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scan.py
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import importlib
import inspect
import pathlib
import re
from datetime import datetime
from typing import Union
import numpy as np
import datajoint as dj
from element_interface.utils import find_root_directory
schema = dj.schema()
_linking_module = None
def activate(
scan_schema_name: str,
*,
create_schema: bool = True,
create_tables: bool = True,
linking_module: str = None,
):
"""Activate this schema.
Args:
scan_schema_name (str): Schema name on the database server to activate the
`scan` module
create_schema (bool): When True (default), create schema in the database if it
does not yet exist.
create_tables (bool): When True (default), create tables in the database if they
do not yet exist.
linking_module (str): A module name or a module containing the required
dependencies to activate the `scan` module.
Dependencies:
Upstream tables:
+ Session: Parent table to Scan, typically identifying a recording session
+ Equipment: Reference table for Scan, specifying the equipment used for the
acquisition of this scan.
+ Location: Reference table for ScanLocation, specifying the scanned regions's
anatomical location in the brain.
"""
if isinstance(linking_module, str):
linking_module = importlib.import_module(linking_module)
assert inspect.ismodule(
linking_module
), "The argument 'dependency' must be a module's name or a module"
global _linking_module
_linking_module = linking_module
schema.activate(
scan_schema_name,
create_schema=create_schema,
create_tables=create_tables,
add_objects=_linking_module.__dict__,
)
# Functions required by element-calcium-imaging -------------------------------
def get_imaging_root_data_dir() -> list:
"""Return imaging root data director(y/ies)
Retrieve the root data director(y/ies) containing the imaging data
for all subjects/sessions (e.g. acquired ScanImage raw files, output files from
processing routines, etc.). All data paths and directories in DataJoint Elements are
recommended to be stored as relative paths (posix format), with respect to some
user-configured "root" directory, which varies from machine to machine
(e.g. different mounted drive locations).
Returns:
dirs (list): A list of string(s) or Path(s) for the absolute paths of the imaging root data
director(y/ies).
"""
root_directories = _linking_module.get_imaging_root_data_dir()
if isinstance(root_directories, (str, pathlib.Path)):
root_directories = [root_directories]
if hasattr(_linking_module, "get_processed_root_data_dir"):
root_directories.append(_linking_module.get_processed_root_data_dir())
return root_directories
def get_processed_root_data_dir() -> Union[str, pathlib.Path]:
"""Retrieve the root directory for all processed data.
All data paths and directories in DataJoint Elements are recommended to be stored as
relative paths (posix format), with respect to some user-configured "root"
directory, which varies from machine to machine (e.g. different mounted drive
locations).
Returns:
dir (str| pathlib.Path): Absolute path of the processed imaging root data
directory.
"""
if hasattr(_linking_module, "get_processed_root_data_dir"):
return _linking_module.get_processed_root_data_dir()
else:
return get_imaging_root_data_dir()[0]
def get_calcium_imaging_files(scan_key: dict, acq_software: str) -> list:
"""Retrieve the list of absolute paths of the calcium imaging files associated with a given Scan and a given acquisition software (e.g. .tif, .sbx, etc.).
Args:
scan_key: Primary key of a Scan entry.
acq_software: name of the acquisition software, matching AcquisitionSoftware entry (i.e. "ScanImage" "Scanbox", "NIS", or "PrairieView")
Returns:
A list of full file paths.
"""
return _linking_module.get_calcium_imaging_files(scan_key, acq_software)
# ----------------------------- Table declarations ----------------------
@schema
class AcquisitionSoftware(dj.Lookup):
"""A list of acquisition softwares supported by the Element.
Required to define a scan.
Attributes:
acq_software (str): Acquisition software
"""
definition = """ # Acquisition softwares
acq_software: varchar(24)
"""
contents = zip(["ScanImage", "Scanbox", "NIS", "PrairieView"])
@schema
class Channel(dj.Lookup):
"""Recording channels for the imaging wavelengths.
Attributes:
channel (int): Channel index
"""
definition = """ # A recording channel
channel : tinyint # 0-based indexing
"""
contents = zip(range(5))
@schema
class Scan(dj.Manual):
"""Scan defined by a measurement done using a scanner and an acquisition software.
The details of the scanning data is placed in other tables, including,
ScanLocation, ScanInfo, and ScanInfo's part tables.
Attributes:
Session (foreign key): A primary key from Session.
scan_id (int): Unique Scan ID.
Equipment (foreign key, optional): A primary key from Equipment.
AcquisitionSoftware (foreign key): A primary key from AcquisitionSoftware.
scan_notes (str, optional): Notes of the experimenter regarding the scan.
"""
definition = """
-> Session
scan_id: int
---
-> [nullable] Equipment
-> AcquisitionSoftware
scan_notes='' : varchar(4095)
"""
@schema
class ScanLocation(dj.Manual):
"""Anatomical location of the scanned region in the brain
Attributes:
Scan (foreign key): A primary key from Scan.
Locaton (foreign key): A primary key from Location.
"""
definition = """ # Anatomical location
-> Scan
---
-> Location
"""
@schema
class ScanInfo(dj.Imported):
"""
Information about the scan extracted from the recorded files.
Attributes:
Scan (foreign key): A primary key from Scan.
nfields (int): Number of fields.
nchannels (int): Number of channels.
ndepths (int): Number of scanning depths (planes).
nframes (int): Number of recorded frames (time steps).
nrois (int): Number of ROIs (see scanimage's multi ROI imaging).
x (float, optional): ScanImage's 0 point in the motor coordinate system (um).
y (float, optional): ScanImage's 0 point in the motor coordinate system (um).
z (float, optional): ScanImage's 0 point in the motor coordinate system (um).
fps (float) : Frames per second (Hz) - Volumetric Scan Rate.
bidirectional (bool): True = bidirectional scanning.
usecs_per_line (float, optional): Microseconds per scan line.
fill_fraction (float, optional): Raster scan temporal fill fraction (see
scanimage)
scan_datetime (datetime, optional): Datetime of the scan.
scan_duration (float, optional): Duration of the scan (s).
bidirectional_z (bool, optional): True = bidirectional z-scan.
"""
definition = """ # General data about the resoscans/mesoscans from header
-> Scan
---
nfields : tinyint # number of fields
nchannels : tinyint # number of channels
ndepths : int # Number of scanning depths (planes)
nframes : int # number of recorded frames (time steps)
nrois : tinyint # number of ROIs (see scanimage's multi ROI imaging)
x=null : float # (um) ScanImage's 0 point in the motor coordinate system
y=null : float # (um) ScanImage's 0 point in the motor coordinate system
z=null : float # (um) ScanImage's 0 point in the motor coordinate system
fps : float # (Hz) frames per second - Volumetric Scan Rate
bidirectional : boolean # true = bidirectional scanning
usecs_per_line=null : float # microseconds per scan line
fill_fraction=null : float # raster scan temporal fill fraction (see scanimage)
scan_datetime=null : datetime # datetime of the scan
scan_duration=null : float # (seconds) duration of the scan
bidirectional_z=null : boolean # true = bidirectional z-scan
"""
class Field(dj.Part):
"""Stores field information of scan, including its coordinates, size, pixel
pitch, etc.
Attributes:
ScanInfo (foreign key): A primary key from ScanInfo.
field_idx (int): Unique field index.
px_height (int): Image height in pixels.
px_width (int): Image width in pixels.
um_height (float, optional): Image height in microns.
um_width (float, optional): Image width in microns.
field_x (float, optional): X coordinate of the center of field in the motor
coordinate system (um).
field_y (float, optional): Y coordinate of the center of field in the motor
coordinate system (um).
field_z (float, optional): Relative depth of field (um).
delay_image (longblob, optional): Delay between the start of the scan and
pixels in this field (ms).
roi (int, optional): The scanning roi (as recorded in the acquisition
software) containing this field - only relevant to mesoscale scans.
"""
definition = """ # field-specific scan information
-> master
field_idx : int
---
px_height : smallint # height in pixels
px_width : smallint # width in pixels
um_height=null : float # height in microns
um_width=null : float # width in microns
field_x=null : float # (um) center of field in the motor coordinate system
field_y=null : float # (um) center of field in the motor coordinate system
field_z=null : float # (um) relative depth of field
delay_image=null : longblob # (ms) delay between the start of the scan and pixels in this field
roi=null : int # the scanning roi (as recorded in the acquisition software) containing this field - only relevant to mesoscale scans
"""
class ScanFile(dj.Part):
"""Filepath of the scan relative to root data directory.
Attributes:
ScanInfo (foreign key): A primary key from ScanInfo.
file_path (str): Path of the scan file relative to the root data directory.
"""
definition = """
-> master
file_path: varchar(255) # Filepath relative to root data directory
"""
def make(self, key):
"""Populate the ScanInfo with the information parsed from image files."""
acq_software = (Scan & key).fetch1("acq_software")
scan_filepaths = get_calcium_imaging_files(key, acq_software)
if acq_software == "ScanImage":
import scanreader
# Read the scan
scan_ = scanreader.read_scan(scan_filepaths)
# Insert in ScanInfo
x_zero, y_zero, z_zero = scan_.motor_position_at_zero or (None, None, None)
self.insert1(
dict(
key,
nfields=scan_.num_fields,
nchannels=scan_.num_channels,
nframes=scan_.num_frames,
ndepths=scan_.num_scanning_depths,
x=x_zero,
y=y_zero,
z=z_zero,
fps=scan_.fps,
bidirectional=scan_.is_bidirectional,
usecs_per_line=scan_.seconds_per_line * 1e6,
fill_fraction=scan_.temporal_fill_fraction,
nrois=scan_.num_rois if scan_.is_multiROI else 0,
scan_duration=scan_.num_frames / scan_.fps,
)
)
# Insert Field(s)
if scan_.is_multiROI:
self.Field.insert(
[
dict(
key,
field_idx=field_id,
px_height=scan_.field_heights[field_id],
px_width=scan_.field_widths[field_id],
um_height=scan_.field_heights_in_microns[field_id],
um_width=scan_.field_widths_in_microns[field_id],
field_x=(
(x_zero or 0)
+ scan_._degrees_to_microns(scan_.fields[field_id].x)
),
field_y=(
(y_zero or 0)
+ scan_._degrees_to_microns(scan_.fields[field_id].y)
),
field_z=((z_zero or 0) + scan_.fields[field_id].depth),
delay_image=scan_.field_offsets[field_id],
roi=scan_.field_rois[field_id][0],
)
for field_id in range(scan_.num_fields)
]
)
else:
self.Field.insert(
[
dict(
key,
field_idx=plane_idx,
px_height=scan_.image_height,
px_width=scan_.image_width,
um_height=getattr(scan_, "image_height_in_microns", None),
um_width=getattr(scan_, "image_width_in_microns", None),
field_x=x_zero if x_zero else None,
field_y=y_zero if y_zero else None,
field_z=(
z_zero + scan_.scanning_depths[plane_idx]
if z_zero
else None
),
delay_image=scan_.field_offsets[plane_idx],
)
for plane_idx in range(scan_.num_scanning_depths)
]
)
elif acq_software == "Scanbox":
import sbxreader
# Read the scan
sbx_meta = sbxreader.sbx_get_metadata(scan_filepaths[0])
sbx_matinfo = sbxreader.sbx_get_info(scan_filepaths[0])
is_multiROI = bool(
sbx_matinfo.mesoscope.enabled
) # currently not handling "multiROI" ingestion
if is_multiROI:
raise NotImplementedError(
"Loading routine not implemented for Scanbox multiROI scan mode"
)
# Insert in ScanInfo
x_zero, y_zero, z_zero = sbx_meta["stage_pos"]
self.insert1(
dict(
key,
nfields=(
sbx_meta["num_fields"]
if is_multiROI
else sbx_meta["num_planes"]
),
nchannels=sbx_meta["num_channels"],
nframes=sbx_meta["num_frames"],
ndepths=sbx_meta["num_planes"],
x=x_zero,
y=y_zero,
z=z_zero,
fps=sbx_meta["frame_rate"],
bidirectional=sbx_meta == "bidirectional",
nrois=sbx_meta["num_rois"] if is_multiROI else 0,
scan_duration=(sbx_meta["num_frames"] / sbx_meta["frame_rate"]),
)
)
# Insert Field(s)
if not is_multiROI:
px_width, px_height = sbx_meta["frame_size"]
self.Field.insert(
[
dict(
key,
field_idx=plane_idx,
px_height=px_height,
px_width=px_width,
um_height=(
px_height * sbx_meta["um_per_pixel_y"]
if sbx_meta["um_per_pixel_y"]
else None
),
um_width=(
px_width * sbx_meta["um_per_pixel_x"]
if sbx_meta["um_per_pixel_x"]
else None
),
field_x=x_zero,
field_y=y_zero,
field_z=z_zero + sbx_meta["etl_pos"][plane_idx],
)
for plane_idx in range(sbx_meta["num_planes"])
]
)
elif acq_software == "NIS":
import nd2
# Read the scan
nd2_file = nd2.ND2File(scan_filepaths[0])
is_multiROI = False # MultiROI to be implemented later
# Frame per second
try:
fps = 1000 / nd2_file.experiment[0].parameters.periods[0].periodDiff.avg
except: # noqa: E722
fps = 1000 / nd2_file.experiment[0].parameters.periodDiff.avg
# Estimate ND2 file scan duration
def estimate_nd2_scan_duration(nd2_scan_obj):
# Calculates scan duration for Nikon images
ti = (
nd2_scan_obj.frame_metadata(0)
.channels[0]
.time.absoluteJulianDayNumber
) # Initial frame's JD.
tf = (
nd2_scan_obj.frame_metadata(nd2_scan_obj.shape[0] - 1)
.channels[0]
.time.absoluteJulianDayNumber
) # Final frame's JD.
return (tf - ti) * 86400 + 1 / fps
scan_duration = sum(
estimate_nd2_scan_duration(nd2.ND2File(f)) for f in scan_filepaths
)
try:
scan_datetime = nd2_file.text_info["date"]
scan_datetime = datetime.strptime(
scan_datetime,
(
"%m/%d/%Y %H:%M:%S %p"
if re.search(("AM|PM"), scan_datetime)
else "%m/%d/%Y %H:%M:%S"
),
)
scan_datetime = datetime.strftime(scan_datetime, "%Y-%m-%d %H:%M:%S")
except: # noqa: E722
scan_datetime = None
# Insert in ScanInfo
self.insert1(
dict(
key,
nfields=nd2_file.sizes.get("P", 1),
nchannels=nd2_file.attributes.channelCount,
nframes=nd2_file.metadata.contents.frameCount,
ndepths=nd2_file.sizes.get("Z", 1),
x=None,
y=None,
z=None,
fps=fps,
bidirectional=bool(
nd2_file.custom_data["GrabberCameraSettingsV1_0"][
"GrabberCameraSettings"
]["PropertiesQuality"]["ScanDirection"]
),
nrois=0,
scan_datetime=scan_datetime,
scan_duration=scan_duration,
)
)
# MultiROI to be implemented later
# Insert in Field
if not is_multiROI:
self.Field.insert(
[
dict(
key,
field_idx=plane_idx,
px_height=nd2_file.attributes.heightPx,
px_width=nd2_file.attributes.widthPx,
um_height=nd2_file.attributes.heightPx
* nd2_file.voxel_size().y,
um_width=nd2_file.attributes.widthPx
* nd2_file.voxel_size().x,
field_x=None,
field_y=None,
field_z=None,
)
for plane_idx in range(nd2_file.sizes.get("Z", 1))
]
)
elif acq_software == "PrairieView":
from element_interface import prairie_view_loader
PVScan_info = prairie_view_loader.get_prairieview_metadata(
scan_filepaths[0]
)
self.insert1(
dict(
key,
nfields=PVScan_info["num_fields"],
nchannels=PVScan_info["num_channels"],
ndepths=PVScan_info["num_planes"],
nframes=PVScan_info["num_frames"],
nrois=PVScan_info["num_rois"],
x=PVScan_info["x_pos"],
y=PVScan_info["y_pos"],
z=PVScan_info["z_pos"],
fps=PVScan_info["frame_rate"],
bidirectional=PVScan_info["bidirectional"],
bidirectional_z=PVScan_info["bidirectional_z"],
usecs_per_line=PVScan_info["usecs_per_line"],
scan_datetime=PVScan_info["scan_datetime"],
scan_duration=PVScan_info["scan_duration"],
)
)
self.Field.insert(
dict(
key,
field_idx=plane_idx,
px_height=PVScan_info["height_in_pixels"],
px_width=PVScan_info["width_in_pixels"],
um_height=PVScan_info["height_in_um"],
um_width=PVScan_info["width_in_um"],
field_x=PVScan_info["fieldX"],
field_y=PVScan_info["fieldY"],
field_z=(
PVScan_info["fieldZ"]
if PVScan_info["num_planes"] == 1
else PVScan_info["fieldZ"][plane_idx]
),
)
for plane_idx in range(PVScan_info["num_planes"])
)
else:
raise NotImplementedError(
f"Loading routine not implemented for {acq_software} "
"acquisition software"
)
# Insert file(s)
root_dir = find_root_directory(get_imaging_root_data_dir(), scan_filepaths[0])
scan_files = [
pathlib.Path(f).relative_to(root_dir).as_posix() for f in scan_filepaths
]
self.ScanFile.insert([{**key, "file_path": f} for f in scan_files])
@schema
class ScanQualityMetrics(dj.Computed):
"""Metrics to assess the quality of the scan.
Attributes:
ScanInfo.Field (foreign key): Primary key from ScanInfo.Field.
"""
definition = """
-> ScanInfo.Field
"""
class Frames(dj.Part):
"""Metrics used to evaluate each frame.
Attributes:
ScanInfo.Field (foreign key): Primary key from ScanInfo.Field.
Channel (foreign key): Primary key from Channel.
min_intensity (longblob): Minimum value of each frame.
mean_intensity (longblob): Mean value of each frame.
max_intensity (longblob): Maximum value of each frame.
contrast (longblob): Contrast of each frame (i.e. difference between the 99 and 1 percentiles)
"""
definition = """
-> master
-> Channel
---
min_intensity: longblob # Minimum value of each frame.
mean_intensity: longblob # Mean value of each frame.
max_intensity: longblob # Maximum value of each frame.
contrast: longblob # Contrast of each frame (i.e. difference between the 99 and 1 percentiles)
"""
def make(self, key):
acq_software, nchannels = (Scan * ScanInfo & key).fetch1(
"acq_software", "nchannels"
)
scan_filepaths = get_calcium_imaging_files(key, acq_software)
if acq_software == "ScanImage":
import scanreader
# Switch from FYXCT to TCYX
data = scanreader.read_scan(scan_filepaths)[key["field_idx"]].transpose(
3, 2, 0, 1
)
elif acq_software == "Scanbox":
from sbxreader import sbx_memmap
# Switch from TFCYX to TCYX
data = sbx_memmap(scan_filepaths)[:, key["field_idx"]]
elif acq_software == "NIS":
import nd2
nd2_file = nd2.ND2File(scan_filepaths[0])
nd2_dims = {k: i for i, k in enumerate(nd2_file.sizes)}
valid_dimensions = "TZCYX"
assert set(nd2_dims) <= set(
valid_dimensions
), f"Unknown dimensions {set(nd2_dims)-set(valid_dimensions)} in file {scan_filepaths[0]}."
# Sort the dimensions in the order of TZCYX, skipping the missing ones.
data = nd2_file.asarray().transpose(
[nd2_dims[x] for x in valid_dimensions if x in nd2_dims]
)
# Expand array to include the missing dimensions.
for i, dim in enumerate("TZC"):
if dim not in nd2_dims:
data = np.expand_dims(data, i)
data = data[:, key["field_idx"]] # Switch from TFCYX to TCYX
self.insert1(key)
for channel in range(nchannels):
movie = data[:, channel, :, :]
self.Frames.insert1(
dict(
key,
channel=channel,
min_intensity=movie.min(axis=(1, 2)),
mean_intensity=movie.mean(axis=(1, 2)),
max_intensity=movie.max(axis=(1, 2)),
contrast=np.percentile(movie, 99, axis=(1, 2))
- np.percentile(movie, 1, axis=(1, 2)),
)
)