def load_tile(t_query):
"""load a single tile (image)
Gets the image path from the \
:data:`TileQuery.RUNTIME`. ``IMAGE`` attribute.
Gets the position of the image with the whole \
volume from :meth:`TileQuery.all_scales`, \
:meth:`TileQuery.tile_origin`, and \
:meth:`TileQuery.blocksize`.
Arguments
-----------
t_query: :class:`TileQuery`
With file path and image position
Returns
--------
numpy.ndarray
1/H/W image volume
"""
# call superclass
Datasource.load_tile(t_query)
# Get needed field from t_query
boss_field = t_query.RUNTIME.IMAGE.SOURCE.BOSS
# Get parameters from t_query
tile_start = boss_field.INFO.START.VALUE
path_dict = boss_field.PATHS.VALUE
i_z, i_y, i_x = t_query.index_zyx + tile_start
# Attempt to get path from dictionary
z_path = path_dict.get(i_z,{})
if type(z_path) is dict:
# Get path from dictionary
path = z_path.get(i_y,{}).get(i_x,'')
else:
# Get path from string
path = z_path.format(column=i_x, row=i_y)
# Sanity check returns empty tile
if not len(path) or not os.path.exists(path):
return []
# Read the image from the file
return BossGrid.imread(path)[np.newaxis]
def load_tile(t_query):
"""load a single tile (image)
Gets the image path from the \
:data:`TileQuery.RUNTIME`. ``IMAGE`` attribute.
Gets the position of the image with the whole \
volume from :meth:`TileQuery.all_scales`, \
:meth:`TileQuery.tile_origin`, and \
:meth:`TileQuery.blocksize`.
Arguments
-----------
t_query: :class:`TileQuery`
With file path and image position
Returns
--------
numpy.ndarray
1/H/W image volume
"""
# call superclass
Datasource.load_tile(t_query)
# Get needed field from t_query
boss_field = t_query.RUNTIME.IMAGE.SOURCE.BOSS
# Get parameters from t_query
tile_start = boss_field.INFO.START.VALUE
path_dict = boss_field.PATHS.VALUE
i_z, i_y, i_x = t_query.index_zyx + tile_start
# Attempt to get path from dictionary
z_path = path_dict.get(i_z, {})
if type(z_path) is dict:
# Get path from dictionary
path = z_path.get(i_y, {}).get(i_x, '')
else:
# Get path from string
path = z_path.format(column=i_x, row=i_y)
# Sanity check returns empty tile
if not len(path) or not os.path.exists(path):
return []
# Read the image from the file
return BossGrid.imread(path)[np.newaxis]
def load_tile(t_query):
"""load a single tile (image)
Gets the image path from the \
:data:`TileQuery.RUNTIME`. ``IMAGE`` attribute.
Gets the position of the image with the whole \
volume from :meth:`TileQuery.all_scales`, \
:meth:`TileQuery.tile_origin`, and \
:meth:`TileQuery.blocksize`.
Arguments
-----------
t_query: :class:`TileQuery`
With file path and image position
Returns
-----------
np.ndarray
An image array that may be as large \
as an entire full resolution slice of \
the whole hdf5 volume. Based on the value \
of :meth:`TileQuery.all_scales`, this array \
will likely be downsampled by to a small fraction \
of the full tile resolution.
"""
# call superclass
Datasource.load_tile(t_query)
# Load data for all the h5 files
h5_files = t_query.RUNTIME.IMAGE.SOURCE.HDF5.VALUE
# Get all the z indices and coordinates
z_stops = list(enumerate(zip(*h5_files)[-1]))
z_starts = z_stops[::-1]
# Find the region to crop
sk, sj, si = t_query.all_scales
[z0, y0, x0], [z1, y1, x1] = t_query.source_tile_bounds
# Get the scaled blocksize for the output array
zb, yb, xb = t_query.blocksize
# get the right h5 files for the current z index
start_z = next((i for i, z in z_starts if z <= z0), 0)
stop_z = next((i for i, z in z_stops if z >= z1), len(z_stops))
needed_files = [h5_files[zi] for zi in range(start_z, stop_z)]
####
# Load from all needed files
####
dtype = getattr(np, t_query.OUTPUT.INFO.TYPE.VALUE)
# Make the full volume for all needed file volumes
full_vol = np.zeros([zb, yb, xb], dtype=dtype)
# Get the first offset
offset_0 = needed_files[0][-1]
# Loop through all needed h5 files
for h5_file in needed_files:
# Offset for this file
z_offset = h5_file[-1]
# Get input and output start
iz0 = max(z0 - z_offset, 0)
# Scale output bounds by z-scale
oz0 = (z_offset - offset_0) // sk
# Load the image region from the h5 file
with h5py.File(h5_file[0]) as fd:
# read from one file
vol = fd[h5_file[1]]
# Get the input and output end-bounds
iz1 = min(z1 - z_offset, vol.shape[0])
# Scale the output bounds by the z-scale
dz = iz1 - iz0
oz1 = oz0 + dz // sk
# Get the volume from one file
file_vol = vol[iz0:iz1:sk, y0:y1:sj, x0:x1:si]
yf, xf = file_vol.shape[1:]
# Add the volume to the full volume
full_vol[oz0:oz1, :yf, :xf] = file_vol
# Combined from all files
return full_vol
def load_tile(t_query):
"""load a single tile (image)
Gets the image path from the \
:data:`TileQuery.RUNTIME`. ``IMAGE`` attribute.
Gets the position of the image with the whole \
volume from :meth:`TileQuery.all_scales`, \
:meth:`TileQuery.tile_origin`, and \
:meth:`TileQuery.blocksize`.
Arguments
-----------
t_query: :class:`TileQuery`
With file path and image position
Returns
-----------
np.ndarray
An image array that may be as large \
as an entire full resolution slice of \
the whole hdf5 volume. Based on the value \
of :meth:`TileQuery.all_scales`, this array \
will likely be downsampled by to a small fraction \
of the full tile resolution.
"""
# call superclass
Datasource.load_tile(t_query)
# Load data for all the h5 files
h5_files = t_query.RUNTIME.IMAGE.SOURCE.HDF5.VALUE
# Get all the z indices and coordinates
z_stops = list(enumerate(zip(*h5_files)[-1]))
z_starts = z_stops[::-1]
# Find the region to crop
sk,sj,si = t_query.all_scales
[z0,y0,x0],[z1,y1,x1] = t_query.source_tile_bounds
# Get the scaled blocksize for the output array
zb,yb,xb = t_query.blocksize
# get the right h5 files for the current z index
start_z = next((i for i, z in z_starts if z <= z0), 0)
stop_z = next((i for i, z in z_stops if z >= z1), len(z_stops))
needed_files = [h5_files[zi] for zi in range(start_z, stop_z)]
####
# Load from all needed files
####
dtype = getattr(np, t_query.OUTPUT.INFO.TYPE.VALUE)
# Make the full volume for all needed file volumes
full_vol = np.zeros([zb, yb, xb], dtype = dtype)
# Get the first offset
offset_0 = needed_files[0][-1]
# Loop through all needed h5 files
for h5_file in needed_files:
# Offset for this file
z_offset = h5_file[-1]
# Get input and output start
iz0 = max(z0 - z_offset, 0)
# Scale output bounds by z-scale
oz0 = (z_offset - offset_0) // sk
# Load the image region from the h5 file
with h5py.File(h5_file[0]) as fd:
# read from one file
vol = fd[h5_file[1]]
# Get the input and output end-bounds
iz1 = min(z1 - z_offset, vol.shape[0])
# Scale the output bounds by the z-scale
dz = iz1 - iz0
oz1 = oz0 + dz // sk
# Get the volume from one file
file_vol = vol[iz0:iz1:sk, y0:y1:sj, x0:x1:si]
yf, xf = file_vol.shape[1:]
# Add the volume to the full volume
full_vol[oz0:oz1,:yf,:xf] = file_vol
# Combined from all files
return full_vol
