diff --git a/.gitignore b/.gitignore index 38d7b8e..e5393f0 100644 --- a/.gitignore +++ b/.gitignore @@ -140,3 +140,10 @@ dmypy.json # Vscode ./vscode + +# generated files +**/*localsync_timestamps.npy +**/*original_timestamps.npy +**/*qc.pdf +**/*temporal_alignment.png +**/*ephys-rig-QC_output.txt diff --git a/.vscode/launch.json b/.vscode/launch.json deleted file mode 100644 index 969d736..0000000 --- a/.vscode/launch.json +++ /dev/null @@ -1,16 +0,0 @@ -{ - // Use IntelliSense to learn about possible attributes. - // Hover to view descriptions of existing attributes. - // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387 - "version": "0.2.0", - "configurations": [ - { - "name": "Python Debugger: Current File", - "type": "debugpy", - "request": "launch", - "program": "${file}", - "console": "integratedTerminal", - "justMyCode": false - } - ] -} \ No newline at end of file diff --git a/src/aind_ephys_rig_qc/generate_report.py b/src/aind_ephys_rig_qc/generate_report.py index 06ceb79..3a7db6a 100644 --- a/src/aind_ephys_rig_qc/generate_report.py +++ b/src/aind_ephys_rig_qc/generate_report.py @@ -32,6 +32,7 @@ def generate_qc_report( report_name="QC.pdf", timestamp_alignment_method="local", original_timestamp_filename="original_timestamps.npy", + num_chunks=3, ): """ Generates a PDF report from an Open Ephys data directory @@ -51,6 +52,9 @@ def generate_qc_report( Option 3: 'none' (don't align timestamps) original_timestamp_filename : str The name of the file for archiving the original timestamps + num_chunks : int + The number of chunks to split the data into for plotting raw data + and PSD """ @@ -61,11 +65,15 @@ def generate_qc_report( pdf.add_page() pdf.set_font("Helvetica", "B", size=12) pdf.set_y(30) - pdf.write(h=12, text=f"Overview of recordings in {directory}") + pdf.write(h=12, text=f"Overview of recordings in:") + pdf.set_y(40) + pdf.set_font("Helvetica", size=10) + pdf.write(h=8, text=f"{directory}") pdf.set_font("Helvetica", "", size=10) - pdf.set_y(45) - pdf.embed_table(get_stream_info(directory), width=pdf.epw) + pdf.set_y(60) + stream_info = get_stream_info(directory) + pdf.embed_table(stream_info, width=pdf.epw) if ( timestamp_alignment_method == "local" @@ -82,7 +90,9 @@ def generate_qc_report( "Please check the local alignment of the timestamps." + "And decide if original timestamps should be overwritten." ) - overwrite = input("Overwrite original timestamps? (y/n): ") + overwrite = input( + "Overwrite original timestamps (check 'temporal_alignment.png')? (y/n): " + ) if overwrite == "y": replace_original_timestamps( @@ -121,13 +131,13 @@ def generate_qc_report( else: print("Local timestamps was not overwritten.") - create_qc_plots(pdf, directory) + create_qc_plots(pdf, directory, num_chunks=num_chunks) pdf.output(os.path.join(directory, report_name)) output_content = output_stream.getvalue() - outfile = os.path.join(directory, "rigQc_output.txt") + outfile = os.path.join(directory, "ephys-rig-QC_output.txt") with open(outfile, "a") as output_file: output_file.write(datetime.now().strftime("%Y-%m-%d %H:%M:%S") + "\n") @@ -162,18 +172,15 @@ def get_stream_info(directory): } for recordnode in session.recordnodes: - current_record_node = os.path.basename(recordnode.directory).split( "Record Node " )[1] for recording in recordnode.recordings: - current_experiment_index = recording.experiment_index current_recording_index = recording.recording_index for stream in recording.continuous: - sample_rate = stream.metadata["sample_rate"] data_shape = stream.samples.shape channel_count = data_shape[1] @@ -234,7 +241,9 @@ def get_event_info(events, stream_name): return pd.DataFrame(data=event_info) -def create_qc_plots(pdf, directory): +def create_qc_plots( + pdf, directory, num_chunks=3, raw_chunk_size=1000, psd_chunk_size=10000 +): """ Create QC plots for an Open Ephys data directory """ @@ -242,25 +251,26 @@ def create_qc_plots(pdf, directory): session = Session(directory) for recordnode in session.recordnodes: - current_record_node = os.path.basename(recordnode.directory).split( "Record Node " )[1] for recording in recordnode.recordings: - current_experiment_index = recording.experiment_index current_recording_index = recording.recording_index events = recording.events for stream in recording.continuous: - duration = ( stream.samples.shape[0] / stream.metadata["sample_rate"] ) + start_frames = np.linspace( + 0, stream.samples.shape[0], num_chunks + 1, endpoint=False + )[1:] stream_name = stream.metadata["stream_name"] + sample_rate = stream.metadata["sample_rate"] pdf.add_page() pdf.set_font("Helvetica", "B", size=12) @@ -291,8 +301,7 @@ def create_qc_plots(pdf, directory): pdf.set_y(65) pdf.write( h=10, - text=f"Sample Rate: " - f"{stream.metadata['sample_rate']} Hz", + text=f"Sample Rate: " f"{sample_rate} Hz", ) pdf.set_y(70) pdf.write(h=10, text=f"Channels: {stream.samples.shape[1]}") @@ -309,17 +318,22 @@ def create_qc_plots(pdf, directory): pdf.set_y(120) pdf.embed_figure( plot_raw_data( - stream.samples, - stream.metadata["sample_rate"], - stream_name, + data=stream.samples, + start_frames=start_frames, + sample_rate=sample_rate, + stream_name=stream_name, + chunk_size=raw_chunk_size, ) ) pdf.set_y(200) pdf.embed_figure( plot_power_spectrum( - directory, - stream_name, + data=stream.samples, + start_frames=start_frames, + sample_rate=sample_rate, + stream_name=stream_name, + chunk_size=psd_chunk_size, ) ) @@ -329,7 +343,6 @@ def create_qc_plots(pdf, directory): if __name__ == "__main__": - if len(sys.argv) != 3: print("Two input arguments are required:") print(" 1. A data directory") diff --git a/src/aind_ephys_rig_qc/pdf_utils.py b/src/aind_ephys_rig_qc/pdf_utils.py index ecf67ac..f3a8fe6 100644 --- a/src/aind_ephys_rig_qc/pdf_utils.py +++ b/src/aind_ephys_rig_qc/pdf_utils.py @@ -87,7 +87,7 @@ def embed_table(self, df, width=190): The width of the image in the PDF """ - DF = df.map(str) # convert all elements to string + DF = df.astype(str) # convert all elements to string DATA = [ list(DF) ] + DF.values.tolist() # Combine columns and rows in one list diff --git a/src/aind_ephys_rig_qc/qc_figures.py b/src/aind_ephys_rig_qc/qc_figures.py index 7c1abe3..f66f094 100644 --- a/src/aind_ephys_rig_qc/qc_figures.py +++ b/src/aind_ephys_rig_qc/qc_figures.py @@ -23,7 +23,9 @@ ) -def plot_raw_data(data, sample_rate, stream_name): +def plot_raw_data( + data, start_frames, sample_rate, stream_name, chunk_size=1000 +): """ Plot a snippet of raw data as an image @@ -31,10 +33,14 @@ def plot_raw_data(data, sample_rate, stream_name): ---------- data : np.ndarray The data to plot (samples x channels) + start_frames : list + The starting frame for each chunk sample_rate : float - The sample rate of the data + The sampling rate of the data stream_name : str The name of the stream + chunk_size : int, default: 1000 + The size of each chunk Returns ------- @@ -43,18 +49,41 @@ def plot_raw_data(data, sample_rate, stream_name): """ fig = Figure(figsize=(10, 4)) - ax = fig.subplots() - ax.imshow(data[:1000, :].T, aspect="auto", cmap="RdBu") - ax.set_title(f"{stream_name} Raw Data") - ax.set_xlabel("Samples") - ax.set_ylabel("Channels") + num_chunks = len(start_frames) + end_frames = start_frames + chunk_size + + axs = fig.subplots(ncols=num_chunks) + + fig.suptitle(f"{stream_name} Raw Data") + for chunk_ind in range(num_chunks): + if num_chunks == 1: + ax = axs + else: + ax = axs[chunk_ind] + start_frame = int(start_frames[chunk_ind]) + end_frame = int(end_frames[chunk_ind]) + ax.imshow( + data[start_frame:end_frame, :].T, + aspect="auto", + cmap="RdBu", + origin="lower", + ) + ax.set_title(f"@ {np.round(start_frame / sample_rate, 2)}s") + ax.set_xlabel("Samples") + ax.set_ylabel("Channels") + fig.subplots_adjust(wspace=0.3) return fig def plot_power_spectrum( - directory, stream_name, num_chunks=3, chunk_size=10000 + data, + start_frames, + stream_name, + sample_rate, + chunk_size=10000, + log_xscale=False, ): """ Plot the power spectrum of the data @@ -63,10 +92,16 @@ def plot_power_spectrum( ---------- data : np.ndarray The data to plot (samples x channels) - sample_rate : float - The sample rate of the data + start_frames : list + The starting frame for each chunk stream_name : str The name of the stream + sample_rate : float + The sampling rate of the data + chunk_size : int, default: 10000 + The size of each chunk + log_xscale : bool, default: False + Whether to use a log scale for the x-axis Returns ------- @@ -74,45 +109,51 @@ def plot_power_spectrum( Figure object containing the plot """ fig = Figure(figsize=(10, 4)) - stream_names, _ = se.get_neo_streams("openephys", directory) - target_stream = [ - curr_stream_name - for curr_stream_name in stream_names - if stream_name in curr_stream_name - ][0] - recording = se.read_openephys( - folder_path=directory, - stream_name=target_stream, + num_chunks = len(start_frames) + axs = fig.subplots( + nrows=2, + ncols=num_chunks, + gridspec_kw={"height_ratios": [2, 1]}, + sharex=True, ) - ax = fig.subplots( - 2, num_chunks, gridspec_kw={"height_ratios": [2, 1]}, sharex=True - ) - sample_rate = recording.get_sampling_frequency() - subsets = si.get_random_data_chunks( - recording, - num_chunks_per_segment=num_chunks, - chunk_size=chunk_size, - concatenated=False, - ) + fig.suptitle(f"{stream_name} PSD") for chunk_ind in range(num_chunks): - subset = subsets[chunk_ind] + if num_chunks == 1: + ax1 = axs[0] + ax2 = axs[1] + else: + ax1 = axs[0, chunk_ind] + ax2 = axs[1, chunk_ind] + start_frame = int(start_frames[chunk_ind]) + end_frame = start_frame + chunk_size + subset = data[start_frame:end_frame] p_channel = [] for i in range(subset.shape[1]): f, p = welch(subset[:, i], fs=sample_rate) - ax[1, chunk_ind].plot(f, p) + ax2.plot(f, p, color="gray", alpha=0.5) p_channel.append(p) p_channel = np.array(p_channel) - extent = [f.min(), f.max(), subset.shape[1] - 1, 0] - ax[0, chunk_ind].imshow( - p_channel, extent=extent, aspect="auto", cmap="inferno" + p_mean = p_channel.mean(axis=0) + ax2.plot(f, p_mean, color="k", lw=1) + + extent = [f.min(), f.max(), 0, subset.shape[1] - 1] + ax1.imshow( + p_channel, + extent=extent, + aspect="auto", + cmap="inferno", + origin="lower", ) - ax[0, chunk_ind].set_ylabel("Channels") - ax[0, chunk_ind].set_title(f"{stream_name} PSD") - ax[1, chunk_ind].set_xlabel("Frequency") - ax[1, chunk_ind].set_ylabel("Power") + ax1.set_ylabel("Channels") + ax2.set_xlabel("Frequency") + ax2.set_ylabel("Power") + if log_xscale: + ax1.set_xscale("log") + ax2.set_xscale("log") + fig.subplots_adjust(wspace=0.3) return fig @@ -213,10 +254,14 @@ def plot_drift(diretory, stream_name): y_locs = recording.get_channel_locations()[:, 1] ylim = [np.min(y_locs), np.max(y_locs)] - fig_drift, axs_drift = plt.subplots( + fig = Figure(figsize=visualization_drift_params["figsize"]) + axs_drift = fig.subplots( ncols=recording.get_num_segments(), - figsize=visualization_drift_params["figsize"], ) + # for testing purposes + if recording.get_total_duration() < 3: + visualization_drift_params["n_skip"] = 1 + alpha = 0.5 for segment_index in range(recording.get_num_segments()): segment_mask = peaks["segment_index"] == segment_index x = peaks[segment_mask]["sample_index"] / recording.sampling_frequency @@ -243,9 +288,11 @@ def plot_drift(diretory, stream_name): ax_drift.spines["top"].set_visible(False) ax_drift.spines["right"].set_visible(False) - ax_drift.set_title(stream_name) + ax_drift.set_title( + f"Drift map: {stream_name}\n# detected peaks: {len(peaks)}" + ) - return fig_drift + return fig def plot_timealign(streams, overwrite=False): diff --git a/src/aind_ephys_rig_qc/temporal_alignment.py b/src/aind_ephys_rig_qc/temporal_alignment.py index 3a93cc7..1117194 100644 --- a/src/aind_ephys_rig_qc/temporal_alignment.py +++ b/src/aind_ephys_rig_qc/temporal_alignment.py @@ -251,7 +251,7 @@ def replace_original_timestamps( ) -def align_timestamps( # noqa +def align_timestamps( # noqa directory, original_timestamp_filename="original_timestamps.npy", pdf=None, @@ -290,13 +290,11 @@ def align_timestamps( # noqa main_stream_index = 0 for recordnode in session.recordnodes: - curr_record_node = os.path.basename(recordnode.directory).split( "Record Node " )[1] for recording in recordnode.recordings: - current_experiment_index = recording.experiment_index current_recording_index = recording.recording_index @@ -382,9 +380,9 @@ def align_timestamps( # noqa pdf.write( h=12, text=( - "Temporal alignment" + - f"of Record Node {curr_record_node}," - f"Experiment {current_experiment_index}," + "Temporal alignment " + f"of Record Node {curr_record_node} - " + f"Experiment {current_experiment_index} - " f"Recording {current_recording_index}" ), ) @@ -398,6 +396,7 @@ def align_timestamps( # noqa axes[2, 0].bar( sample_intervals_cat, sample_intervals_counts ) + axes[2, 1].axis("off") # save the timestamps for continuous in the main stream stream_folder_name = [ @@ -464,9 +463,7 @@ def align_timestamps( # noqa np.save(ts_filename_aligned_local_events, ts_main_events) for stream_idx, stream in enumerate(recording.continuous): - if stream_idx != main_stream_index: - stream_name = stream.metadata["stream_name"] print("Processing stream: ", stream_name) source_node_id = stream.metadata["source_node_id"] @@ -666,6 +663,8 @@ def align_timestamps( # noqa np.save(ts_filename_aligned_local_events, ts_events) fig.savefig(os.path.join(directory, "temporal_alignment.png")) + return fig + def align_timestamps_harp( directory, @@ -696,13 +695,11 @@ def align_timestamps_harp( ] for recordnode in session.recordnodes: - 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Merger -> Record Node", + "bit_volts": 0.0003051850944757462, + "units": "" + } + ] + } + ], + "events": [ + { + "folder_name": "Neuropix-PXI-100.ProbeA-AP/TTL/", + "channel_name": "Neuropixels PXI Sync", + "description": "Status of SMA sync line on PXI card", + "identifier": "neuropixels.sync", + "sample_rate": 30000.0, + "type": "int16", + "source_processor": "Neuropix-PXI", + "stream_name": "ProbeA-AP", + "initial_state": 0 + }, + { + "folder_name": "Neuropix-PXI-100.ProbeA-LFP/TTL/", + "channel_name": "Neuropixels PXI Sync", + "description": "Status of SMA sync line on PXI card", + "identifier": "neuropixels.sync", + "sample_rate": 2500.0, + "type": "int16", + "source_processor": "Neuropix-PXI", + "stream_name": "ProbeA-LFP", + "initial_state": 0 + }, + { + "folder_name": "NI-DAQmx-103.PXIe-6341/TTL/", + "channel_name": "PXIe-6341Digital Input Line", + "description": "Digital Line from a NIDAQ device containing 8 inputs", + "identifier": "identifier", + "sample_rate": 30000.0, + "type": "int16", + "source_processor": "NI-DAQmx", + "stream_name": "PXIe-6341", + "initial_state": 0 + }, + { + "folder_name": "MessageCenter/", + "channel_name": "Messages", + "description": "Broadcasts messages from the MessageCenter", + "identifier": "messagecenter.events", + "sample_rate": 30000.0, + "type": "string", + "source_processor": "Message Center", + "stream_name": "PXIe-6341" + } + ], + "spikes": [] + } \ No newline at end of file diff --git a/tests/resources/ephys_test_data/691894_2023-10-04_18-03-13_0.5s/Record Node 104/experiment1/recording1/sync_messages.txt b/tests/resources/ephys_test_data/691894_2023-10-04_18-03-13_0.5s/Record Node 104/experiment1/recording1/sync_messages.txt new file mode 100755 index 0000000..d407c5a --- /dev/null +++ b/tests/resources/ephys_test_data/691894_2023-10-04_18-03-13_0.5s/Record Node 104/experiment1/recording1/sync_messages.txt @@ -0,0 +1,4 @@ +Software Time (milliseconds since midnight Jan 1st 1970 UTC): 1696467793470 +Start Time for Neuropix-PXI (100) - ProbeA-AP @ 30000 Hz: 127572 +Start Time for Neuropix-PXI (100) - ProbeA-LFP @ 2500 Hz: 10631 +Start Time for NI-DAQmx (103) - PXIe-6341 @ 30000 Hz: 130001 diff --git a/tests/resources/ephys_test_data/691894_2023-10-04_18-03-13_0.5s/Record Node 104/settings.xml b/tests/resources/ephys_test_data/691894_2023-10-04_18-03-13_0.5s/Record Node 104/settings.xml new file mode 100755 index 0000000..4d55567 --- /dev/null +++ b/tests/resources/ephys_test_data/691894_2023-10-04_18-03-13_0.5s/Record Node 104/settings.xml @@ -0,0 +1,710 @@ + + + + + 0.6.6 + 8 + 4 Oct 2023 18:03:13 + Windows 10 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + + + + + + + + + + diff --git a/tests/test_generate_report.py b/tests/test_generate_report.py index cb66884..3cda2ae 100644 --- a/tests/test_generate_report.py +++ b/tests/test_generate_report.py @@ -2,19 +2,24 @@ import os import unittest +from pathlib import Path from unittest.mock import patch from matplotlib.figure import Figure from aind_ephys_rig_qc.generate_report import generate_qc_report from aind_ephys_rig_qc.qc_figures import plot_drift +test_folder = Path(__file__).parent / "resources" / "ephys_test_data" +test_dataset = "691894_2023-10-04_18-03-13_0.5s" + + class TestGenerateReport(unittest.TestCase): """Example Test Class""" @patch("builtins.input", return_value="y") def test_generate_report_overwriting(self, mock_input): """Check if output is pdf.""" - directory = "F:/npOptoRecordings/691894_2023-10-04_18-03-13" + directory = str(test_folder / test_dataset) report_name = "qc.pdf" generate_qc_report(directory, report_name) self.assertTrue(os.path.exists(os.path.join(directory, report_name))) @@ -22,14 +27,22 @@ def test_generate_report_overwriting(self, mock_input): @patch("builtins.input", return_value="n") def test_generate_report_not_overwrting(self, mock_input): """Check if output is pdf.""" - directory = "F:/npOptoRecordings/691894_2023-10-04_18-03-13" + directory = str(test_folder / test_dataset) report_name = "qc.pdf" generate_qc_report(directory, report_name) self.assertTrue(os.path.exists(os.path.join(directory, report_name))) + @patch("builtins.input", return_value="n") + def test_generate_report_num_chunks(self, mock_input): + """Check if output is pdf.""" + directory = str(test_folder / test_dataset) + report_name = "qc.pdf" + generate_qc_report(directory, report_name, num_chunks=1) + self.assertTrue(os.path.exists(os.path.join(directory, report_name))) + def test_drift(self): """Check if output is figure.""" - directory = "F:/npOptoRecordings/691894_2023-10-04_18-03-13" + directory = str(test_folder / test_dataset) stream_name = "ProbeA-AP" fig = plot_drift(directory, stream_name) self.assertIsInstance(fig, Figure)