example for refactored stream

check_stream_init_new.py

@@ -0,0 +1,85 @@
+import py_neuromodulation as nm
+from py_neuromodulation.stream.data_processor import DataProcessor
+from py_neuromodulation.stream.rawdata_generator import RawDataGenerator
+from py_neuromodulation.stream.mnelsl_generator import MNELSLGenerator
+from py_neuromodulation.stream.mnelsl_player import LSLOfflinePlayer
+import asyncio
+
+async def main():
+    (
+        RUN_NAME,
+        PATH_RUN,
+        PATH_BIDS,
+        PATH_OUT,
+        datatype,
+    ) = nm.io.get_paths_example_data()
+
+    (
+        raw,
+        data,
+        sfreq,
+        line_noise,
+        coord_list,
+        coord_names,
+    ) = nm.io.read_BIDS_data(PATH_RUN=PATH_RUN)
+
+    channels = nm.utils.create_channels(
+        ch_names=raw.ch_names,
+        ch_types=raw.get_channel_types(),
+        reference="default",
+        bads=raw.info["bads"],
+        new_names="default",
+        used_types=("ecog", "dbs", "seeg"),
+        target_keywords=["MOV_RIGHT"],
+    )
+
+    settings = nm.NMSettings.get_fast_compute()
+
+    data_generator = RawDataGenerator(data,
+                                    settings.sampling_rate_features_hz,
+                                    settings.segment_length_features_ms,
+                                    channels,
+                                    sfreq,
+                                    )
+
+    data_writer = nm.utils.data_writer.DataWriter(
+        out_dir=PATH_OUT, save_csv=True, save_interval=10, experiment_name=RUN_NAME
+    )
+
+    data_processor = DataProcessor(
+        sfreq=sfreq,
+        settings=settings,
+        channels=channels,
+        coord_names=coord_names,
+        coord_list=coord_list,
+        line_noise=line_noise,
+        verbose=True,
+    )
+
+    rawdata_generator = nm.stream.rawdata_generator.RawDataGenerator(
+        data, settings.sampling_rate_features_hz, settings.segment_length_features_ms, channels, sfreq
+    )
+
+    lslplayer = LSLOfflinePlayer(stream_name="example_stream", raw=raw)
+    import numpy as np
+    lslplayer.start_player(chunk_size=30, n_repeat=5000)
+
+    lsl_generator = MNELSLGenerator(
+        segment_length_features_ms=settings.segment_length_features_ms,
+        sampling_rate_features_hz=settings.sampling_rate_features_hz,
+        stream_name="example_stream"
+    )
+
+    stream = nm.Stream(verbose=True)
+
+    # get_event_loop might be necessary for calling run() without the main function
+    #df_features = asyncio.get_event_loop().run_until_complete(
+    features = await stream.run(
+        data_processor=data_processor,
+        #data_generator=rawdata_generator,
+        data_generator=lsl_generator,
+        data_writer=data_writer,
+    )
+
+if __name__ == "__main__":
+    asyncio.run(main())