From 03e748c198b49fe4b3d5f5ac5dd079499f491c70 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Wed, 17 Jul 2024 13:13:49 +0200
Subject: [PATCH] Changed names of static methods
---
model_server/base/roiset.py | 35 +++++++++++++++---------------
tests/base/test_roiset.py | 14 ++++++------
tests/test_ilastik/test_ilastik.py | 4 ++--
3 files changed, 26 insertions(+), 27 deletions(-)
diff --git a/model_server/base/roiset.py b/model_server/base/roiset.py
index 70e73469..74d85ace 100644
--- a/model_server/base/roiset.py
+++ b/model_server/base/roiset.py
@@ -62,8 +62,7 @@ class RoiSetExportParams(BaseModel):
derived_channels: bool = False
-
-def _get_label_ids(acc_seg_mask: GenericImageDataAccessor, allow_3d=False, connect_3d=True) -> InMemoryDataAccessor:
+def get_label_ids(acc_seg_mask: GenericImageDataAccessor, allow_3d=False, connect_3d=True) -> InMemoryDataAccessor:
"""
Convert binary segmentation mask into either a 2D or 3D object identities map
:param acc_seg_mask: binary segmentation mask (mono) of either two or three dimensions
@@ -98,7 +97,7 @@ def _get_label_ids(acc_seg_mask: GenericImageDataAccessor, allow_3d=False, conne
)
-def _focus_metrics():
+def focus_metrics():
return {
'max_intensity': lambda x: np.max(x),
'stdev': lambda x: np.std(x),
@@ -109,7 +108,7 @@ def _focus_metrics():
}
-def _filter_df(df: pd.DataFrame, filters: RoiFilter = None) -> pd.DataFrame:
+def filter_df(df: pd.DataFrame, filters: RoiFilter = None) -> pd.DataFrame:
query_str = 'label > 0' # always true
if filters is not None: # parse filters
for k, val in filters.dict(exclude_unset=True).items():
@@ -122,7 +121,7 @@ def _filter_df(df: pd.DataFrame, filters: RoiFilter = None) -> pd.DataFrame:
# TODO: get overlapping bounding boxes
-def _filter_overlap_bbox(df: pd.DataFrame) -> pd.DataFrame:
+def filter_overlap_bbox(df: pd.DataFrame) -> pd.DataFrame:
def _compare(r0, r1):
olx = (r0.x0 < r1.x1) and (r0.x1 > r1.x0)
@@ -141,7 +140,7 @@ def _filter_overlap_bbox(df: pd.DataFrame) -> pd.DataFrame:
sdf['overlaps_with'] = second
return sdf
-def _make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFrame:
+def make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFrame:
"""
Build dataframe associate object IDs with summary stats
:param acc_raw: accessor to raw image data
@@ -169,7 +168,7 @@ def _make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFram
})
df['zi'] = df['label'].apply(lambda x: (acc_obj_ids.data == x).sum(axis=(0, 1, 2)).argmax())
- df = _df_insert_slices(df, acc_raw.shape_dict, expand_box_by)
+ df = df_insert_slices(df, acc_raw.shape_dict, expand_box_by)
# TODO: make this contingent on whether seg is included
def _make_binary_mask(r):
@@ -185,7 +184,7 @@ def _make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFram
return df
-def _df_insert_slices(df: pd.DataFrame, sd: dict, expand_box_by) -> pd.DataFrame:
+def df_insert_slices(df: pd.DataFrame, sd: dict, expand_box_by) -> pd.DataFrame:
h = sd['Y']
w = sd['X']
nz = sd['Z']
@@ -233,7 +232,7 @@ def _df_insert_slices(df: pd.DataFrame, sd: dict, expand_box_by) -> pd.DataFrame
return df
-def _safe_add(a, g, b):
+def safe_add(a, g, b):
assert a.dtype == b.dtype
assert a.shape == b.shape
assert g >= 0.0
@@ -244,7 +243,7 @@ def _safe_add(a, g, b):
np.iinfo(a.dtype).max
).astype(a.dtype)
-def _make_object_ids_from_df(df: pd.DataFrame, sd: dict) -> InMemoryDataAccessor:
+def make_object_ids_from_df(df: pd.DataFrame, sd: dict) -> InMemoryDataAccessor:
id_mask = np.zeros((sd['Y'], sd['X'], 1, sd['Z']), dtype='uint16')
if 'binary_mask' not in df.columns:
raise MissingSegmentationError('RoiSet dataframe does not contain segmentation')
@@ -305,8 +304,8 @@ class RoiSet(object):
):
assert acc_obj_ids.chroma == 1
- df = _filter_df(
- _make_df_from_object_ids(
+ df = filter_df(
+ make_df_from_object_ids(
acc_raw, acc_obj_ids, expand_box_by=params.expand_box_by
),
params.filters,
@@ -333,7 +332,7 @@ class RoiSet(object):
:param params: optional arguments that influence the definition and representation of ROIs
:return: object identities map
"""
- return RoiSet.from_object_ids(acc_raw, _get_label_ids(acc_seg, allow_3d=allow_3d, connect_3d=connect_3d), params)
+ return RoiSet.from_object_ids(acc_raw, get_label_ids(acc_seg, allow_3d=allow_3d, connect_3d=connect_3d), params)
# TODO: generate overlapping RoiSet from multiple masks
@@ -347,7 +346,7 @@ class RoiSet(object):
# TODO: get overlapping segments
def get_overlap_seg(self) -> pd.DataFrame:
- dfbb = _filter_overlap_bbox(self._df)
+ dfbb = filter_overlap_bbox(self._df)
def _iou(roi_i):
roi1 = self._df.loc[roi_i.index]
roi2 = self._df.loc[roi_i.overlaps_with]
@@ -568,7 +567,7 @@ class RoiSet(object):
continue
assert isinstance(ci, int)
assert ci < raw.chroma
- stack[:, :, ii, :] = _safe_add(
+ stack[:, :, ii, :] = safe_add(
stack[:, :, ii, :], # either black or grayscale channel
rgb_overlay_weights[ii],
raw.data[:, :, ci, :]
@@ -610,7 +609,7 @@ class RoiSet(object):
# make a 2d patch, find optimal z-position determined by focus_metric function on each channel separately
elif focus_metric is not None:
- foc = _focus_metrics()[focus_metric]
+ foc = focus_metrics()[focus_metric]
patch = np.zeros([ph, pw, pc, 1], dtype=patch3d.dtype)
@@ -775,7 +774,7 @@ class RoiSet(object):
@property
def acc_obj_ids(self):
- return _make_object_ids_from_df(self._df, self.acc_raw.shape_dict)
+ return make_object_ids_from_df(self._df, self.acc_raw.shape_dict)
# TODO: add docstring
# TODO: make this work with obj det dataset
@@ -794,7 +793,7 @@ class RoiSet(object):
except Exception as e:
raise DeserializeRoiSet(e)
df['binary_mask'] = df.apply(_read_binary_mask, axis=1)
- id_mask = _make_object_ids_from_df(df, acc_raw.shape_dict)
+ id_mask = make_object_ids_from_df(df, acc_raw.shape_dict)
return RoiSet.from_object_ids(acc_raw, id_mask)
diff --git a/tests/base/test_roiset.py b/tests/base/test_roiset.py
index bb428b5b..faf53d61 100644
--- a/tests/base/test_roiset.py
+++ b/tests/base/test_roiset.py
@@ -7,7 +7,7 @@ from pathlib import Path
import pandas as pd
-from model_server.base.roiset import _filter_overlap_bbox, RoiSetExportParams, RoiSetMetaParams
+from model_server.base.roiset import filter_overlap_bbox, RoiSetExportParams, RoiSetMetaParams
from model_server.base.roiset import RoiSet
from model_server.base.accessors import generate_file_accessor, InMemoryDataAccessor, write_accessor_data_to_file, PatchStack
from model_server.base.models import DummyInstanceSegmentationModel
@@ -70,7 +70,7 @@ class TestOverlapLogic(unittest.TestCase):
]
def test_overlap_bbox(self):
- res = _filter_overlap_bbox(self.df)
+ res = filter_overlap_bbox(self.df)
self.assertEqual(len(res), 2)
self.assertTrue((res.loc[0, 'overlaps_with'] == 1).all())
self.assertTrue((res.loc[1, 'overlaps_with'] == 2).all())
@@ -560,7 +560,7 @@ class TestRoiSetMultichannelProducts(BaseTestRoiSetMonoProducts, unittest.TestCa
self.assertEqual(pacc.chroma, 1)
-from model_server.base.roiset import _get_label_ids
+from model_server.base.roiset import get_label_ids
class TestRoiSetSerialization(unittest.TestCase):
def setUp(self) -> None:
@@ -577,19 +577,19 @@ class TestRoiSetSerialization(unittest.TestCase):
return mask_3d.sum() == mask_mip.sum()
def test_id_map_connects_z(self):
- id_map = _get_label_ids(self.seg_mask_3d, allow_3d=True, connect_3d=True)
+ id_map = get_label_ids(self.seg_mask_3d, allow_3d=True, connect_3d=True)
labels = np.unique(id_map.data)[1:]
is_2d = all([self._label_is_2d(id_map.data, la) for la in labels])
self.assertFalse(is_2d)
def test_id_map_disconnects_z(self):
- id_map = _get_label_ids(self.seg_mask_3d, allow_3d=True, connect_3d=False)
+ id_map = get_label_ids(self.seg_mask_3d, allow_3d=True, connect_3d=False)
labels = np.unique(id_map.data)[1:]
is_2d = all([self._label_is_2d(id_map.data, la) for la in labels])
self.assertTrue(is_2d)
def test_create_roiset_from_3d_obj_ids(self):
- id_map = _get_label_ids(self.seg_mask_3d, allow_3d=True, connect_3d=False)
+ id_map = get_label_ids(self.seg_mask_3d, allow_3d=True, connect_3d=False)
self.assertEqual(self.stack_ch_pa.shape, id_map.shape)
roiset = RoiSet.from_object_ids(
@@ -601,7 +601,7 @@ class TestRoiSetSerialization(unittest.TestCase):
self.assertGreater(len(roiset.get_df()['zi'].unique()), 1)
def test_create_roiset_from_2d_obj_ids(self):
- id_map = _get_label_ids(self.seg_mask_3d, allow_3d=False)
+ id_map = get_label_ids(self.seg_mask_3d, allow_3d=False)
self.assertEqual(self.stack_ch_pa.shape[0:3], id_map.shape[0:3])
self.assertEqual(id_map.nz, 1)
diff --git a/tests/test_ilastik/test_ilastik.py b/tests/test_ilastik/test_ilastik.py
index bd2be94a..35a41813 100644
--- a/tests/test_ilastik/test_ilastik.py
+++ b/tests/test_ilastik/test_ilastik.py
@@ -5,7 +5,7 @@ import numpy as np
from model_server.base.accessors import CziImageFileAccessor, generate_file_accessor, InMemoryDataAccessor, PatchStack, write_accessor_data_to_file
from model_server.extensions.ilastik import models as ilm
from model_server.extensions.ilastik.workflows import infer_px_then_ob_model
-from model_server.base.roiset import _get_label_ids, RoiSet, RoiSetMetaParams
+from model_server.base.roiset import get_label_ids, RoiSet, RoiSetMetaParams
from model_server.base.workflows import classify_pixels
import model_server.conf.testing as conf
@@ -403,7 +403,7 @@ class TestIlastikObjectClassification(unittest.TestCase):
self.roiset = RoiSet(
stack_ch_pa,
- _get_label_ids(seg_mask),
+ get_label_ids(seg_mask),
params=RoiSetMetaParams(
mask_type='boxes',
filters={'area': {'min': 1e3, 'max': 1e4}},
--
GitLab