Closed pauladkisson closed 4 months ago
_aggregate_results_arhmm_***
, whose mapping to experiment_type
can be found in the analysis_configuration.TEMPLATE
file in the code repo.
session_20210215162554-455929
Kai's Description:
Each session directory contains:
proc
, directory – Output of moseq-extract.depth.avi
– Raw, lossless-compressed depth frames.depth_ts.txt
– Timestamps for depth frames.feedback_ts.txt
– Timestamps at which the target syllable was detected, and a boolean denoting whether or not reinforcement was given.- A number of other intermediate processing files.
If the experiment included photometry, the session folder will contain:
ir.avi
– Infrared video containing LED flashes used to align video stream with photometry data.ir_ts.avi
– Timestamps for frames inir.avi
.tdt_data_*.dat
– Raw recording from the TDT.tdt_data_*.json
- Metadata from the TDT recording.
centroid_x_mm
, centroid_y_mm
, etc.) under scalars
uuid
, SessionName
, etc.) under metadata/acquisition
metadata/extraction/parameters
results_00.mp4
(Tx80x80)depth_ts.txt
= semi-regular timestamps for each frameConclusion: The .h5 file may effectively replace the kinematic data from the .parquet files since it is non-redundant and also comes w/ relevant MoSeq parameters. Might want to develop a MoSeqInterface in neuroconv like DeepLabCutInterface (depending on usage outside Datta Lab).
frames
from results_00.h5 all show different views of the same sessionConclusion: Can use VideoInterface from neuroconv (potentially w/ some modifications) for original depth.avi and ir.avi files. Can store .mp4 version as a separate file w/ a disclaimer that it should only be used for qualitative inspection.
Several metdata files throughout the directory
DepthDataType
, etc.) and session (SessionName
, etc.)Conclusion: Everything work keeping should be in the moseq .h5 file (I think).
Conclusion: Add raw photometry to FPInterface. Double check interpretation w/ Datta Lab.
In the photometry sessions,
photometry_df.parquet
and photometry_df_v2.parquet
have aligned photometry dataalignment_df.parquet
have alignment info including IR indices from tdt and videoConclusion: Could be useful for verifying output.
depth_ts.txt
, ir_ts.txt
= semi-regular (with some skips) timestampspredictions.txt
= syllable prediction from MoSeq (offline or online?)pc_scores.txt
= 10 PC values of depth used to train MoSeq --> ignore bc derivedConclusion: timestamp info should be in .h5 file, predictions need to be included in the MoSeqInterface, PCs can be ignored.
Notes for the new data shared over Google Drive
See #20 for description from Datta Lab.