10. LBM Step 3: Segmentation#
10.1. Segmentation: Extract neuronal locations and planar time-traces.#
Apply the constrained nonnegative matrix factorization (CNMF) source separation algorithm to extract initial estimates of neuronal spatial footprints and calcium traces.
Apply quality control metrics to evaluate the initial estimates, and narrow down to the final set of estimates.
11. Caiman docs on component eval#
https://caiman.readthedocs.io/en/latest/Getting_Started.html#component-evaluation
The quality of detected components is evaluated with three parameters:
Spatial footprint consistency (rval): The spatial footprint of the component is compared with the frames where this component is active. Other component’s signals are subtracted from these frames, and the resulting raw data is correlated against the spatial component. This ensures that the raw data at the spatial footprint aligns with the extracted trace.
Trace signal-noise-ratio (SNR): Peak SNR is calculated from strong calcium transients and the noise estimate.
CNN-based classifier (cnn): The shape of components is evaluated by a 4-layered convolutional neural network trained on a manually annotated dataset. The CNN assigns a value of 0-1 to each component depending on its resemblance to a neuronal soma.
Each parameter has a low threshold:
(rval_lowest (default -1), SNR_lowest (default 0.5), cnn_lowest (default 0.1))
and high threshold
(rval_thr (default 0.8), min_SNR (default 2.5), min_cnn_thr (default 0.9))
A component has to exceed ALL low thresholds as well as ONE high threshold to be accepted.
import os
from pathlib import Path
import logging
import mesmerize_core as mc
from mesmerize_viz import *
from mesmerize_core.caiman_extensions.cnmf import cnmf_cache
from caiman.source_extraction.cnmf import cnmf, params
from caiman.motion_correction import high_pass_filter_space
from caiman.summary_images import correlation_pnr
# os.environ['WGPU_BACKEND_TYPE']='OpenGL'
# os.environ["CONDA_PREFIX_1"] = ""
os.environ["QT_PLATFORM_PLUGIN"] = "xcb"
import napari
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import zarr
from ipywidgets import IntSlider, VBox
from sidecar import Sidecar
try:
import cv2
cv2.setNumThreads(0)
except():
pass
if os.name == "nt":
# disable the cache on windows, this will be automatic in a future version
cnmf_cache.set_maxsize(0)
pd.options.display.max_colwidth = 120
# set up logging
debug = True
logger = logging.getLogger("caiman")
logger.setLevel(logging.DEBUG)
handler = logging.StreamHandler()
log_format = logging.Formatter("%(relativeCreated)12d [%(filename)s:%(funcName)10s():%(lineno)s] [%(process)d] %(message)s")
handler.setFormatter(log_format)
logger.addHandler(handler)
logging.getLogger("caiman").setLevel(logging.WARNING)
12. Data Paths (TODO)#
The batch folder gets fairly cluttered with memmory mapped files. This needs some cleaning before putting into tree form.
/ raw_data_path/
└── session_01
├── animal_01
│ ├── pre_processed/
│ │ ├── plane_1/
│ │ ├── plane_1/
│ │ ├── plane_2/
│ │ └── plane_N/
│ └── batch_dataframe.pickle
For this demo set the caiman_data dir as the parent raw data path
12.1. Batch path, this is where caiman outputs will be organized, same as the previous step#
This can be anywhere, it does not need to be under the parent raw data path.
parent_path = Path().home() / "caiman_data" / "animal_01" / "session_01"
batch_path = parent_path / 'batch.pickle'
mc.set_parent_raw_data_path(str(parent_path))
# you could alos load the registration batch and
# save this patch in a new dataframe (saved to disk automatically)
try:
df = mc.load_batch(batch_path)
except (IsADirectoryError, FileNotFoundError):
df = mc.create_batch(batch_path)
df=df.caiman.reload_from_disk()
df
| algo | item_name | input_movie_path | params | outputs | added_time | ran_time | algo_duration | comments | uuid | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | mcorr | extracted_plane_1 | tiff\extracted_plane_1.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328_mean_projection.n... | 2024-09-26T11:56:54 | 2024-09-26T12:02:55 | 77.3 sec | None | b32f41bf-a9a5-4965-be7c-e6779e854328 |
| 1 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': a057e39e-a2df-41d3-8217-83c9cd7ffb6d\a057e39e-a2df-41d3-8217-83c9cd7ffb6d_mean_projection.n... | 2024-09-26T16:26:20 | 2024-09-26T16:28:48 | 143.18 sec | None | a057e39e-a2df-41d3-8217-83c9cd7ffb6d |
| 2 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 0d8d3234-eab7-4f90-9405-53a2ad7917dc\0d8d3234-eab7-4f90-9405-53a2ad7917dc_mean_projection.n... | 2024-10-01T12:09:56 | 2024-10-01T12:26:42 | 996.44 sec | None | 0d8d3234-eab7-4f90-9405-53a2ad7917dc |
| 3 | mcorr | plane_1 | tiff\extracted_plane_1.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': c220fb8a-cef9-4784-91a2-84f33d760b75\c220fb8a-cef9-4784-91a2-84f33d760b75_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:28:06 | 83.34 sec | None | c220fb8a-cef9-4784-91a2-84f33d760b75 |
| 4 | mcorr | plane_2 | tiff\extracted_plane_2.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': ecdbaa07-8893-4352-8658-19a8357306b8\ecdbaa07-8893-4352-8658-19a8357306b8_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:29:29 | 83.69 sec | None | ecdbaa07-8893-4352-8658-19a8357306b8 |
| 5 | mcorr | plane_3 | tiff\extracted_plane_3.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 48bad9bd-8a15-4d42-ae64-cb199ff498bc\48bad9bd-8a15-4d42-ae64-cb199ff498bc_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:30:53 | 83.81 sec | None | 48bad9bd-8a15-4d42-ae64-cb199ff498bc |
| 6 | mcorr | plane_4 | tiff\extracted_plane_4.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 29217cfc-8575-4c35-b8b0-2fb29a4cb416\29217cfc-8575-4c35-b8b0-2fb29a4cb416_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:32:17 | 82.93 sec | None | 29217cfc-8575-4c35-b8b0-2fb29a4cb416 |
| 7 | mcorr | plane_5 | tiff\extracted_plane_5.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': f9e87c87-913e-4027-a3bd-83c4c7182493\f9e87c87-913e-4027-a3bd-83c4c7182493_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:33:39 | 82.31 sec | None | f9e87c87-913e-4027-a3bd-83c4c7182493 |
| 8 | mcorr | plane_6 | tiff\extracted_plane_6.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': baf9fc6a-9159-46fd-a6b8-603d02c30c99\baf9fc6a-9159-46fd-a6b8-603d02c30c99_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:35:02 | 82.48 sec | None | baf9fc6a-9159-46fd-a6b8-603d02c30c99 |
| 9 | mcorr | plane_7 | tiff\extracted_plane_7.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 7afd6d4c-7787-4e02-8dfc-fd0ce578164d\7afd6d4c-7787-4e02-8dfc-fd0ce578164d_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:36:24 | 81.99 sec | None | 7afd6d4c-7787-4e02-8dfc-fd0ce578164d |
| 10 | mcorr | plane_8 | tiff\extracted_plane_8.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 28a3cd15-7671-4a5e-8744-9e8e73e35ee9\28a3cd15-7671-4a5e-8744-9e8e73e35ee9_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:37:48 | 83.8 sec | None | 28a3cd15-7671-4a5e-8744-9e8e73e35ee9 |
| 11 | mcorr | plane_9 | tiff\extracted_plane_9.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 379d8c22-52c6-4a6a-ae8e-69ccd1d5c5ed\379d8c22-52c6-4a6a-ae8e-69ccd1d5c5ed_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:39:11 | 83.03 sec | None | 379d8c22-52c6-4a6a-ae8e-69ccd1d5c5ed |
| 12 | mcorr | plane_10 | tiff\extracted_plane_10.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 679fe640-ee6c-480c-bc71-e941000b8851\679fe640-ee6c-480c-bc71-e941000b8851_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:40:33 | 82.51 sec | None | 679fe640-ee6c-480c-bc71-e941000b8851 |
| 13 | mcorr | plane_11 | tiff\extracted_plane_11.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': d5f2446a-0f42-472a-b969-735c7980b96b\d5f2446a-0f42-472a-b969-735c7980b96b_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:41:56 | 82.22 sec | None | d5f2446a-0f42-472a-b969-735c7980b96b |
| 14 | mcorr | plane_12 | tiff\extracted_plane_12.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 888fa033-522f-4fec-bbd6-607f93fffc11\888fa033-522f-4fec-bbd6-607f93fffc11_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:43:19 | 82.73 sec | None | 888fa033-522f-4fec-bbd6-607f93fffc11 |
| 15 | mcorr | plane_13 | tiff\extracted_plane_13.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 9c53c1bc-e865-4977-89da-1c1bff7d4d21\9c53c1bc-e865-4977-89da-1c1bff7d4d21_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:44:41 | 81.82 sec | None | 9c53c1bc-e865-4977-89da-1c1bff7d4d21 |
| 16 | mcorr | plane_14 | tiff\extracted_plane_14.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 6f3101c4-9792-497a-939f-5a4780848a0d\6f3101c4-9792-497a-939f-5a4780848a0d_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:46:03 | 82.3 sec | None | 6f3101c4-9792-497a-939f-5a4780848a0d |
| 17 | mcorr | plane_15 | tiff\extracted_plane_15.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 41ed61cb-4b3e-4117-9db6-e054b1d8c697\41ed61cb-4b3e-4117-9db6-e054b1d8c697_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:47:26 | 82.44 sec | None | 41ed61cb-4b3e-4117-9db6-e054b1d8c697 |
| 18 | mcorr | plane_16 | tiff\extracted_plane_16.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 625b34c3-eae3-4ad8-8015-5cc48122c7ec\625b34c3-eae3-4ad8-8015-5cc48122c7ec_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:48:48 | 82.0 sec | None | 625b34c3-eae3-4ad8-8015-5cc48122c7ec |
| 19 | mcorr | plane_17 | tiff\extracted_plane_17.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': e6a54884-a8a8-447b-be78-70957a62f161\e6a54884-a8a8-447b-be78-70957a62f161_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:50:11 | 83.41 sec | None | e6a54884-a8a8-447b-be78-70957a62f161 |
| 20 | mcorr | plane_18 | tiff\extracted_plane_18.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': c21edffc-96ae-4103-b0e7-9ae4af82a6a7\c21edffc-96ae-4103-b0e7-9ae4af82a6a7_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:51:33 | 81.7 sec | None | c21edffc-96ae-4103-b0e7-9ae4af82a6a7 |
| 21 | mcorr | plane_19 | tiff\extracted_plane_19.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': bbcf4810-f29e-4fde-a425-fa81a34e7c14\bbcf4810-f29e-4fde-a425-fa81a34e7c14_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:52:56 | 82.56 sec | None | bbcf4810-f29e-4fde-a425-fa81a34e7c14 |
| 22 | mcorr | plane_20 | tiff\extracted_plane_20.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 3f1399d9-951f-46b7-8424-8a5019984015\3f1399d9-951f-46b7-8424-8a5019984015_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:54:19 | 83.5 sec | None | 3f1399d9-951f-46b7-8424-8a5019984015 |
| 23 | mcorr | plane_21 | tiff\extracted_plane_21.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 666389a4-64ae-48e1-bcb0-381a48cff336\666389a4-64ae-48e1-bcb0-381a48cff336_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:55:42 | 82.36 sec | None | 666389a4-64ae-48e1-bcb0-381a48cff336 |
| 24 | mcorr | plane_22 | tiff\extracted_plane_22.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 09e7e82e-3365-409d-b961-33e51d022ba5\09e7e82e-3365-409d-b961-33e51d022ba5_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:57:06 | 83.45 sec | None | 09e7e82e-3365-409d-b961-33e51d022ba5 |
| 25 | mcorr | plane_23 | tiff\extracted_plane_23.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 450d0648-35c0-4528-b199-c448b4b3de7a\450d0648-35c0-4528-b199-c448b4b3de7a_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:58:28 | 82.03 sec | None | 450d0648-35c0-4528-b199-c448b4b3de7a |
| 26 | mcorr | plane_24 | tiff\extracted_plane_24.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 31b2befb-4833-4a1e-83ef-4c177244bd33\31b2befb-4833-4a1e-83ef-4c177244bd33_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:59:51 | 82.94 sec | None | 31b2befb-4833-4a1e-83ef-4c177244bd33 |
| 27 | mcorr | plane_25 | tiff\extracted_plane_25.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': b60dc323-4e70-4c7f-88f8-f7255e9252c5\b60dc323-4e70-4c7f-88f8-f7255e9252c5_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T14:01:15 | 83.64 sec | None | b60dc323-4e70-4c7f-88f8-f7255e9252c5 |
| 28 | mcorr | plane_26 | tiff\extracted_plane_26.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 6edd066c-6801-4c96-b71e-a34f3f446514\6edd066c-6801-4c96-b71e-a34f3f446514_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T14:02:36 | 80.91 sec | None | 6edd066c-6801-4c96-b71e-a34f3f446514 |
| 29 | mcorr | plane_27 | tiff\extracted_plane_27.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': df55466a-8e2e-44d7-93d6-bc2ba0c5ab01\df55466a-8e2e-44d7-93d6-bc2ba0c5ab01_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T14:03:58 | 81.79 sec | None | df55466a-8e2e-44d7-93d6-bc2ba0c5ab01 |
| 30 | mcorr | plane_28 | tiff\extracted_plane_28.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 2f2fa5da-3177-42ac-967c-240a46091e79\2f2fa5da-3177-42ac-967c-240a46091e79_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T14:05:20 | 82.38 sec | None | 2f2fa5da-3177-42ac-967c-240a46091e79 |
## TEMP
old_batch_path = parent_path / 'batch.pickle'
old_batch = mc.load_batch(old_batch_path)
mcorr_old = old_batch.iloc[0]
13. CNMF#
Perform CNMF using the mcorr output.
Similar to mcorr, put the CNMF params within the main key. The refit key will perform a second iteration, as shown in the caiman demo_pipeline.ipynb notebook.
13.1. Initial parameters#
In general in Caiman, estimators are first initialized with a set of parameters, and then they are fit against actual data in a separate step. In this section, we’ll define a parameters object that will subsequently be used to initialize our different estimators.
The parameters are divided into different categories. We will not discuss them in detail in this section, but will go over them when needed (and note that in this notebook we will mostly focus on CNMF and later steps):
fnames: List of paths to the file(s) to be analysed. Memmap and hdf5 result files will be saved in the same directory.
fr: Imaging frame rate in frames per second.
decay_time: Length of a typical transient in seconds. decay_time is an approximation of the time scale over which to expect a significant shift in the calcium signal during a transient. It defaults to 0.4, which is appropriate for fast indicators (GCaMP6f), slow indicators might use 1 or even more. However, decay_time does not have to precisely fit the data, approximations are enough.
p: Order of the autoregressive model. p = 0 turns deconvolution off. If transients in your data rise instantaneously, set p = 1 (occurs at low sample rate or slow indicator). If transients have visible rise time, set p = 2. If the wrong order is chosen, spikes are extracted unreliably.
nb: Number of global background components. This is a measure of the complexity of your background noise. Defaults to nb = 2, assuming a relatively homogeneous background. nb = 3 might fit for more complex noise, nb = 1 is usually too low. If nb is set too low, extracted traces appear too noisy, if nb is set too high, neuronal signal starts getting absorbed into the background reduction, resulting in reduced transients.
merge_thr: Merging threshold of components after initialization. If two components are correlated more than this value (e.g. when during initialization a neuron was split in two components), they are merged and treated as one.
rf: Half-size of the patches in pixels. Should be at least 3 to 4 times larger than the expected neuron size to capture the complete neuron and its local background. Larger patches lead to less parallelization.
stride: Overlap between patches in pixels. This should be roughly the neuron diameter. Larger overlap increases computational load, but yields better results during reconstruction/denoising of the data.
K : Number of (expected) components per patch. Adapt to rf and estimated component density.
gSig: Expected half-size of neurons in pixels [rows X columns]. CRUCIAL parameter for proper component detection.
method_init: Initialization method, depends mainly on the recording method. Use greedy_roi for 2p data, corr_pnr for 1p data, and sparse_nmf for dendritic/axonal data.
ssub/tsub: Spatial and temporal subsampling during initialization. Defaults to 1 (no compression). Can be set to 2 or even higher to save resources, but might impair detection/extraction quality.
Protein |
Max dF/F |
Half-rise time (ms) |
Time to peak (ms) |
Half-decay time (ms) |
|---|---|---|---|---|
jGCaMP7f (control) |
0.21±0.1 |
24.8±6.6 |
99.5±30.2 |
181.9±76.0 |
jGCaMP8f |
0.41±0.12 |
7.1±0.74 |
24.8±6.1 |
67.4±11.2 |
jGCaMP8m |
0.76±0.22 |
7.1±0.61 |
29.0±11.2 |
118.3±13.2 |
jGCaMP8s |
1.11±0.22 |
10.1±0.86 |
57.0±12.9 |
306.7±32.2 |
jGCaMP8.712* |
0.66±0.18 |
10.9±1.24 |
41.6±8.1 |
94.8±13.3 |
rf = 300
k = 150
# general dataset-dependent parameters
fr = 9.62 # imaging rate in frames per second
decay_time = 0.4 # length of a typical transient in seconds
dxy = (1., 1.) # spatial resolution in x and y in (um per pixel)
# CNMF parameters for source extraction and deconvolution
p = 2 # order of the autoregressive system (set p=2 if there is visible rise time in data)
gnb = 1 # number of global background components (set to 1 or 2)
merge_thr = 0.80 # merging threshold, max correlation allowed
bas_nonneg = True # enforce nonnegativity constraint on calcium traces (technically on baseline)
rf = 40 # half-size of the patches in pixels (patch width is rf*2 + 1)
stride_cnmf = 10 # amount of overlap between the patches in pixels (overlap is stride_cnmf+1)
# K = 780 # number of components per patch
gSig = np.array([7.5, 7.5]) # expected half-width of neurons in pixels (Gaussian kernel standard deviation)
# gSiz = None #2*gSig + 1 # Gaussian kernel width and hight
method_init = 'greedy_roi' # initialization method (if analyzing dendritic data see demo_dendritic.ipynb)
# method_init = '' # initialization method (if analyzing dendritic data see demo_dendritic.ipynb)
ssub = 1 # spatial subsampling during initialization
tsub = 1 # temporal subsampling during intialization
# parameters for component evaluation
min_SNR = 1.4 # signal to noise ratio for accepting a component
rval_thr = 0.80 # space correlation threshold for accepting a component
params_cnmf = {
'main': {
'fr': fr,
'dxy': dxy,
'decay_time': decay_time,
'p': p,
'nb': gnb,
'rf': rf,
'K': k,
'gSig': gSig,
# 'gSiz': gSiz,
'stride': stride_cnmf,
'method_init': method_init,
'rolling_sum': True,
'use_cnn': False,
'ssub': ssub,
'tsub': tsub,
'merge_thr': merge_thr,
'bas_nonneg': bas_nonneg,
'min_SNR': min_SNR,
'rval_thr': rval_thr,
},
'refit': True
}
14. Run CNMF#
The API is identical to running mcorr.
You can provide the mcorr item row to input_movie_path and it will resolve the path of the input movie from the entry in the DataFrame.
df = df.caiman.reload_from_disk()
df.caiman.add_item(
algo='cnmf',
input_movie_path=df.iloc[0],
params=params_cnmf,
item_name=f'cnmf_1',
)
df
| algo | item_name | input_movie_path | params | outputs | added_time | ran_time | algo_duration | comments | uuid | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | mcorr | extracted_plane_1 | tiff\extracted_plane_1.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328_mean_projection.n... | 2024-09-26T11:56:54 | 2024-09-26T12:02:55 | 77.3 sec | None | b32f41bf-a9a5-4965-be7c-e6779e854328 |
| 1 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': a057e39e-a2df-41d3-8217-83c9cd7ffb6d\a057e39e-a2df-41d3-8217-83c9cd7ffb6d_mean_projection.n... | 2024-09-26T16:26:20 | 2024-09-26T16:28:48 | 143.18 sec | None | a057e39e-a2df-41d3-8217-83c9cd7ffb6d |
| 2 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 9777376d-092c-43db-b14a-c9be1e142e5c\9777376d-092c-43db-b14a-c9be1e142e5c_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T14:41:40 | 161.74 sec | None | 9777376d-092c-43db-b14a-c9be1e142e5c |
| 3 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 88177367-8fbf-499b-940e-1fb9c331b499\88177367-8fbf-499b-940e-1fb9c331b499_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T14:44:32 | 172.71 sec | None | 88177367-8fbf-499b-940e-1fb9c331b499 |
| 4 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': a3bd82e1-618e-4279-8a67-ae3fe52a10d2\a3bd82e1-618e-4279-8a67-ae3fe52a10d2_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T14:47:31 | 179.02 sec | None | a3bd82e1-618e-4279-8a67-ae3fe52a10d2 |
| 5 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 03f6d9ca-c686-466e-9c8a-8076f787fc7b\03f6d9ca-c686-466e-9c8a-8076f787fc7b_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T14:50:13 | 161.89 sec | None | 03f6d9ca-c686-466e-9c8a-8076f787fc7b |
| 6 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 4bf6de48-8531-448f-b207-5f31299a12da\4bf6de48-8531-448f-b207-5f31299a12da_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T14:53:04 | 170.76 sec | None | 4bf6de48-8531-448f-b207-5f31299a12da |
| 7 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 3b9e8974-9d74-4f69-9370-ae731296203c\3b9e8974-9d74-4f69-9370-ae731296203c_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T14:56:01 | 177.33 sec | None | 3b9e8974-9d74-4f69-9370-ae731296203c |
| 8 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 705e6404-a883-4a19-9162-53a29aa62132\705e6404-a883-4a19-9162-53a29aa62132_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T14:59:31 | 209.84 sec | None | 705e6404-a883-4a19-9162-53a29aa62132 |
| 9 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 8bed5bd7-9261-46bb-bc17-091241f3b414\8bed5bd7-9261-46bb-bc17-091241f3b414_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:03:25 | 234.05 sec | None | 8bed5bd7-9261-46bb-bc17-091241f3b414 |
| 10 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 4cf62c5c-ed76-40ee-bf5c-6ed878aa924b\4cf62c5c-ed76-40ee-bf5c-6ed878aa924b_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:07:23 | 237.78 sec | None | 4cf62c5c-ed76-40ee-bf5c-6ed878aa924b |
| 11 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': d46488b0-5e55-4e4f-84dc-9bb14dc9db17\d46488b0-5e55-4e4f-84dc-9bb14dc9db17_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:10:50 | 207.15 sec | None | d46488b0-5e55-4e4f-84dc-9bb14dc9db17 |
| 12 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 5158332e-9c9a-4395-8044-70667b0ef869\5158332e-9c9a-4395-8044-70667b0ef869_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:14:44 | 234.05 sec | None | 5158332e-9c9a-4395-8044-70667b0ef869 |
| 13 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': f2d0cc26-ab86-4b8b-95ff-9aacf40c1c92\f2d0cc26-ab86-4b8b-95ff-9aacf40c1c92_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:18:44 | 239.34 sec | None | f2d0cc26-ab86-4b8b-95ff-9aacf40c1c92 |
| 14 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 683f31bc-fdb2-4d27-b860-2fd272e83172\683f31bc-fdb2-4d27-b860-2fd272e83172_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:23:16 | 272.6 sec | None | 683f31bc-fdb2-4d27-b860-2fd272e83172 |
| 15 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 05f36389-5168-47d5-9216-3feabe0a64f3\05f36389-5168-47d5-9216-3feabe0a64f3_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:28:07 | 290.92 sec | None | 05f36389-5168-47d5-9216-3feabe0a64f3 |
| 16 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 79beadbb-7140-4c23-b914-768a4b5b4a4d\79beadbb-7140-4c23-b914-768a4b5b4a4d_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:33:16 | 308.79 sec | None | 79beadbb-7140-4c23-b914-768a4b5b4a4d |
| 17 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': 926d6546-12c8-43ac-a033-9a4c97817b31\926d6546-12c8-43ac-a033-9a4c97817b31_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:37:50 | 273.53 sec | None | 926d6546-12c8-43ac-a033-9a4c97817b31 |
| 18 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': e1069d70-5735-47c4-8102-594a1f9f1702\e1069d70-5735-47c4-8102-594a1f9f1702_mean_projection.n... | 2024-09-30T14:36:58 | 2024-09-30T15:42:58 | 308.31 sec | None | e1069d70-5735-47c4-8102-594a1f9f1702 |
| 19 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | None | 2024-10-01T12:09:56 | None | None | None | 0d8d3234-eab7-4f90-9405-53a2ad7917dc |
df.iloc[-1].caiman.run()
Running 0d8d3234-eab7-4f90-9405-53a2ad7917dc with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_...
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T12:09:56
ran_time None
algo_duration None
comments None
uuid 0d8d3234-eab7-4f90-9405-53a2ad7917dc
Name: 19, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
80246405 [cluster.py:setup_cluster():225] [11836] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
80246405 [cluster.py:setup_cluster():225] [11836] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
80246514 [params.py:change_params():1151] [11836] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
80246514 [params.py:change_params():1151] [11836] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
making memmap
80257365 [cluster.py:setup_cluster():225] [11836] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
80257365 [cluster.py:setup_cluster():225] [11836] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
<mesmerize_core.caiman_extensions.common.DummyProcess at 0x21847a824a0>
14.1. Check for an error#
df = df.caiman.reload_from_disk()
df.iloc[-1].outputs['traceback']
df.iloc[-1].params
{'main': {'fr': 9.62,
'dxy': (1.0, 1.0),
'decay_time': 0.4,
'p': 2,
'nb': 1,
'rf': 40,
'K': 150,
'gSig': array([7.5, 7.5]),
'stride': 10,
'method_init': '',
'rolling_sum': True,
'use_cnn': False,
'ssub': 1,
'tsub': 1,
'merge_thr': 0.8,
'bas_nonneg': True,
'min_SNR': 1.4,
'rval_thr': 0.8},
'refit': True}
df = df.caiman.reload_from_disk()
df.iloc[-1].params = params_cnmf
df.iloc[-1].caiman.run()
Running 2f191e31-12a0-4636-a75e-f3ab50e04198 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_...
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs {'success': False, 'traceback': 'multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
Fil...
added_time 2024-10-01T11:59:30
ran_time 2024-10-01T12:04:35
algo_duration 23.77 sec
comments None
uuid 2f191e31-12a0-4636-a75e-f3ab50e04198
Name: 24, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': '', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
79988308 [cluster.py:setup_cluster():225] [11836] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
79988308 [cluster.py:setup_cluster():225] [11836] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
79988409 [params.py:change_params():1151] [11836] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
79988409 [params.py:change_params():1151] [11836] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
making memmap
79999702 [cluster.py:setup_cluster():225] [11836] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
79999702 [cluster.py:setup_cluster():225] [11836] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
<mesmerize_core.caiman_extensions.common.DummyProcess at 0x2183a703670>
15. CNMF outputs#
Similar to mcorr, you can use the mesmerize-core API to fetch the outputs.
API reference for mesmerize-CNMF API reference for caiman-CNMF
15.1. CNMF Object#
mcorr_movie = df.iloc[0].mcorr.get_output()
cnmf_model = df.iloc[-1].cnmf.get_output()
num_traces = cnmf_model.estimates.C
num_traces.shape
(8533, 1730)
gSig = 3
corr, pnr = correlation_pnr(mcorr_movie[::2], gSig=gSig, swap_dim=False)
16. Interactive Parameter Exploration#
from ipywidgets import Tab, Text, Button, VBox, interact_manual, interactive
@interact_manual(parent_path=str(parent_path), batch_path=str(batch_path))
def start_widget(parent_path, batch_path):
mc.set_parent_raw_data_path(parent_path)
df = mc.load_batch(batch_path)
tab = Tab()
# mcorr_container = df.mcorr.viz(start_index=0)
cnmf_container = df.cnmf.viz(start_index=19)
tab.children = [cnmf_container.show()]
tab.titles = ["cnmf"]
display(tab)
16.1. Temporal components, residuals#
index = -1 # the last item added
rcb = df.iloc[index].cnmf.get_rcb()
residuals = df.iloc[index].cnmf.get_residuals()
input_movie = df.iloc[index].caiman.get_input_movie()
# temporal components
temporal = df.iloc[index].cnmf.get_temporal()
temporal_good = df.iloc[index].cnmf.get_temporal("good")
temporal_bad = df.iloc[index].cnmf.get_temporal("bad")
temporal_with_residuals = df.iloc[index].cnmf.get_temporal(add_residuals=True)
correlation_image = df.iloc[-1].caiman.get_corr_image()
components_good = df.iloc[-1].cnmf.get_good_components()
components_bad = df.iloc[-1].cnmf.get_bad_components()
mean_img = df.iloc[-1].caiman.get_projection('mean')
std_img = df.iloc[-1].caiman.get_projection('std')
masks = df.iloc[-1].cnmf.get_masks()
print(f'Temporal Components (good/bad): {temporal_good.shape} / {temporal_bad.shape}')
print(f'Spatial Components (good/bad): {components_good.shape} / {components_bad.shape}')
good_masks = df.iloc[-1].cnmf.get_masks('good')
bad_masks = df.iloc[-1].cnmf.get_masks('bad')
fig, ax = plt.subplots(1,2, sharey=True)
ax[0].imshow(mean_img)
ax[1].imshow(correlation_image)
<matplotlib.image.AxesImage at 0x7f7acd8fc810>
cnmf_model.params
# dim order: txy[,z]
plt.plot(cnmf_model.estimates.C[3,:])
plt.show()
Many of the cnmf functions take a rich set of arguments
16.1.1. Get specific components#
df.iloc[-1].cnmf.get_temporal(np.array([1, 5, 9]))
array([[ 114.17567548, 1109.50506026, 1065.47162328, ..., 402.61607549,
348.24701629, 304.12614734],
[ 45.03461595, 45.03461595, 45.03461595, ..., 132.04335154,
126.66286509, 121.61509965],
[ 0. , 358.81892873, 391.91603586, ..., 270.95206299,
256.85871484, 243.49842054]])
16.1.2. add risiduals / contours#
# get temporal with the residuals, i.e. C + YrA
temporal_with_residuals = df.iloc[index].cnmf.get_temporal(add_residuals=True)
viewer = napari.Viewer()
viewer.add_image(temporal_with_residuals, name='traces+residuals')
# get contours
contours = df.iloc[-1].cnmf.get_contours()
len(contours)
2
viz_cnmf = df.cnmf.viz()
viz_cnmf.show()
Returns: (list of np.ndarray of contour coordinates, list of center of mass)
# get_contours() also takes arguments
contours_good = df.iloc[index].cnmf.get_contours("good")
len(contours_good[0]) # number of contours
swap_dim
# get the first contour using swap_dim=True (default)
swap_dim_true = df.iloc[index].cnmf.get_contours()[0][0]
# get the first contour with swap_dim=False
swap_dim_false = df.iloc[index].cnmf.get_contours(swap_dim=False)[0][0]
plt.plot(
swap_dim_true[:, 0],
swap_dim_true[:, 1],
label="swap_dim=True"
)
plt.plot(
swap_dim_false[:, 0],
swap_dim_false[:, 1],
label="swap_dim=False"
)
plt.legend()
# swap_dim swaps the x and y dims
plt.plot(
swap_dim_true[:, 0],
swap_dim_true[:, 1],
linewidth=30
)
plt.plot(
swap_dim_false[:, 1],
swap_dim_false[:, 0],
linewidth=10
)
17. Reconstructed movie - A * C#
18. Reconstructed background - b * f#
19. Residuals - Y - AC - bf#
Mesmerize-core provides these outputs as lazy arrays. This allows you to work with arrays that would otherwise be hundreds of gigabytes or terabytes in size.
rcm = df.iloc[index].cnmf.get_rcm()
rcm
20. Using LazyArrays#
rcm_accepted = df.iloc[index].cnmf.get_rcm("good")
rcm_rejected = df.iloc[index].cnmf.get_rcm("bad")
rcb = df.iloc[index].cnmf.get_rcb()
residuals = df.iloc[index].cnmf.get_residuals()
input_movie = df.iloc[index].caiman.get_input_movie()
rcb.shape
napari.view_image(rcb)
21. Parameter Gridsearch#
As shown for motion correction, the purpose of mesmerize-core is to perform parameter searches
# itertools.product makes it easy to loop through parameter variants
# basically, it's easier to read that deeply nested for loops
from copy import deepcopy
from itertools import product
# variants of several parameters
gSig_variants = [4, 6]
K_variants = [4, 8]
merge_thr_variants = [0.8, 0.95]
# always use deepcopy like before
new_params_cnmf = deepcopy(params_cnmf)
# create a parameter grid
parameter_grid = product(gSig_variants, K_variants, merge_thr_variants)
# a single for loop to go through all the various parameter combinations
for gSig, K, merge_thr in parameter_grid:
# deep copy params dict just like before
new_params_cnmf = deepcopy(new_params_cnmf)
new_params_cnmf["main"]["gSig"] = [gSig, gSig]
new_params_cnmf["main"]["K"] = K
new_params_cnmf["main"]["merge_thr"] = merge_thr
# add param combination variant to batch
df.caiman.add_item(
algo="cnmf",
item_name=df.iloc[1]["item_name"], # good mcorr item
input_movie_path=df.iloc[1],
params=new_params_cnmf
)
21.1. Pull contours / good components#
row_ix = 1
# get the contours and center of masses using mesmerize_core
contours, coms = df.iloc[row_ix].cnmf.get_contours(component_indices="good", swap_dim=False)
# get the signal-to-noise ratio of each "good" component to color components
snr_comps = df.iloc[row_ix].cnmf.get_output().estimates.SNR_comp
# get the good component_ixs
good_ixs = df.iloc[row_ix].cnmf.get_good_components()
# only get snr_comps of good_ixs
snr_comps = snr_comps[good_ixs]
np.log10(snr_comps)[:10]
View the diffs
df.caiman.get_params_diffs(algo="cnmf", item_name=df.iloc[-1]["item_name"])
| merge_thr | K | gSig | |
|---|---|---|---|
| 3 | 0.8 | 4 | (4, 4) |
| 4 | 0.95 | 4 | (4, 4) |
| 5 | 0.8 | 8 | (4, 4) |
| 6 | 0.95 | 8 | (4, 4) |
| 7 | 0.8 | 4 | (6, 6) |
| 8 | 0.95 | 4 | (6, 6) |
| 9 | 0.8 | 8 | (6, 6) |
| 10 | 0.95 | 8 | (6, 6) |
22. Run the cnmf batch items#
for i, row in df.iterrows():
if row["outputs"] is not None: # item has already been run
continue # skip
process = row.caiman.run()
# on Windows you MUST reload the batch dataframe after every iteration because it uses the `local` backend.
# this is unnecessary on Linux & Mac
# "DummyProcess" is used for local backend so this is automatic
if process.__class__.__name__ == "DummyProcess":
df = df.caiman.reload_from_disk()
Running 5cb543ec-5358-4b35-83cf-bfd19fa06a68 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name extracted_plane_1
input_movie_path b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_...
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':...
outputs None
added_time 2024-09-27T14:48:59
ran_time None
algo_duration None
comments None
uuid 5cb543ec-5358-4b35-83cf-bfd19fa06a68
Name: 3, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts': (6, 6), 'max_deviation_rigid': 3, 'pw_rigid': True, 'p': 2, 'nb': 1, 'rf': 40, 'gSig': (4, 4), 'gSiz': None, 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.5, 'rval_thr': 0.8, 'K': 4}, 'refit': True}
16876777 [cluster.py:setup_cluster():225] [16612] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
16876888 [params.py:change_params():1151] [16612] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
16880718 [paths.py:get_tempdir():46] [16612] Default temporary dir C:\Users\RBO\caiman_data\temp does not exist, creating
making memmap
16890809 [cluster.py:setup_cluster():225] [16612] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running df52a609-d986-4bc0-a0a2-526cbfda057d with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name extracted_plane_1
input_movie_path b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_...
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':...
outputs None
added_time 2024-09-27T14:48:59
ran_time None
algo_duration None
comments None
uuid df52a609-d986-4bc0-a0a2-526cbfda057d
Name: 4, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts': (6, 6), 'max_deviation_rigid': 3, 'pw_rigid': True, 'p': 2, 'nb': 1, 'rf': 40, 'gSig': (4, 4), 'gSiz': None, 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.95, 'bas_nonneg': True, 'min_SNR': 1.5, 'rval_thr': 0.8, 'K': 4}, 'refit': True}
16956929 [cluster.py:setup_cluster():225] [16612] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
16957033 [params.py:change_params():1151] [16612] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
making memmap
16967754 [cluster.py:setup_cluster():225] [16612] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running f38614e3-d632-434a-9721-290aceeb4907 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name extracted_plane_1
input_movie_path b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_...
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':...
outputs None
added_time 2024-09-27T14:48:59
ran_time None
algo_duration None
comments None
uuid f38614e3-d632-434a-9721-290aceeb4907
Name: 5, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts': (6, 6), 'max_deviation_rigid': 3, 'pw_rigid': True, 'p': 2, 'nb': 1, 'rf': 40, 'gSig': (4, 4), 'gSiz': None, 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.5, 'rval_thr': 0.8, 'K': 8}, 'refit': True}
17032862 [cluster.py:setup_cluster():225] [16612] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
17032966 [params.py:change_params():1151] [16612] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
making memmap
17043554 [cluster.py:setup_cluster():225] [16612] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
23. Load outputs#
df = df.caiman.reload_from_disk()
df
| algo | item_name | input_movie_path | params | outputs | added_time | ran_time | algo_duration | comments | uuid | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | mcorr | extracted_plane_1 | tiff\extracted_plane_1.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328_mean_projection.n... | 2024-09-26T11:56:54 | 2024-09-26T12:02:55 | 77.3 sec | None | b32f41bf-a9a5-4965-be7c-e6779e854328 |
| 1 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'strides': (48, 48), 'overlaps': (24, 24), 'max_shifts':... | {'mean-projection-path': a057e39e-a2df-41d3-8217-83c9cd7ffb6d\a057e39e-a2df-41d3-8217-83c9cd7ffb6d_mean_projection.n... | 2024-09-26T16:26:20 | 2024-09-26T16:28:48 | 143.18 sec | None | a057e39e-a2df-41d3-8217-83c9cd7ffb6d |
| 2 | cnmf | cnmf_1 | b32f41bf-a9a5-4965-be7c-e6779e854328\b32f41bf-a9a5-4965-be7c-e6779e854328-extracted_plane_1_els__d1_583_d2_536_d3_1_... | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 0d8d3234-eab7-4f90-9405-53a2ad7917dc\0d8d3234-eab7-4f90-9405-53a2ad7917dc_mean_projection.n... | 2024-10-01T12:09:56 | 2024-10-01T12:26:42 | 996.44 sec | None | 0d8d3234-eab7-4f90-9405-53a2ad7917dc |
| 3 | mcorr | plane_1 | tiff\extracted_plane_1.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': c220fb8a-cef9-4784-91a2-84f33d760b75\c220fb8a-cef9-4784-91a2-84f33d760b75_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:28:06 | 83.34 sec | None | c220fb8a-cef9-4784-91a2-84f33d760b75 |
| 4 | mcorr | plane_2 | tiff\extracted_plane_2.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': ecdbaa07-8893-4352-8658-19a8357306b8\ecdbaa07-8893-4352-8658-19a8357306b8_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:29:29 | 83.69 sec | None | ecdbaa07-8893-4352-8658-19a8357306b8 |
| 5 | mcorr | plane_3 | tiff\extracted_plane_3.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 48bad9bd-8a15-4d42-ae64-cb199ff498bc\48bad9bd-8a15-4d42-ae64-cb199ff498bc_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:30:53 | 83.81 sec | None | 48bad9bd-8a15-4d42-ae64-cb199ff498bc |
| 6 | mcorr | plane_4 | tiff\extracted_plane_4.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 29217cfc-8575-4c35-b8b0-2fb29a4cb416\29217cfc-8575-4c35-b8b0-2fb29a4cb416_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:32:17 | 82.93 sec | None | 29217cfc-8575-4c35-b8b0-2fb29a4cb416 |
| 7 | mcorr | plane_5 | tiff\extracted_plane_5.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': f9e87c87-913e-4027-a3bd-83c4c7182493\f9e87c87-913e-4027-a3bd-83c4c7182493_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:33:39 | 82.31 sec | None | f9e87c87-913e-4027-a3bd-83c4c7182493 |
| 8 | mcorr | plane_6 | tiff\extracted_plane_6.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': baf9fc6a-9159-46fd-a6b8-603d02c30c99\baf9fc6a-9159-46fd-a6b8-603d02c30c99_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:35:02 | 82.48 sec | None | baf9fc6a-9159-46fd-a6b8-603d02c30c99 |
| 9 | mcorr | plane_7 | tiff\extracted_plane_7.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 7afd6d4c-7787-4e02-8dfc-fd0ce578164d\7afd6d4c-7787-4e02-8dfc-fd0ce578164d_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:36:24 | 81.99 sec | None | 7afd6d4c-7787-4e02-8dfc-fd0ce578164d |
| 10 | mcorr | plane_8 | tiff\extracted_plane_8.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 28a3cd15-7671-4a5e-8744-9e8e73e35ee9\28a3cd15-7671-4a5e-8744-9e8e73e35ee9_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:37:48 | 83.8 sec | None | 28a3cd15-7671-4a5e-8744-9e8e73e35ee9 |
| 11 | mcorr | plane_9 | tiff\extracted_plane_9.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 379d8c22-52c6-4a6a-ae8e-69ccd1d5c5ed\379d8c22-52c6-4a6a-ae8e-69ccd1d5c5ed_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:39:11 | 83.03 sec | None | 379d8c22-52c6-4a6a-ae8e-69ccd1d5c5ed |
| 12 | mcorr | plane_10 | tiff\extracted_plane_10.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 679fe640-ee6c-480c-bc71-e941000b8851\679fe640-ee6c-480c-bc71-e941000b8851_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:40:33 | 82.51 sec | None | 679fe640-ee6c-480c-bc71-e941000b8851 |
| 13 | mcorr | plane_11 | tiff\extracted_plane_11.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': d5f2446a-0f42-472a-b969-735c7980b96b\d5f2446a-0f42-472a-b969-735c7980b96b_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:41:56 | 82.22 sec | None | d5f2446a-0f42-472a-b969-735c7980b96b |
| 14 | mcorr | plane_12 | tiff\extracted_plane_12.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 888fa033-522f-4fec-bbd6-607f93fffc11\888fa033-522f-4fec-bbd6-607f93fffc11_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:43:19 | 82.73 sec | None | 888fa033-522f-4fec-bbd6-607f93fffc11 |
| 15 | mcorr | plane_13 | tiff\extracted_plane_13.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 9c53c1bc-e865-4977-89da-1c1bff7d4d21\9c53c1bc-e865-4977-89da-1c1bff7d4d21_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:44:41 | 81.82 sec | None | 9c53c1bc-e865-4977-89da-1c1bff7d4d21 |
| 16 | mcorr | plane_14 | tiff\extracted_plane_14.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 6f3101c4-9792-497a-939f-5a4780848a0d\6f3101c4-9792-497a-939f-5a4780848a0d_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:46:03 | 82.3 sec | None | 6f3101c4-9792-497a-939f-5a4780848a0d |
| 17 | mcorr | plane_15 | tiff\extracted_plane_15.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 41ed61cb-4b3e-4117-9db6-e054b1d8c697\41ed61cb-4b3e-4117-9db6-e054b1d8c697_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:47:26 | 82.44 sec | None | 41ed61cb-4b3e-4117-9db6-e054b1d8c697 |
| 18 | mcorr | plane_16 | tiff\extracted_plane_16.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 625b34c3-eae3-4ad8-8015-5cc48122c7ec\625b34c3-eae3-4ad8-8015-5cc48122c7ec_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:48:48 | 82.0 sec | None | 625b34c3-eae3-4ad8-8015-5cc48122c7ec |
| 19 | mcorr | plane_17 | tiff\extracted_plane_17.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': e6a54884-a8a8-447b-be78-70957a62f161\e6a54884-a8a8-447b-be78-70957a62f161_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:50:11 | 83.41 sec | None | e6a54884-a8a8-447b-be78-70957a62f161 |
| 20 | mcorr | plane_18 | tiff\extracted_plane_18.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': c21edffc-96ae-4103-b0e7-9ae4af82a6a7\c21edffc-96ae-4103-b0e7-9ae4af82a6a7_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:51:33 | 81.7 sec | None | c21edffc-96ae-4103-b0e7-9ae4af82a6a7 |
| 21 | mcorr | plane_19 | tiff\extracted_plane_19.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': bbcf4810-f29e-4fde-a425-fa81a34e7c14\bbcf4810-f29e-4fde-a425-fa81a34e7c14_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:52:56 | 82.56 sec | None | bbcf4810-f29e-4fde-a425-fa81a34e7c14 |
| 22 | mcorr | plane_20 | tiff\extracted_plane_20.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 3f1399d9-951f-46b7-8424-8a5019984015\3f1399d9-951f-46b7-8424-8a5019984015_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:54:19 | 83.5 sec | None | 3f1399d9-951f-46b7-8424-8a5019984015 |
| 23 | mcorr | plane_21 | tiff\extracted_plane_21.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 666389a4-64ae-48e1-bcb0-381a48cff336\666389a4-64ae-48e1-bcb0-381a48cff336_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:55:42 | 82.36 sec | None | 666389a4-64ae-48e1-bcb0-381a48cff336 |
| 24 | mcorr | plane_22 | tiff\extracted_plane_22.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 09e7e82e-3365-409d-b961-33e51d022ba5\09e7e82e-3365-409d-b961-33e51d022ba5_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:57:06 | 83.45 sec | None | 09e7e82e-3365-409d-b961-33e51d022ba5 |
| 25 | mcorr | plane_23 | tiff\extracted_plane_23.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 450d0648-35c0-4528-b199-c448b4b3de7a\450d0648-35c0-4528-b199-c448b4b3de7a_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:58:28 | 82.03 sec | None | 450d0648-35c0-4528-b199-c448b4b3de7a |
| 26 | mcorr | plane_24 | tiff\extracted_plane_24.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 31b2befb-4833-4a1e-83ef-4c177244bd33\31b2befb-4833-4a1e-83ef-4c177244bd33_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T13:59:51 | 82.94 sec | None | 31b2befb-4833-4a1e-83ef-4c177244bd33 |
| 27 | mcorr | plane_25 | tiff\extracted_plane_25.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': b60dc323-4e70-4c7f-88f8-f7255e9252c5\b60dc323-4e70-4c7f-88f8-f7255e9252c5_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T14:01:15 | 83.64 sec | None | b60dc323-4e70-4c7f-88f8-f7255e9252c5 |
| 28 | mcorr | plane_26 | tiff\extracted_plane_26.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 6edd066c-6801-4c96-b71e-a34f3f446514\6edd066c-6801-4c96-b71e-a34f3f446514_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T14:02:36 | 80.91 sec | None | 6edd066c-6801-4c96-b71e-a34f3f446514 |
| 29 | mcorr | plane_27 | tiff\extracted_plane_27.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': df55466a-8e2e-44d7-93d6-bc2ba0c5ab01\df55466a-8e2e-44d7-93d6-bc2ba0c5ab01_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T14:03:58 | 81.79 sec | None | df55466a-8e2e-44d7-93d6-bc2ba0c5ab01 |
| 30 | mcorr | plane_28 | tiff\extracted_plane_28.tif | {'main': {'var_name_hdf5': 'mov', 'max_shifts': (10, 10), 'strides': (48, 48), 'overlaps': (24, 24), 'max_deviation_... | {'mean-projection-path': 2f2fa5da-3177-42ac-967c-240a46091e79\2f2fa5da-3177-42ac-967c-240a46091e79_mean_projection.n... | 2024-10-01T13:24:33 | 2024-10-01T14:05:20 | 82.38 sec | None | 2f2fa5da-3177-42ac-967c-240a46091e79 |
cnmf_params_all = df.iloc[2].params
cnmf_params_all
{'main': {'fr': 9.62,
'dxy': (1.0, 1.0),
'decay_time': 0.4,
'p': 2,
'nb': 1,
'rf': 40,
'K': 150,
'gSig': array([7.5, 7.5]),
'stride': 10,
'method_init': 'greedy_roi',
'rolling_sum': True,
'use_cnn': False,
'ssub': 1,
'tsub': 1,
'merge_thr': 0.8,
'bas_nonneg': True,
'min_SNR': 1.4,
'rval_thr': 0.8},
'refit': True}
cnmf_batch = parent_path / 'results'
cnmf_batch.mkdir(exist_ok=True, parents=True)
cnmf_batch = mc.load_batch(cnmf_batch / 'cnmf_batch.pickle')
cnmf_batch
| algo | item_name | input_movie_path | params | outputs | added_time | ran_time | algo_duration | comments | uuid | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | cnmf | cnmf_1 | tiff\extracted_plane_1.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': faeb27e8-40b9-4e5a-ad8c-b9cc73c03635\faeb27e8-40b9-4e5a-ad8c-b9cc73c03635_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T16:54:16 | 946.94 sec | None | faeb27e8-40b9-4e5a-ad8c-b9cc73c03635 |
| 1 | cnmf | cnmf_1 | tiff\extracted_plane_2.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 89b676c7-9480-47d7-b190-e4bbc2a5decc\89b676c7-9480-47d7-b190-e4bbc2a5decc_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T17:10:06 | 949.6 sec | None | 89b676c7-9480-47d7-b190-e4bbc2a5decc |
| 2 | cnmf | cnmf_1 | tiff\extracted_plane_3.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': f03ead24-ab13-48e7-87c0-27d5940a7c91\f03ead24-ab13-48e7-87c0-27d5940a7c91_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T17:28:57 | 1131.04 sec | None | f03ead24-ab13-48e7-87c0-27d5940a7c91 |
| 3 | cnmf | cnmf_1 | tiff\extracted_plane_4.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 585a0fc2-40d4-45f2-badf-ba13d5cc77a6\585a0fc2-40d4-45f2-badf-ba13d5cc77a6_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T17:51:18 | 1340.32 sec | None | 585a0fc2-40d4-45f2-badf-ba13d5cc77a6 |
| 4 | cnmf | cnmf_1 | tiff\extracted_plane_5.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 544c2a52-0b90-4b74-baae-b2ca913c7c2a\544c2a52-0b90-4b74-baae-b2ca913c7c2a_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T18:08:22 | 1024.35 sec | None | 544c2a52-0b90-4b74-baae-b2ca913c7c2a |
| 5 | cnmf | cnmf_1 | tiff\extracted_plane_6.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': d6c3f33c-2b90-4c6d-a4ad-f237dae5f73b\d6c3f33c-2b90-4c6d-a4ad-f237dae5f73b_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T18:24:00 | 937.73 sec | None | d6c3f33c-2b90-4c6d-a4ad-f237dae5f73b |
| 6 | cnmf | cnmf_1 | tiff\extracted_plane_7.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': ca269a68-06d0-4f96-b508-87160fdf37ab\ca269a68-06d0-4f96-b508-87160fdf37ab_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T18:39:39 | 939.58 sec | None | ca269a68-06d0-4f96-b508-87160fdf37ab |
| 7 | cnmf | cnmf_1 | tiff\extracted_plane_8.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': a9cb2077-073a-4552-9669-e53ba0c96803\a9cb2077-073a-4552-9669-e53ba0c96803_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T18:55:09 | 929.57 sec | None | a9cb2077-073a-4552-9669-e53ba0c96803 |
| 8 | cnmf | cnmf_1 | tiff\extracted_plane_9.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': c0205f69-ccb6-4304-9cee-18af09d11663\c0205f69-ccb6-4304-9cee-18af09d11663_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T19:10:49 | 940.35 sec | None | c0205f69-ccb6-4304-9cee-18af09d11663 |
| 9 | cnmf | cnmf_1 | tiff\extracted_plane_10.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 1fac642d-6cef-4a68-9415-737213b4462d\1fac642d-6cef-4a68-9415-737213b4462d_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T19:28:15 | 1045.02 sec | None | 1fac642d-6cef-4a68-9415-737213b4462d |
| 10 | cnmf | cnmf_1 | tiff\extracted_plane_11.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 97569a0f-b5c4-41b5-9268-b4ddeda9d740\97569a0f-b5c4-41b5-9268-b4ddeda9d740_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T19:45:46 | 1051.62 sec | None | 97569a0f-b5c4-41b5-9268-b4ddeda9d740 |
| 11 | cnmf | cnmf_1 | tiff\extracted_plane_12.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': c2d0864d-1313-4ded-8b7f-4a7f02947b2d\c2d0864d-1313-4ded-8b7f-4a7f02947b2d_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T20:01:40 | 953.4 sec | None | c2d0864d-1313-4ded-8b7f-4a7f02947b2d |
| 12 | cnmf | cnmf_1 | tiff\extracted_plane_13.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 8301c084-fe7c-4e84-b8d7-db6fcc8893ed\8301c084-fe7c-4e84-b8d7-db6fcc8893ed_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T20:17:40 | 960.7 sec | None | 8301c084-fe7c-4e84-b8d7-db6fcc8893ed |
| 13 | cnmf | cnmf_1 | tiff\extracted_plane_14.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 1eabd9f9-1a57-4c08-a830-9276371c00a9\1eabd9f9-1a57-4c08-a830-9276371c00a9_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T20:33:51 | 970.13 sec | None | 1eabd9f9-1a57-4c08-a830-9276371c00a9 |
| 14 | cnmf | cnmf_1 | tiff\extracted_plane_15.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 25be7a5b-dd16-42cd-bd4a-1312b4c6e791\25be7a5b-dd16-42cd-bd4a-1312b4c6e791_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T20:52:06 | 1095.19 sec | None | 25be7a5b-dd16-42cd-bd4a-1312b4c6e791 |
| 15 | cnmf | cnmf_1 | tiff\extracted_plane_16.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': f87dc096-6bb2-40dd-8dff-20f1362423b0\f87dc096-6bb2-40dd-8dff-20f1362423b0_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T21:08:23 | 977.02 sec | None | f87dc096-6bb2-40dd-8dff-20f1362423b0 |
| 16 | cnmf | cnmf_1 | tiff\extracted_plane_17.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 0e6f8223-3002-4430-a987-d83a6d7c7bd8\0e6f8223-3002-4430-a987-d83a6d7c7bd8_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T21:28:21 | 1197.8 sec | None | 0e6f8223-3002-4430-a987-d83a6d7c7bd8 |
| 17 | cnmf | cnmf_1 | tiff\extracted_plane_18.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 52ab80e3-880f-4ae5-bd38-711c0138ebe2\52ab80e3-880f-4ae5-bd38-711c0138ebe2_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T21:46:45 | 1104.12 sec | None | 52ab80e3-880f-4ae5-bd38-711c0138ebe2 |
| 18 | cnmf | cnmf_1 | tiff\extracted_plane_19.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 65c8dfa4-2a65-4618-8240-7f08fccce4ad\65c8dfa4-2a65-4618-8240-7f08fccce4ad_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T22:05:32 | 1126.88 sec | None | 65c8dfa4-2a65-4618-8240-7f08fccce4ad |
| 19 | cnmf | cnmf_1 | tiff\extracted_plane_20.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 473b088b-1b8e-4ecb-97e2-75eb299851b2\473b088b-1b8e-4ecb-97e2-75eb299851b2_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T22:23:00 | 1048.28 sec | None | 473b088b-1b8e-4ecb-97e2-75eb299851b2 |
| 20 | cnmf | cnmf_1 | tiff\extracted_plane_21.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 60d2fc66-20a9-4f00-b6f7-b9e80440efe7\60d2fc66-20a9-4f00-b6f7-b9e80440efe7_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T22:41:10 | 1090.04 sec | None | 60d2fc66-20a9-4f00-b6f7-b9e80440efe7 |
| 21 | cnmf | cnmf_1 | tiff\extracted_plane_22.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 8926526d-cc18-47e2-b599-1496b2c9f03e\8926526d-cc18-47e2-b599-1496b2c9f03e_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T23:01:26 | 1215.23 sec | None | 8926526d-cc18-47e2-b599-1496b2c9f03e |
| 22 | cnmf | cnmf_1 | tiff\extracted_plane_23.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': f2b1c811-e02a-4058-a15b-861ee1128793\f2b1c811-e02a-4058-a15b-861ee1128793_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T23:20:00 | 1114.08 sec | None | f2b1c811-e02a-4058-a15b-861ee1128793 |
| 23 | cnmf | cnmf_1 | tiff\extracted_plane_24.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 5c9bd42e-fb07-43f0-a18d-0b9e516db4ec\5c9bd42e-fb07-43f0-a18d-0b9e516db4ec_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T23:38:35 | 1114.86 sec | None | 5c9bd42e-fb07-43f0-a18d-0b9e516db4ec |
| 24 | cnmf | cnmf_1 | tiff\extracted_plane_25.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 84004c56-81c1-474b-ab38-327fbf79bf8c\84004c56-81c1-474b-ab38-327fbf79bf8c_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-01T23:57:28 | 1132.94 sec | None | 84004c56-81c1-474b-ab38-327fbf79bf8c |
| 25 | cnmf | cnmf_1 | tiff\extracted_plane_26.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 23521021-6791-4d41-855d-779eefce6840\23521021-6791-4d41-855d-779eefce6840_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-02T00:14:28 | 1019.75 sec | None | 23521021-6791-4d41-855d-779eefce6840 |
| 26 | cnmf | cnmf_1 | tiff\extracted_plane_27.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 07907a0b-b138-41e3-99a7-f7153738a640\07907a0b-b138-41e3-99a7-f7153738a640_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-02T00:34:07 | 1179.51 sec | None | 07907a0b-b138-41e3-99a7-f7153738a640 |
| 27 | cnmf | cnmf_1 | tiff\extracted_plane_28.tif | {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],... | {'mean-projection-path': 8b7cbfb4-7c62-4780-a90c-5275cbe1f318\8b7cbfb4-7c62-4780-a90c-5275cbe1f318_mean_projection.n... | 2024-10-01T16:34:44 | 2024-10-02T00:49:55 | 947.96 sec | None | 8b7cbfb4-7c62-4780-a90c-5275cbe1f318 |
for i in range(1, 31):
item_name_str = df.iloc[i]['item_name']
if 'plane' in item_name_str:
filename = f'extracted_{item_name_str}.tif'
filepath = parent_path / 'tiff' / filename
# find output that matches item_name_str
cnmf_batch.caiman.add_item(
algo='cnmf',
input_movie_path=filepath,
params=cnmf_params_all,
item_name=f'cnmf_1',
)
cnmf_batch = cnmf_batch.caiman.reload_from_disk()
cnmf_batch
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[1], line 1
----> 1 cnmf_batch = cnmf_batch.caiman.reload_from_disk()
2 cnmf_batch
NameError: name 'cnmf_batch' is not defined
for i, row in cnmf_batch.iterrows():
if row["outputs"] is not None:
continue
process = row.caiman.run()
# on Windows you MUST reload the batch dataframe after every iteration because it uses the `local` backend.
# this is unnecessary on Linux & Mac
# "DummyProcess" is used for local backend so this is automatic
if process.__class__.__name__ == "DummyProcess":
df = cnmf_batch.caiman.reload_from_disk()
Running faeb27e8-40b9-4e5a-ad8c-b9cc73c03635 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_1.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid faeb27e8-40b9-4e5a-ad8c-b9cc73c03635
Name: 0, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
12963988 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
12964133 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_1.tif'> shaped series axes do not match shape
making memmap
12977206 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
13904154 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [8875]. Changing their value to -1.
Running 89b676c7-9480-47d7-b190-e4bbc2a5decc with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_2.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 89b676c7-9480-47d7-b190-e4bbc2a5decc
Name: 1, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
13910972 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
13911069 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_2.tif'> shaped series axes do not match shape
making memmap
13924222 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running f03ead24-ab13-48e7-87c0-27d5940a7c91 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_3.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid f03ead24-ab13-48e7-87c0-27d5940a7c91
Name: 2, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
14860679 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
14860787 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_3.tif'> shaped series axes do not match shape
making memmap
14873610 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 585a0fc2-40d4-45f2-badf-ba13d5cc77a6 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_4.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 585a0fc2-40d4-45f2-badf-ba13d5cc77a6
Name: 3, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
15991797 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
15991909 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_4.tif'> shaped series axes do not match shape
making memmap
16004684 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 544c2a52-0b90-4b74-baae-b2ca913c7c2a with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_5.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 544c2a52-0b90-4b74-baae-b2ca913c7c2a
Name: 4, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
17332164 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
17332271 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_5.tif'> shaped series axes do not match shape
making memmap
17344985 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
18349840 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [8732]. Changing their value to -1.
Running d6c3f33c-2b90-4c6d-a4ad-f237dae5f73b with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_6.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid d6c3f33c-2b90-4c6d-a4ad-f237dae5f73b
Name: 5, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
18356589 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
18356697 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_6.tif'> shaped series axes do not match shape
making memmap
18369597 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
19287618 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [8801]. Changing their value to -1.
Running ca269a68-06d0-4f96-b508-87160fdf37ab with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_7.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid ca269a68-06d0-4f96-b508-87160fdf37ab
Name: 6, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
19294349 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
19294490 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_7.tif'> shaped series axes do not match shape
making memmap
19307355 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
20226922 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [8772]. Changing their value to -1.
Running a9cb2077-073a-4552-9669-e53ba0c96803 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_8.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid a9cb2077-073a-4552-9669-e53ba0c96803
Name: 7, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
20233980 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
20234094 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_8.tif'> shaped series axes do not match shape
making memmap
20246734 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
21156660 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [8804]. Changing their value to -1.
Running c0205f69-ccb6-4304-9cee-18af09d11663 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_9.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid c0205f69-ccb6-4304-9cee-18af09d11663
Name: 8, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
21163606 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
21163705 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_9.tif'> shaped series axes do not match shape
making memmap
21176421 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
22096999 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [8836]. Changing their value to -1.
Running 1fac642d-6cef-4a68-9415-737213b4462d with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_10.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 1fac642d-6cef-4a68-9415-737213b4462d
Name: 9, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
22104019 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
22104119 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_10.tif'> shaped series axes do not match shape
making memmap
22116719 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 97569a0f-b5c4-41b5-9268-b4ddeda9d740 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_11.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 97569a0f-b5c4-41b5-9268-b4ddeda9d740
Name: 10, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
23149086 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
23149198 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_11.tif'> shaped series axes do not match shape
making memmap
23161891 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running c2d0864d-1313-4ded-8b7f-4a7f02947b2d with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_12.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid c2d0864d-1313-4ded-8b7f-4a7f02947b2d
Name: 11, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
24200760 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
24200873 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_12.tif'> shaped series axes do not match shape
making memmap
24213260 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 8301c084-fe7c-4e84-b8d7-db6fcc8893ed with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_13.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 8301c084-fe7c-4e84-b8d7-db6fcc8893ed
Name: 12, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
25154225 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
25154351 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_13.tif'> shaped series axes do not match shape
making memmap
25166700 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 1eabd9f9-1a57-4c08-a830-9276371c00a9 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_14.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 1eabd9f9-1a57-4c08-a830-9276371c00a9
Name: 13, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
26114993 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
26115098 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_14.tif'> shaped series axes do not match shape
making memmap
26127828 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 25be7a5b-dd16-42cd-bd4a-1312b4c6e791 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_15.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 25be7a5b-dd16-42cd-bd4a-1312b4c6e791
Name: 14, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
27085173 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
27085275 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_15.tif'> shaped series axes do not match shape
making memmap
27097698 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running f87dc096-6bb2-40dd-8dff-20f1362423b0 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_16.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid f87dc096-6bb2-40dd-8dff-20f1362423b0
Name: 15, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
28180411 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
28180503 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_16.tif'> shaped series axes do not match shape
making memmap
28193026 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 0e6f8223-3002-4430-a987-d83a6d7c7bd8 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_17.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 0e6f8223-3002-4430-a987-d83a6d7c7bd8
Name: 16, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
29157494 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
29157591 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_17.tif'> shaped series axes do not match shape
making memmap
29170250 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
30348548 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [ 582 3959]. Changing their value to -1.
Running 52ab80e3-880f-4ae5-bd38-711c0138ebe2 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_18.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 52ab80e3-880f-4ae5-bd38-711c0138ebe2
Name: 17, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
30355360 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
30355468 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_18.tif'> shaped series axes do not match shape
making memmap
30367833 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
31452651 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [9105]. Changing their value to -1.
Running 65c8dfa4-2a65-4618-8240-7f08fccce4ad with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_19.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 65c8dfa4-2a65-4618-8240-7f08fccce4ad
Name: 18, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
31459533 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
31459639 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_19.tif'> shaped series axes do not match shape
making memmap
31472279 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 473b088b-1b8e-4ecb-97e2-75eb299851b2 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_20.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 473b088b-1b8e-4ecb-97e2-75eb299851b2
Name: 19, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
32586470 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
32586579 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_20.tif'> shaped series axes do not match shape
making memmap
32599260 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
33628117 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [7225 9423]. Changing their value to -1.
Running 60d2fc66-20a9-4f00-b6f7-b9e80440efe7 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_21.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 60d2fc66-20a9-4f00-b6f7-b9e80440efe7
Name: 20, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
33634801 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
33634913 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_21.tif'> shaped series axes do not match shape
making memmap
33647481 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
34717794 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [9804]. Changing their value to -1.
Running 8926526d-cc18-47e2-b599-1496b2c9f03e with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_22.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 8926526d-cc18-47e2-b599-1496b2c9f03e
Name: 21, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
34724915 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
34725027 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_22.tif'> shaped series axes do not match shape
making memmap
34737745 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
35933489 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [9962]. Changing their value to -1.
Running f2b1c811-e02a-4058-a15b-861ee1128793 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_23.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid f2b1c811-e02a-4058-a15b-861ee1128793
Name: 22, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
35940221 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
35940329 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_23.tif'> shaped series axes do not match shape
making memmap
35953329 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
37047605 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [10077]. Changing their value to -1.
Running 5c9bd42e-fb07-43f0-a18d-0b9e516db4ec with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_24.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 5c9bd42e-fb07-43f0-a18d-0b9e516db4ec
Name: 23, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
37054379 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
37054485 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_24.tif'> shaped series axes do not match shape
making memmap
37067507 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 84004c56-81c1-474b-ab38-327fbf79bf8c with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_25.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 84004c56-81c1-474b-ab38-327fbf79bf8c
Name: 24, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
38169309 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
38169411 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_25.tif'> shaped series axes do not match shape
making memmap
38182278 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
Running 23521021-6791-4d41-855d-779eefce6840 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_26.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 23521021-6791-4d41-855d-779eefce6840
Name: 25, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
39302316 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
39302420 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_26.tif'> shaped series axes do not match shape
making memmap
39315055 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
40315273 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [ 947 1288]. Changing their value to -1.
Running 07907a0b-b138-41e3-99a7-f7153738a640 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_27.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 07907a0b-b138-41e3-99a7-f7153738a640
Name: 26, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
40322141 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
40322241 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_27.tif'> shaped series axes do not match shape
making memmap
40334799 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
41494502 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [ 891 5310 5924]. Changing their value to -1.
Running 8b7cbfb4-7c62-4780-a90c-5275cbe1f318 with local backend
************************************************************************
Starting CNMF item:
algo cnmf
item_name cnmf_1
input_movie_path tiff\extracted_plane_28.tif
params {'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': [7.5, 7.5],...
outputs None
added_time 2024-10-01T16:34:44
ran_time None
algo_duration None
comments None
uuid 8b7cbfb4-7c62-4780-a90c-5275cbe1f318
Name: 27, dtype: object
With params:{'main': {'fr': 9.62, 'dxy': (1.0, 1.0), 'decay_time': 0.4, 'p': 2, 'nb': 1, 'rf': 40, 'K': 150, 'gSig': array([7.5, 7.5]), 'stride': 10, 'method_init': 'greedy_roi', 'rolling_sum': True, 'use_cnn': False, 'ssub': 1, 'tsub': 1, 'merge_thr': 0.8, 'bas_nonneg': True, 'min_SNR': 1.4, 'rval_thr': 0.8}, 'refit': True}
41501713 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
41501811 [params.py:change_params():1151] [16596] In setting CNMFParams, non-pathed parameters were used; this is deprecated. In some future version of Caiman, allow_legacy will default to False (and eventually will be removed)
<tifffile.TiffFile 'extracted_plane_28.tif'> shaped series axes do not match shape
making memmap
41514314 [cluster.py:setup_cluster():225] [16596] The local backend is an alias for the multiprocessing backend, and the alias may be removed in some future version of Caiman
performing CNMF
fitting images
refitting
performing eval
42442632 [estimates.py:evaluate_components():1060] [16596] NaN values detected for space correlation in [ 4414 4684 7886 8450 8963 10179]. Changing their value to -1.
import fastplitlib as fpl
# create image widget for raw neural activity
raw_iw = fpl.Figure()
# re-add our identified good components from before using the SNR mapping
contours_graphic = raw_iw[0,0].add_line_collection(data=contours, cmap="spring", thickness=2, name="contours")
# get temporal components
temporal = df.iloc[row_ix].cnmf.get_temporal(component_indices="good")
# temporal plot
plot_temporal = fpl.Figure(size=(600,100))
plot_temporal[0,0].add_line(temporal[0], colors="magenta")
# add a linear selector to temporal trace
plot_temporal[0,0].graphics[0].add_linear_selector()
# show temporal plot and mcorr/rcm plot in ipywidgets VBox
sc = Sidecar()
# with sc:
display(VBox([raw_iw.show(), plot_temporal.show()]))
from ipywidgets import Tab, Text, Button, VBox, interact_manual, interactive
@interact_manual(parent_path=str(parent_path), batch_path=str(batch_path))
def start_widget(parent_path, batch_path):
mc.set_parent_raw_data_path(parent_path)
df = mc.load_batch(batch_path)
tab = Tab()
# mcorr_container = df.mcorr.viz()
cnmf_container = df.cnmf.viz(start_index=1)
tab.children = [cnmf_container.show()]
tab.titles = ["cnmf"]
display(tab)