audio['waveform'])
+
+
+def test_join_converts_inputs_to_mono(join_node):
+    """Tests that stereo inputs are correctly converted to mono before joining."""
+    sr = 44100
+    samples = 1000
+    # Left input is stereo, Right is mono
+    left_stereo_in = create_dummy_audio(1, 2, samples, sr)
+    right_mono_in = create_dummy_audio(1, 1, samples, sr)
+
+    (result_audio,) = join_node.join_channels(left_stereo_in, right_mono_in)
+
+    # Left channel of the output should be the average of the stereo input
+    expected_left_mono = torch.mean(left_stereo_in['waveform'], dim=1, keepdim=True)
+
+    assert result_audio['waveform'].shape == (1, 2, samples)
+    assert torch.allclose(result_audio['waveform'][:, 0:1, :], expected_left_mono)
+    assert torch.allclose(result_audio['waveform'][:, 1:2, :], right_mono_in['waveform'])
+
+
+def test_join_aligns_and_batches(join_node):
+    """Tests that mismatched SR, length, and batch sizes are handled."""
+    # Left: B=2, 1ch, 44.1k SR, 1s long
+    audio_left = create_dummy_audio(2, 1, 44100, 44100)
+    # Right: B=3, 2ch, 22.05k SR, 0.5s long
+    audio_right = create_dummy_audio(3, 2, 11025, 22050)
+
+    (result_audio,) = join_node.join_channels(audio_left, audio_right)
+
+    # Expected output shape:
+    # Batch size = max(2, 3) = 3
+    # Channels = 2 (stereo)
+    # SR = 44100 (from left)
+    # Samples = 44100 (from left, since right is 11025*2=22050 after resampling)
+    assert result_audio['waveform'].shape == (3, 2, 44100)
+    assert result_audio['sample_rate'] == 44100
+
+    # Check the repeated last item for the left channel
+    assert torch.allclose(result_audio['waveform'][1, 0, :], result_audio['waveform'][2, 0, :])
+
+
+# --- Tests for AudioSplit2Channels ---
+
+def test_split_simple(split_node):
+    """Tests splitting a standard stereo signal."""
+    sr = 44100
+    samples = 1000
+    stereo_audio = create_dummy_audio(1, 2, samples, sr)
+
+    (left_out, right_out) = split_node.split_channels(stereo_audio)
+
+    # Check left channel output
+    assert left_out['sample_rate'] == sr
+    assert left_out['waveform'].shape == (1, 1, samples)
+    assert torch.allclose(left_out['waveform'], stereo_audio['waveform'][:, 0:1, :])
+
+    # Check right channel output
+    assert right_out['sample_rate'] == sr
+    assert right_out['waveform'].shape == (1, 1, samples)
+    assert torch.allclose(right_out['waveform'], stereo_audio['waveform'][:, 1:2, :])
+
+
+def test_split_with_batch(split_node):
+    """Tests that splitting preserves the batch dimension."""
+    sr = 44100
+    samples = 1000
+    stereo_batch = create_dummy_audio(5, 2, samples, sr)
+
+    (left_out, right_out) = split_node.split_channels(stereo_batch)
+
+    assert left_out['waveform'].shape == (5, 1, samples)
+    assert right_out['waveform'].shape == (5, 1, samples)
+
+
+def test_split_raises_error_on_non_stereo(split_node):
+    """Tests that an error is raised if the input is not stereo."""
+    # Test with mono
+    mono_audio = create_dummy_audio(1, 1, 1000, 44100)
+    with pytest.raises(ValueError, match="Input audio must be stereo"):
+        split_node.split_channels(mono_audio)
+
+    # Test with 3 channels
+    three_ch_audio = create_dummy_audio(1, 3, 1000, 44100)
+    with pytest.raises(ValueError, match="Input audio must be stereo"):
+        split_node.split_channels(three_ch_audio)