diff --git a/aliby/tile/tiler.py b/aliby/tile/tiler.py
index 1046a87af1743a36ea3d264c57ceaaaffe7d5fba..3197122b6813a2acf0343838f62ff72fc9b661c7 100644
--- a/aliby/tile/tiler.py
+++ b/aliby/tile/tiler.py
@@ -1,6 +1,10 @@
-"""Segment/segmented pipelines.
+"""
+Segment/segmented pipelines.
Includes splitting the image into traps/parts,
-cell segmentation, nucleus segmentation."""
+cell segmentation, nucleus segmentation
+
+Standard order is (T, C, Z, Y, X)
+"""
import warnings
from functools import lru_cache
import h5py
@@ -244,6 +248,9 @@ class Tiler(ProcessABC):
super().__init__(parameters)
self.image = image
self.channels = metadata["channels"]
+ assert (
+ parameters.ref_channel in self.channels
+ ), "Reference channel not in the available channels"
self.ref_channel = self.get_channel_index(parameters.ref_channel)
self.trap_locs = trap_locs
try:
@@ -340,9 +347,7 @@ class Tiler(ProcessABC):
except:
print(
"Warning: Error ocurred when fetching "
- "images. Attempt {}".format(
- n_attempts + 1
- )
+ "images. Attempt {}".format(n_attempts + 1)
)
self.image.conn.connect()
n_attempts += 1
@@ -559,7 +564,6 @@ class Tiler(ProcessABC):
for i, ch in enumerate(self.channels):
if item in ch:
return i
- raise Exception(item + " not found. Check parameters sent to Tiler.")
###
diff --git a/aliby/tile/traps.py b/aliby/tile/traps.py
index 1891b35a9b234772e42afa932538e503e87b1b5b..0c2080475caf73ea15bb1581e0b637a0f9975692 100644
--- a/aliby/tile/traps.py
+++ b/aliby/tile/traps.py
@@ -300,142 +300,6 @@ def get_xy_tile(img, xmin, xmax, ymin, ymax, xidx=2, yidx=3, pad_val=None):
return tile
-def get_trap_timelapse(
- raw_expt, trap_locations, trap_id, tile_size=117, channels=None, z=None
-):
- """
- Get a timelapse for a given trap by specifying the trap_id
- :param trap_id: An integer defining which trap to choose. Counted
- between 0 and Tiler.n_traps - 1
- :param tile_size: The size of the trap tile (centered around the
- trap as much as possible, edge cases exist)
- :param channels: Which channels to fetch, indexed from 0.
- If None, defaults to [0]
- :param z: Which z_stacks to fetch, indexed from 0.
- If None, defaults to [0].
- :return: A numpy array with the timelapse in (C,T,X,Y,Z) order
- """
- # Set the defaults (list is mutable)
- channels = channels if channels is not None else [0]
- z = z if z is not None else [0]
- # Get trap location for that id:
- trap_centers = [
- trap_locations[i][trap_id] for i in range(len(trap_locations))
- ]
-
- max_shape = (raw_expt.shape[2], raw_expt.shape[3])
- tiles_shapes = [
- get_tile_shapes((x[0], x[1]), tile_size, max_shape)
- for x in trap_centers
- ]
-
- timelapse = [
- get_xy_tile(
- raw_expt[channels, i, :, :, z],
- xmin,
- xmax,
- ymin,
- ymax,
- pad_val=None,
- )
- for i, (xmin, xmax, ymin, ymax) in enumerate(tiles_shapes)
- ]
- return np.hstack(timelapse)
-
-
-def get_trap_timelapse_omero(
- raw_expt,
- trap_locations,
- trap_id,
- tile_size=117,
- channels=None,
- z=None,
- t=None,
-):
- """
- Get a timelapse for a given trap by specifying the trap_id
- :param raw_expt: A Timelapse object from which data is obtained
- :param trap_id: An integer defining which trap to choose. Counted
- between 0 and Tiler.n_traps - 1
- :param tile_size: The size of the trap tile (centered around the
- trap as much as possible, edge cases exist)
- :param channels: Which channels to fetch, indexed from 0.
- If None, defaults to [0]
- :param z: Which z_stacks to fetch, indexed from 0.
- If None, defaults to [0].
- :return: A numpy array with the timelapse in (C,T,X,Y,Z) order
- """
- # Set the defaults (list is mutable)
- channels = channels if channels is not None else [0]
- z_positions = z if z is not None else [0]
- times = (
- t if t is not None else np.arange(raw_expt.shape[1])
- ) # TODO choose sub-set of time points
- shape = (len(channels), len(times), tile_size, tile_size, len(z_positions))
- # Get trap location for that id:
- zct_tiles, slices, trap_ids = all_tiles(
- trap_locations,
- shape,
- raw_expt,
- z_positions,
- channels,
- times,
- [trap_id],
- )
-
- # TODO Make this an explicit function in TimelapseOMERO
- images = raw_expt.pixels.getTiles(zct_tiles)
- timelapse = np.full(shape, np.nan)
- total = len(zct_tiles)
- for (z, c, t, _), (y, x), image in tqdm(
- zip(zct_tiles, slices, images), total=total
- ):
- ch = channels.index(c)
- tp = times.tolist().index(t)
- z_pos = z_positions.index(z)
- timelapse[ch, tp, x[0]: x[1], y[0]: y[1], z_pos] = image
-
- # for x in timelapse: # By channel
- # np.nan_to_num(x, nan=np.nanmedian(x), copy=False)
- return timelapse
-
-
-def all_tiles(
- trap_locations, shape, raw_expt, z_positions, channels, times, traps
-):
- _, _, x, y, _ = shape
- _, _, MAX_X, MAX_Y, _ = raw_expt.shape
-
- trap_ids = []
- zct_tiles = []
- slices = []
- for z in z_positions:
- for ch in channels:
- for t in times:
- for trap_id in traps:
- centre = trap_locations[t][trap_id]
- (
- xmin,
- ymin,
- xmax,
- ymax,
- r_xmin,
- r_ymin,
- r_xmax,
- r_ymax,
- ) = tile_where(centre, x, y, MAX_X, MAX_Y)
- slices.append(
- (
- (r_ymin - ymin, r_ymax - ymin),
- (r_xmin - xmin, r_xmax - xmin),
- )
- )
- tile = (r_ymin, r_xmin, r_ymax - r_ymin, r_xmax - r_xmin)
- zct_tiles.append((z, ch, t, tile))
- trap_ids.append(trap_id) # So we remember the order!
- return zct_tiles, slices, trap_ids
-
-
def tile_where(centre, x, y, MAX_X, MAX_Y):
# Find the position of the tile
xmin = int(centre[1] - x // 2)