def test_eq(self, trafo):
"""multicolor.Registrator: Test equality operator"""
r1 = multicolor.Registrator()
r1.parameters1 = trafo
r1.parameters2 = trafo * 2
r2 = multicolor.Registrator()
r2.parameters1 = trafo
r2.parameters2 = trafo * 3
assert r1 == r1
assert r1 != r2
assert r1 != "bla"
def test_save_load(self, save_fmt, trafo, tmp_path):
"""multicolor.Registrator: save to/load from binary file"""
cc = multicolor.Registrator()
cc.parameters1 = trafo
cc.parameters2 = np.linalg.inv(trafo)
data_keys = ("c1", "c2")
# Test with file object
with open(tmp_path / f"save.{save_fmt}", "w+b") as f:
cc.save(f, fmt=save_fmt, key=data_keys)
f.seek(0)
cc_loaded_file = multicolor.Registrator.load(f,
fmt=save_fmt,
key=data_keys)
np.testing.assert_allclose(cc_loaded_file.parameters1, trafo)
np.testing.assert_allclose(cc_loaded_file.parameters2,
np.linalg.inv(trafo))
# Test with file name
fname = tmp_path / f"bla.{save_fmt}"
cc.save(fname, fmt=save_fmt, key=data_keys)
cc_loaded_fname = multicolor.Registrator.load(fname,
fmt=save_fmt,
key=data_keys)
np.testing.assert_allclose(cc_loaded_fname.parameters1, trafo)
np.testing.assert_allclose(cc_loaded_fname.parameters2,
np.linalg.inv(trafo))
def test_determine_parameters(self, dataframes, dataframe_pairs, trafo):
"""multicolor.Registrator.determine_parameters"""
cc = multicolor.Registrator(dataframes[0], dataframes[1])
cc.determine_parameters()
res = cc.pairs.sort_values(("channel1", "x")).reset_index(drop=True)
pd.testing.assert_frame_equal(res, dataframe_pairs)
np.testing.assert_allclose(cc.parameters1, trafo)
np.testing.assert_allclose(cc.parameters2, np.linalg.inv(trafo))
def test_find_pairs_multi_file(self, dataframes, dataframe_pairs):
"""multicolor.Registrator.find_pairs, list of input features"""
cc = multicolor.Registrator([dataframes[0]] * 2, [dataframes[1]] * 2)
cc.find_pairs()
res = cc.pairs.sort_values(("channel1", "x")).reset_index(drop=True)
exp = pd.concat([dataframe_pairs] * 2)
exp = exp.sort_values(("channel1", "x")).reset_index(drop=True)
pd.testing.assert_frame_equal(res, exp)
def __init__(self, parent=None):
super().__init__(parent)
self._channels = {}
self._frameSel = multicolor.FrameSelector("")
self._registrator = multicolor.Registrator()
self.channelsChanged.connect(self._imageDataChanged)
self.registratorChanged.connect(self._imageDataChanged)
self.excitationSeqChanged.connect(self._imageDataChanged)
def test_call_img(self):
"""multicolor.Registrator.__call__: image arg"""
cc = multicolor.Registrator(None, None)
img = np.arange(50)[:, np.newaxis] + np.arange(100)[np.newaxis, :]
cc.parameters1 = np.array([[-1, 0, img.shape[1] - 1], [0, 1, 0],
[0, 0, 1]])
cc.parameters2 = np.linalg.inv(cc.parameters1)
img_corr = cc(img, channel=1)
np.testing.assert_allclose(img_corr, img[:, ::-1])
def test_yaml(self, trafo):
"""multicolor.Registrator: save to/load from YAML"""
cc = multicolor.Registrator()
cc.parameters1 = trafo
cc.parameters2 = np.linalg.inv(trafo)
sio = StringIO()
io.yaml.safe_dump(cc, sio)
sio.seek(0)
cc_loaded = io.yaml.safe_load(sio)
np.testing.assert_allclose(cc_loaded.parameters1, trafo)
np.testing.assert_allclose(cc_loaded.parameters2, np.linalg.inv(trafo))
def test_call_img_callable_cval(self):
"""multicolor.Registrator.__call__: image arg with callable `cval`"""
cc = multicolor.Registrator(None, None)
img = np.arange(50)[:, np.newaxis] + np.arange(100)[np.newaxis, :]
cc.parameters1 = np.array([[-1, 0, img.shape[1] // 2 - 1], [0, 1, 0],
[0, 0, 1]])
cc.parameters2 = np.linalg.inv(cc.parameters1)
img_corr = cc(img, channel=1, cval=lambda x: -10)
exp = np.empty_like(img)
exp[:, :exp.shape[1] // 2] = img[:, img.shape[1] // 2 - 1::-1]
exp[:, exp.shape[1] // 2:] = -10
np.testing.assert_allclose(img_corr, exp)
def calc_registration(self, plot: bool = True,
max_frame: Optional[int] = None,
params: Optional[Dict[str, Any]] = None
) -> Optional[mpl.figure.FigureCanvasBase]:
"""Calculate transformation between color channels
Localize beads using the options set with :py:meth:`set_bead_loc_opts`,
find pairs and fit transformation. Store result in
:py:attr:`self.tracker.registrator`.
Parameters
----------
plot
If True, plot the fit results and return the figure canvas.
max_frame
Maximum frame number to consider. Useful if beads defocused in
later frames. If `None` use all frames.
params
Passed to :py:meth:`multicolor.Registrator.determine_parameters`.
Returns
-------
If ``plot=True``, return the figure canvas which can be displayed
in Jupyter notebooks.
"""
label = ipywidgets.Label(value="Starting…")
display(label)
n_files = len(self.special_sources["registration"])
locs = {"donor": [], "acceptor": []}
for n, img_file in enumerate(
self.special_sources["registration"].values()):
label.value = f"Locating beads (file {n+1}/{n_files})"
im_seq, to_close = self._open_image_sequence(img_file)
for chan in "donor", "acceptor":
locator = self.locators[f"reg_{chan}"]
lo = locator.batch_func(im_seq[chan][:max_frame],
**locator.options)
locs[chan].append(lo)
label.layout = ipywidgets.Layout(display="none")
cc = multicolor.Registrator(locs["donor"], locs["acceptor"])
cc.determine_parameters(**params or {})
self.tracker.registrator = cc
if plot:
fig, ax = plt.subplots(1, 2)
cc.test(ax=ax)
return fig.canvas
def test_fit_parameters(self, dataframe_pairs, trafo):
"""multicolor.Registrator.fit_parameters"""
cc = multicolor.Registrator(None, None)
# Add outlier
dataframe_pairs.loc[dataframe_pairs.index.max() + 1] = \
[10., 12., -70., -110.]
cc.pairs = dataframe_pairs
cc.fit_parameters()
# Check whether ambiguous outlier pairs were removed
res = cc.pairs.sort_values(("channel1", "x")).reset_index(drop=True)
pd.testing.assert_frame_equal(res, dataframe_pairs.iloc[:-1])
# Check transforms
np.testing.assert_allclose(cc.parameters1, trafo)
np.testing.assert_allclose(cc.parameters2, np.linalg.inv(trafo))
def test_find_pairs_multi_frame(self, dataframes, dataframe_pairs):
"""multicolor.Registrator.find_pairs, multiple frames"""
dfs = []
for d in dataframes:
d1 = d.copy()
d["frame"] = 0
d1["frame"] = 1
dfs.append(pd.concat([d, d1], ignore_index=True))
cc = multicolor.Registrator(dfs[0], dfs[1])
cc.find_pairs()
res = cc.pairs.sort_values(("channel1", "x")).reset_index(drop=True)
exp = pd.concat([dataframe_pairs] * 2)
exp = exp.sort_values(("channel1", "x")).reset_index(drop=True)
pd.testing.assert_frame_equal(res, exp)
def test_call_dataframe(self, dataframes):
"""multicolor.Registrator.__call__: DataFrame arg"""
cc = multicolor.Registrator(*dataframes)
cc.determine_parameters()
res = cc.pairs["channel1"].copy()
res["frame"] = 0
exp = cc.pairs["channel2"].copy()
exp["frame"] = res["frame"]
res2 = cc(res, channel=1, inplace=False)
cc(res, channel=1, inplace=True)
pd.testing.assert_frame_equal(res, exp)
pd.testing.assert_frame_equal(res2, exp)
def test_determine_parameters_mirrored(self, dataframes, dataframe_pairs,
trafo):
"""multicolor.Registrator.determine_parameters, mirrored 1st axis"""
mirror_x = dataframes[0]["x"].max()
dataframes[0]["x"] = mirror_x - dataframes[0]["x"]
dataframe_pairs["channel1", "x"] = \
mirror_x - dataframe_pairs["channel1", "x"]
cc = multicolor.Registrator(dataframes[0], dataframes[1])
cc.determine_parameters()
res = cc.pairs.sort_values(("channel1", "x"), ascending=False)
res = res.reset_index(drop=True)
pd.testing.assert_frame_equal(res, dataframe_pairs)
trafo = trafo @ np.array([[-1, 0, mirror_x], [0, 1, 0], [0, 0, 1]])
np.testing.assert_allclose(cc.parameters1, trafo)
np.testing.assert_allclose(cc.parameters2, np.linalg.inv(trafo))
def __init__(self, parent=None):
super().__init__(parent)
self.dataRoles = [
"display", "key", "ddImg", "daImg", "aaImg", "particles"
]
self._channels = {
"acceptor": {
"source_id": 0,
"roi": None
},
"donor": {
"source_id": 0,
"roi": None
}
}
self._excitationSeq = ""
self._registrator = multicolor.Registrator()
self._trackLengthRange = [0, np.inf]
self.propagateProperty("channels")
self.propagateProperty("excitationSeq")
self.propagateProperty("registrator")
def test_find_pairs_no_frame(self, dataframes, dataframe_pairs):
"""multicolor.Registrator.find_pairs, no "frame" column"""
cc = multicolor.Registrator(dataframes[0], dataframes[1])
cc.find_pairs()
res = cc.pairs.sort_values(("channel1", "x")).reset_index(drop=True)
pd.testing.assert_frame_equal(res, dataframe_pairs)