From 8e2efc00654614224a81adfb43c523ed391adaab Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Al=C3=A1n=20Mu=C3=B1oz?= <alan.munoz@ed.ac.uk>
Date: Fri, 17 Mar 2023 19:42:52 +0000
Subject: [PATCH] docs(readme): refresh RemoteImageViewer info
---
README.md | 16 +++++++++++-----
src/aliby/utils/imageViewer.py | 24 ++++++++++++------------
2 files changed, 23 insertions(+), 17 deletions(-)
diff --git a/README.md b/README.md
index 98c1d528..4c4e84c7 100644
--- a/README.md
+++ b/README.md
@@ -80,12 +80,18 @@ It fetches the metadata from the Image object, and uses the TilerParameters valu
```python
fpath = "h5/location"
-trap_id = 9
-trange = list(range(0, 30))
+tile_id = 9
+trange = range(0, 10)
ncols = 8
riv = remoteImageViewer(fpath)
-trap_tps = riv.get_trap_timepoints(trap_id, trange, ncols)
+trap_tps = [riv.tiler.get_tiles_timepoint(tile_id, t) for t in trange]
+
+# You can also access labelled traps
+m_ts = riv.get_labelled_trap(tile_id=0, tps=[0])
+
+# And plot them directly
+riv.plot_labelled_trap(trap_id=0, channels=[0, 1, 2, 3], trange=range(10))
```
Depending on the network speed can take several seconds at the moment.
@@ -95,8 +101,8 @@ For a speed-up: take fewer z-positions if you can.
Alternatively, if you want to get all the traps at a given timepoint:
```python
-timepoint = 0
-seg_expt.get_tiles_timepoints(timepoint, tile_size=96, channels=None,
+timepoint = (4,6)
+tiler.get_tiles_timepoint(timepoint, channels=None,
z=[0,1,2,3,4])
```
diff --git a/src/aliby/utils/imageViewer.py b/src/aliby/utils/imageViewer.py
index f97f2fb0..5e9f0a04 100644
--- a/src/aliby/utils/imageViewer.py
+++ b/src/aliby/utils/imageViewer.py
@@ -6,12 +6,12 @@ Example of usage:
fpath = "/home/alan/Documents/dev/skeletons/scripts/data/16543_2019_07_16_aggregates_CTP_switch_2_0glu_0_0glu_URA7young_URA8young_URA8old_01/URA8_young018.h5"
-trap_id = 9
-trange = list(range(0, 30))
+tile_id = 9
+trange = list(range(0, 10))
ncols = 8
riv = remoteImageViewer(fpath)
-riv.plot_labelled_trap(trap_id, trange, [0], ncols=ncols)
+riv.plot_labelled_trap(tile_id, trange, [0], ncols=ncols)
"""
@@ -224,7 +224,7 @@ class RemoteImageViewer(BaseImageViewer):
def get_labelled_trap(
self,
- trap_id: int,
+ tile_id: int,
tps: t.Union[range, t.Collection[int]],
channels=None,
concatenate=True,
@@ -234,12 +234,12 @@ class RemoteImageViewer(BaseImageViewer):
Core method to fetch traps and labels together
"""
imgs = self.get_pos_timepoints(tps, channels=channels, **kwargs)
- imgs_list = [x[trap_id] for x in imgs.values()]
+ imgs_list = [x[tile_id] for x in imgs.values()]
outlines = [
- self.cells.at_time(tp, kind="edgemask").get(trap_id, [])
+ self.cells.at_time(tp, kind="edgemask").get(tile_id, [])
for tp in tps
]
- lbls = [self.cells.labels_at_time(tp).get(trap_id, []) for tp in tps]
+ lbls = [self.cells.labels_at_time(tp).get(tile_id, []) for tp in tps]
lbld_outlines = [
np.stack([mask * lbl for mask, lbl in zip(maskset, lblset)]).max(
axis=0
@@ -253,7 +253,7 @@ class RemoteImageViewer(BaseImageViewer):
imgs_list = np.concatenate(imgs_list, axis=1)
return lbld_outlines, imgs_list
- def get_images(self, trap_id, trange, channels, **kwargs):
+ def get_images(self, tile_id, trange, channels, **kwargs):
"""
Wrapper to fetch images
"""
@@ -262,13 +262,13 @@ class RemoteImageViewer(BaseImageViewer):
for ch in self._find_channels(channels):
out, imgs[ch] = self.get_labelled_trap(
- trap_id, trange, channels=[ch], **kwargs
+ tile_id, trange, channels=[ch], **kwargs
)
return out, imgs
def plot_labelled_trap(
self,
- trap_id: int,
+ tile_id: int,
channels,
trange: t.Union[range, t.Collection[int]],
remove_axis: bool = False,
@@ -288,7 +288,7 @@ class RemoteImageViewer(BaseImageViewer):
Parameters
----------
- trap_id : int
+ tile_id : int
Identifier of trap
channels : Union[str, int]
Channels to use
@@ -325,7 +325,7 @@ class RemoteImageViewer(BaseImageViewer):
nrows = int(np.ceil(len(trange) / ncols))
width = self.tiler.tile_size * ncols
- out, images = self.get_images(trap_id, trange, channels, **kwargs)
+ out, images = self.get_images(tile_id, trange, channels, **kwargs)
# dilation makes outlines easier to see
out = dilation(out).astype(float)
--
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