def point():
o = PointI()
populate_shape(o)
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
o.id = rlong(3L)
return o
def __init__(self, roicoord=ROICoordinate(), x=0, y=0, width=0, height=0):
ShapeData.__init__(self)
self.x = rdouble(x)
self.y = rdouble(y)
self.width = rdouble(width)
self.height = rdouble(height)
self.setCoord(roicoord)
def opt_unit_label(identity_transform):
o = LabelI()
populate_shape(o, identity_transform, False)
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(7)
return o
def _parse_mnu_roi(self, columns):
"""Parses out ROI from OmeroTables columns for 'MNU' datasets."""
log.debug("Parsing %s MNU ROIs..." % (len(columns[0].values)))
image_ids = columns[self.IMAGE_COL].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = FileAnnotationI(self.file_annotation.id.val, False)
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
values = columns[3].values
shape.cx = rdouble(float(values[i]))
values = columns[2].values
shape.cy = rdouble(float(values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
if len(rois) == self.ROI_UPDATE_LIMIT:
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
self.thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns[self.ROI_COL].values += batches[k]
def __init__(self, roicoord=ROICoordinate(), x=0, y=0):
warnings.warn("This module is deprecated as of OMERO 5.3.0",
DeprecationWarning)
ShapeData.__init__(self)
self.x = rdouble(x)
self.y = rdouble(y)
self.setCoord(roicoord)
def opt_unit_label():
o = LabelI()
populate_shape(o, False)
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(7L)
return o
def __init__(self, roicoord=ROICoordinate(), x1=0, y1=0, x2=0, y2=0):
ShapeData.__init__(self)
self.x1 = rdouble(x1)
self.y1 = rdouble(y1)
self.x2 = rdouble(x2)
self.y2 = rdouble(y2)
self.setCoord(roicoord)
def create_mask(
binim, rgba=None, z=None, c=None, t=None, text=None,
raise_on_no_mask=False):
"""
Create a mask shape from a binary image (background=0)
:param numpy.array binim: Binary 2D array, must contain values [0, 1] only
:param rgba int-4-tuple: Optional (red, green, blue, alpha) colour
:param z: Optional Z-index for the mask
:param c: Optional C-index for the mask
:param t: Optional T-index for the mask
:param text: Optional text for the mask
:param raise_on_no_mask: If True (default) throw an exception if no mask
found, otherwise return an empty Mask
:return: An OMERO mask
:raises NoMaskFound: If no labels were found
:raises InvalidBinaryImage: If the maximum labels is greater than 1
"""
# Find bounding box to minimise size of mask
xmask = binim.sum(0).nonzero()[0]
ymask = binim.sum(1).nonzero()[0]
if any(xmask) and any(ymask):
x0 = min(xmask)
w = max(xmask) - x0 + 1
y0 = min(ymask)
h = max(ymask) - y0 + 1
submask = binim[y0:(y0 + h), x0:(x0 + w)]
if (not np.array_equal(np.unique(submask), [0, 1]) and not
np.array_equal(np.unique(submask), [1])):
raise Exception("Invalid binary image")
else:
if raise_on_no_mask:
raise Exception("No mask found")
x0 = 0
w = 0
y0 = 0
h = 0
submask = []
mask = MaskI()
mask.setBytes(np.packbits(np.asarray(submask, dtype=int)))
mask.setWidth(rdouble(w))
mask.setHeight(rdouble(h))
mask.setX(rdouble(x0))
mask.setY(rdouble(y0))
if rgba is not None:
ch = ColorHolder.fromRGBA(*rgba)
mask.setFillColor(rint(ch.getInt()))
if z is not None:
mask.setTheZ(rint(z))
if c is not None:
mask.setTheC(rint(c))
if t is not None:
mask.setTheT(rint(t))
if text is not None:
mask.setTextValue(rstring(text))
return mask
def roi_from_binary_image(binim, rgba):
# Find bounding box to minimise size of mask
xmask = binim.sum(0).nonzero()[0]
ymask = binim.sum(1).nonzero()[0]
x0 = min(xmask)
w = max(xmask) - x0 + 1
y0 = min(ymask)
h = max(ymask) - y0 + 1
submask = binim[y0:(y0 + h), x0:(x0 + w)]
# print (x0, y0, w, h)
mask = omero.model.MaskI()
# BUG in older versions of Numpy:
# https://github.com/numpy/numpy/issues/5377
# Need to convert to an int array
# mask.setBytes(np.packbits(submask))
mask.setBytes(np.packbits(np.asarray(submask, dtype=int)))
mask.setWidth(rdouble(w))
mask.setHeight(rdouble(h))
mask.setX(rdouble(x0))
mask.setY(rdouble(y0))
ch = omero.gateway.ColorHolder.fromRGBA(*rgba)
mask.setFillColor(rint(ch.getInt()))
roi = omero.model.RoiI()
roi.addShape(mask)
return roi
def label():
o = LabelI()
populate_shape(o)
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(7L)
return o
def __init__(self, roicoord=ROICoordinate(), cx=0, cy=0, rx=0, ry=0):
ShapeData.__init__(self)
self.cx = rdouble(cx)
self.cy = rdouble(cy)
self.rx = rdouble(rx)
self.ry = rdouble(ry)
self.setCoord(roicoord)
def __init__(self, roicoord = ROICoordinate(), cx = 0, cy = 0, rx = 0, ry = 0):
ShapeData.__init__(self);
self.cx = rdouble(cx);
self.cy = rdouble(cy);
self.rx = rdouble(rx);
self.ry = rdouble(ry);
self.setCoord(roicoord);
def opt_unit_label():
o = LabelI()
populate_shape(o, False)
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(7L)
return o
def __init__(self, roicoord = ROICoordinate(), x = 0, y = 0, width = 0, height = 0):
ShapeData.__init__(self);
self.x = rdouble(x);
self.y = rdouble(y);
self.width = rdouble(width);
self.height = rdouble(height);
self.setCoord(roicoord);
def point():
o = PointI()
populate_shape(o)
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
o.id = rlong(3L)
return o
def __init__(self, roicoord = ROICoordinate(), x1 = 0, y1 = 0, x2 = 0, y2 = 0):
ShapeData.__init__(self);
self.x1 = rdouble(x1);
self.y1 = rdouble(y1);
self.x2 = rdouble(x2);
self.y2 = rdouble(y2);
self.setCoord(roicoord);
def label():
o = LabelI()
populate_shape(o)
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(7L)
return o
def create_shape_point(x_pos,
y_pos,
z_pos=None,
c_pos=None,
t_pos=None,
name=None,
stroke_color=(255, 255, 255, 255),
fill_color=(10, 10, 10, 20),
stroke_width=1):
point = model.PointI()
point.x = rtypes.rdouble(x_pos)
point.y = rtypes.rdouble(y_pos)
if z_pos is not None:
point.theZ = rtypes.rint(z_pos)
if c_pos is not None:
point.theC = rtypes.rint(c_pos)
if t_pos is not None:
point.theT = rtypes.rint(t_pos)
_set_shape_properties(shape=point,
name=name,
stroke_color=stroke_color,
stroke_width=stroke_width,
fill_color=fill_color)
return point
def __init__(self, roicoord = ROICoordinate(), bytes = None, x = 0, y = 0, width = 0, height = 0):
ShapeData.__init__(self);
self.x = rdouble(x);
self.y = rdouble(y);
self.width = rdouble(width);
self.height = rdouble(height);
self.bytesdata = bytes;
self.setCoord(roicoord);
def create_omero_point(data, image):
point = PointI()
point.x = rdouble(get_x(data))
point.y = rdouble(get_y(data))
point.theZ = rint(get_z(data, image))
point.theT = rint(get_t(data, image))
point.textValue = rstring("point-from-napari")
return point
def create_roi(im, x, y, t):
p = omero.model.PointI()
p.setTheT(rint(t))
p.setCx(rdouble(x))
p.setCy(rdouble(y))
roi = omero.model.RoiI()
roi.addShape(p)
roi.setImage(im)
return roi
def ellipse():
o = EllipseI()
populate_shape(o)
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
o.rx = rdouble(3.0)
o.ry = rdouble(4.0)
o.id = rlong(1L)
return o
def mask():
o = MaskI()
populate_shape(o)
o.x = rdouble(0.0)
o.y = rdouble(0.0)
o.width = rdouble(1.0)
o.height = rdouble(2.0)
o.id = rlong(8L)
return o
def rectangle():
o = RectangleI()
populate_shape(o)
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.width = rdouble(3.0)
o.height = rdouble(4.0)
o.id = rlong(2L)
return o
def create_shape_point(x_pos, y_pos, z_pos, t_pos, point_name=None):
point = model.PointI()
point.x = rtypes.rdouble(x_pos)
point.y = rtypes.rdouble(y_pos)
point.theZ = rtypes.rint(z_pos)
point.theT = rtypes.rint(t_pos)
_set_shape_properties(point, name=point_name)
return point
def __init__(self, roicoord=ROICoordinate(), x1=0, y1=0, x2=0, y2=0):
warnings.warn("This module is deprecated as of OMERO 5.3.0",
DeprecationWarning)
ShapeData.__init__(self)
self.x1 = rdouble(x1)
self.y1 = rdouble(y1)
self.x2 = rdouble(x2)
self.y2 = rdouble(y2)
self.setCoord(roicoord)
def __init__(self, roicoord=ROICoordinate(), bytes=None,
x=0, y=0, width=0, height=0):
ShapeData.__init__(self)
self.x = rdouble(x)
self.y = rdouble(y)
self.width = rdouble(width)
self.height = rdouble(height)
self.bytesdata = bytes
self.setCoord(roicoord)
def rectangle():
o = RectangleI()
populate_shape(o)
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.width = rdouble(3.0)
o.height = rdouble(4.0)
o.id = rlong(2L)
return o
def ellipse():
o = EllipseI()
populate_shape(o)
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
o.rx = rdouble(3.0)
o.ry = rdouble(4.0)
o.id = rlong(1L)
return o
def rectangle(identity_transform):
o = RectangleI()
populate_shape(o, identity_transform)
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.width = rdouble(3.0)
o.height = rdouble(4.0)
o.id = rlong(2)
return o
def mask(identity_transform):
o = MaskI()
populate_shape(o, identity_transform)
o.x = rdouble(0.0)
o.y = rdouble(0.0)
o.width = rdouble(1.0)
o.height = rdouble(2.0)
o.id = rlong(8)
return o
def create_roi(self, img):
roi = omero.model.RoiI()
point = omero.model.PointI()
point.setCx(rdouble(1))
point.setCy(rdouble(2))
roi.addShape(point)
roi.setImage(img)
roi = self.client.getSession().getUpdateService().saveAndReturnObject(
roi)
return roi
def ellipse_with_annotations():
o = EllipseI()
populate_shape(o)
add_annotations(o)
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
o.rx = rdouble(3.0)
o.ry = rdouble(4.0)
o.id = rlong(1L)
return o
def ellipse_with_annotations():
o = EllipseI()
populate_shape(o)
add_annotations(o)
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
o.rx = rdouble(3.0)
o.ry = rdouble(4.0)
o.id = rlong(1L)
return o
def create_roi(self, img):
roi = omero.model.RoiI()
point = omero.model.PointI()
point.setX(rdouble(1))
point.setY(rdouble(2))
roi.addShape(point)
roi.setImage(img)
roi = self.client.getSession().getUpdateService().saveAndReturnObject(
roi)
return roi
def basic_line(default_id):
shape = omero.model.LineI()
shape.id = rlong(default_id)
shape.x1 = rdouble(0.0)
shape.y1 = rdouble(1.0)
shape.x2 = rdouble(2.0)
shape.y2 = rdouble(3.0)
# r=17,g=34,b=51,a=255
shape.strokeColor = rint(ctypes.c_int(0x112233FF).value)
return shape
def point():
o = PointI()
populate_shape(o)
if SCHEMA_VERSION == '2015-01':
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
else:
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(3L)
return o
def point(identity_transform):
o = PointI()
populate_shape(o, identity_transform)
if SCHEMA_VERSION == '2015-01':
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
else:
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(3)
return o
def point():
o = PointI()
populate_shape(o)
if SCHEMA_VERSION == "2015-01":
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
else:
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(3L)
return o
def test_objective_settings(self):
iid = self.create_test_image(size_c=2, session=self.sf).id.val
conn = omero.gateway.BlitzGateway(client_obj=self.client)
image = conn.getObject("Image", iid)
# Create Objective
update = conn.getUpdateService()
objective = omero.model.ObjectiveI()
objective.model = rstring("SuperZoom ABC")
objective.manufacturer = rstring("ImageCo")
objective.lensNA = rdouble(1.4)
objective.nominalMagnification = rdouble(100)
objective.calibratedMagnification = rdouble(100.1)
objective.lotNumber = rstring("123")
objective.serialNumber = rstring("abcdefX")
objective.iris = rbool(True)
immersions = list(conn.getEnumerationEntries("ImmersionI"))
corrections = list(conn.getEnumerationEntries("CorrectionI"))
objective.correction = corrections[0]._obj
objective.immersion = immersions[0]._obj
objective.instrument = update.saveAndReturnObject(
omero.model.InstrumentI())
objective = update.saveAndReturnObject(objective)
settings = omero.model.ObjectiveSettingsI()
settings.objective = objective
settings = update.saveAndReturnObject(settings)
image._obj.objectiveSettings = settings
update.saveAndReturnObject(image._obj)
# reload...
image = conn.getObject("Image", iid)
json_data = acquisitionMetadataMarshal(image)
print(json_data)
assert json_data["objectiveSettings"] == {
"id": settings.id.val,
"objective": {
"id": objective.id.val,
"model": "SuperZoom ABC",
"manufacturer": "ImageCo",
"lensNA": 1.4,
"nominalMagnification": 100,
"calibratedMagnification": 100.1,
"lotNumber": "123",
"serialNumber": "abcdefX",
"immersion": immersions[0].value,
"correction": corrections[0].value,
"iris": True
}
}
def basic_ellipse(default_id):
shape = omero.model.EllipseI()
shape.id = rlong(default_id)
shape.x = rdouble(0.0)
shape.y = rdouble(.1)
shape.radiusX = rdouble(1.0)
shape.radiusY = rdouble(.5)
# r=17,g=34,b=51,a=68
shape.fillColor = rint(ctypes.c_int(0x11223344).value)
# r=255,g=254,b=253,a=252 (i.e. negative int value = -66052)
shape.strokeColor = rint(ctypes.c_int(0xfffefdfc).value)
return shape
def addRoi(self, request, imageid):
img = self.getImage0(imageid)
if img is None:
return None
data = json.loads(request.body)
shapes = data['shapes']
x = y = l = z = t = -1
for s in shapes:
for k in s:
val = s[k]
if k == "x":
x = int(val)
elif k == "y":
y = int(val)
elif k == "width":
l = int(val)
elif k == "theZ":
z = int(val)
elif k == "theT":
t = int(val)
elif k == "fillColorAsInt":
fill = int(val)
elif k == "strokeColorAsInt":
stroke = int(val)
elif k == "strokeWidth":
strokeWidth = int(val)
if (x < 0 or y < 0 or z < 0 or t < 0 or l <= 0):
return None
updateService = self._connection.getUpdateService()
roi = RoiI()
roi.setImage(img._obj)
rect = RectangleI()
rect.x = rdouble(x)
rect.y = rdouble(y)
rect.width = rdouble(l)
rect.height = rdouble(l)
rect.theZ = rint(z)
rect.theT = rint(t)
rect.setFillColor(rint(fill))
strokeLen = LengthI()
strokeLen.setValue(strokeWidth)
strokeLen.setUnit(UnitsLength.PIXEL)
rect.setStrokeWidth(strokeLen)
rect.setStrokeColor(rint(stroke))
roi.addShape(rect)
if (updateService.saveAndReturnObject(roi) is None):
return None
return self.get_rois(imageid)
def addRoi(self, request, imageid):
img = self.getImage0(imageid)
if img is None:
return None
data = json.loads(request.body)
shapes = data['shapes']
x = y = l = z = t = -1
for s in shapes:
for k in s:
val = s[k]
if k == "x":
x = int(val)
elif k == "y":
y = int(val)
elif k == "width":
l = int(val)
elif k == "theZ":
z = int(val)
elif k == "theT":
t = int(val)
elif k == "fillColorAsInt":
fill = int(val)
elif k == "strokeColorAsInt":
stroke = int(val)
elif k == "strokeWidth":
strokeWidth = int(val)
if (x < 0 or y < 0 or z < 0 or t < 0 or l <= 0):
return None
updateService = self._connection.getUpdateService()
roi = RoiI()
roi.setImage(img._obj)
rect = RectangleI()
rect.x = rdouble(x)
rect.y = rdouble(y)
rect.width = rdouble(l)
rect.height = rdouble(l)
rect.theZ = rint(z)
rect.theT = rint(t)
rect.setFillColor(rint(fill))
strokeLen = LengthI()
strokeLen.setValue(strokeWidth)
strokeLen.setUnit(UnitsLength.PIXEL)
rect.setStrokeWidth(strokeLen)
rect.setStrokeColor(rint(stroke))
roi.addShape(rect)
if (updateService.saveAndReturnObject(roi) is None):
return None
return self.get_rois(imageid)
def create_shape_line(x1_pos, y1_pos, x2_pos, y2_pos, z_pos, t_pos,
line_name=None, stroke_color=(255, 255, 255, 255), stroke_width=1):
line = model.LineI()
line.x1 = rtypes.rdouble(x1_pos)
line.x2 = rtypes.rdouble(x2_pos)
line.y1 = rtypes.rdouble(y1_pos)
line.y2 = rtypes.rdouble(y2_pos)
line.theZ = rtypes.rint(z_pos)
line.theT = rtypes.rint(t_pos)
_set_shape_properties(line, name=line_name,
stroke_color=stroke_color,
stroke_width=stroke_width)
return line
def create_roi(img, x, y, t, text=None):
roi = omero.model.RoiI()
roi.setImage(img._obj)
rect = omero.model.RectangleI()
rect.x = rdouble(x)
rect.y = rdouble(y)
rect.width = rdouble(W)
rect.height = rdouble(H)
if text:
rect.textValue = rstring(text)
rect.theZ = rint(0)
rect.theT = rint(t)
roi.addShape(rect)
return roi
def addRect(roi, x=10, y=10, w=100, h=50, theZ=0, theT=0, label=None):
""" create and save a rectangle shape, add it to roi """
rect = omero.model.RectI()
rect.x = rdouble(x)
rect.y = rdouble(y)
rect.width = rdouble(w)
rect.height = rdouble(h)
if theZ is not None:
rect.theZ = rint(theZ)
if theT is not None:
rect.theT = rint(theT)
if label is not None:
rect.textValue = wrap(label)
rect.setRoi(roi)
roi.addShape(rect)
def testGetAttrWorks(self):
rbool(True).val
rdouble(0.0).val
rfloat(0.0).val
rint(0).val
rlong(0).val
rtime(0).val
rinternal(None).val
robject(None).val
rstring("").val
rclass("").val
rarray().val
rlist().val
rset().val
rmap().val
def to_rois(cx_column, cy_column, pixels):
unloaded_image = ImageI(pixels.image.id, False)
rois = list()
for index in range(len(cx_column.values)):
cx = rdouble(cx_column.values[index])
cy = rdouble(cy_column.values[index])
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = cx
shape.cy = cy
roi.addShape(shape)
roi.image = unloaded_image
rois.append(roi)
return rois
def ellipse():
o = EllipseI()
populate_shape(o)
if SCHEMA_VERSION == "2015-01":
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
o.rx = rdouble(3.0)
o.ry = rdouble(4.0)
else:
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.radiusX = rdouble(3.0)
o.radiusY = rdouble(4.0)
o.id = rlong(1L)
return o
def decode(self, data):
t = super(AffineTransform201501Decoder, self).decode(data)
t.setA00(rdouble(data['A00']))
t.setA10(rdouble(data['A10']))
t.setA01(rdouble(data['A01']))
t.setA11(rdouble(data['A11']))
t.setA02(rdouble(data['A02']))
t.setA12(rdouble(data['A12']))
return t
def create_roi_for_plane(session, iid, z, c, t, robject=False):
"""
Create a ROI consisting of an entire single plane
:param session: An active session
:param iid: Image ID
:param z: Z index
:param c: C index
:param t: T index
:param robject: If true return the ROI object, default is to return the ID
:return: The new ROI
"""
qs = session.getQueryService()
us = session.getUpdateService()
p = omero.sys.ParametersI()
p.addId(iid)
im = qs.findByQuery('FROM Image i join fetch i.pixels where i.id=:id', p)
assert im
px = im.getPrimaryPixels()
rect = omero.model.RectI()
rect.setX(rdouble(0))
rect.setY(rdouble(0))
rect.setWidth(rdouble(px.getSizeX().val))
rect.setHeight(rdouble(px.getSizeY().val))
rect.setTheZ(rint(z))
rect.setTheC(rint(c))
rect.setTheT(rint(t))
roi = omero.model.RoiI()
roi.addShape(rect)
roi.setImage(im)
roi = us.saveAndReturnObject(roi)
if robject:
return roi
return roi.getId().val
def create_affine_transform(a00, a10, a01, a11, a02, a12):
t = AffineTransformI()
t.setA00(rdouble(a00))
t.setA10(rdouble(a10))
t.setA01(rdouble(a01))
t.setA11(rdouble(a11))
t.setA02(rdouble(a02))
t.setA12(rdouble(a12))
return t
def parse(self):
provider = self.original_file_provider
data = provider.get_original_file_data(self.original_file)
try:
rows = list(csv.reader(data, delimiter=","))
finally:
data.close()
columns = [
ImageColumn("Image", "", list()),
RoiColumn("ROI", "", list()),
StringColumn("Type", "", 12, list()),
]
for row in rows[1:]:
wellnumber = self.well_name_to_number(row[0])
image = self.analysis_ctx.\
image_from_wellnumber(wellnumber)
# TODO: what to do with the field?!
# field = int(row[1])
# image = images[field]
roi = RoiI()
shape = PointI()
shape.cx = rdouble(float(row[2]))
shape.cy = rdouble(float(row[3]))
shape.textValue = rstring(row[4])
roi.addShape(shape)
roi.image = image.proxy()
rid = self.update_service\
.saveAndReturnIds([roi])[0]
columns[0].values.append(image.id.val)
columns[1].values.append(rid)
columns[2].values.append(row[4])
return MeasurementParsingResult([columns])
def identity_transform():
t = AffineTransformI()
if SCHEMA_VERSION == "2015-01":
t.convert_svg_transform("matrix(1 0 0 1 0 0)")
else:
t.setA00(rdouble(1))
t.setA10(rdouble(0))
t.setA01(rdouble(0))
t.setA11(rdouble(1))
t.setA02(rdouble(0))
t.setA12(rdouble(0))
t.id = rlong(8L)
return t
def translation_transform():
t = AffineTransformI()
if SCHEMA_VERSION == "2015-01":
t.convert_svg_transform("translate(3 4)")
else:
t.setA00(rdouble(1))
t.setA10(rdouble(0))
t.setA01(rdouble(0))
t.setA11(rdouble(1))
t.setA02(rdouble(3))
t.setA12(rdouble(4))
t.id = rlong(8L)
return t
def rotation_transform():
t = AffineTransformI()
if SCHEMA_VERSION == "2015-01":
t.convert_svg_transform("rotate(45 50 100)")
else:
t.setA00(rdouble(0.7071067811865476))
t.setA10(rdouble(0.7071067811865475))
t.setA01(rdouble(-0.7071067811865475))
t.setA11(rdouble(0.7071067811865476))
t.setA02(rdouble(85.35533905932736))
t.setA12(rdouble(-6.066017177982129))
t.id = rlong(8L)
return t
def scale_transform():
t = AffineTransformI()
if SCHEMA_VERSION == "2015-01":
t.convert_svg_transform("scale(1.5 2.5)")
else:
t.setA00(rdouble(1.5))
t.setA10(rdouble(0))
t.setA01(rdouble(0))
t.setA11(rdouble(2.5))
t.setA02(rdouble(0))
t.setA12(rdouble(0))
t.id = rlong(8L)
return t
def test_find_rois_for_plane(self, projection):
def getIds(objs, robject=True):
if robject:
return sorted(unwrap(o.getId()) for o in objs)
return sorted(objs)
im = self.create_image()
iid = unwrap(im.getId())
r1 = utils.create_roi_for_plane(
self.sess, unwrap(im.getId()), 2, 3, 4, robject=True)
r2 = utils.create_roi_for_plane(
self.sess, unwrap(im.getId()), 2, 4, 6, robject=True)
r3 = utils.create_roi_for_plane(
self.sess, unwrap(im.getId()), 2, 4, 8, robject=True)
r3.getShape(0).setWidth(rdouble(1))
r3 = self.sess.getUpdateService().saveAndReturnObject(r3)
r4 = utils.create_roi_for_plane(
self.sess, unwrap(im.getId()), 2, 4, 8, robject=True)
r4.addShape(omero.model.RectI())
r4 = self.sess.getUpdateService().saveAndReturnObject(r4)
rs = utils.find_rois_for_plane(self.sess, iid=iid, z=1000)
assert rs == []
rs = utils.find_rois_for_plane(
self.sess, iid=iid, fullplane=True, projection=projection)
assert getIds(rs, not projection) == getIds([r1, r2])
rs = utils.find_rois_for_plane(
self.sess, iid=iid, singleshape=False, projection=projection)
assert getIds(rs, not projection) == getIds([r1, r2, r4])
rs = utils.find_rois_for_plane(
self.sess, iid=iid, fullplane=False, projection=projection)
assert getIds(rs, not projection) == getIds([r1, r2, r3])
rs = utils.find_rois_for_plane(
self.sess, iid=iid, c=4, fullplane=False, singleshape=False,
projection=projection)
assert getIds(rs, not projection) == getIds([r2, r3, r4])
def parse_and_populate_roi(self, columns_as_list):
# First sanity check our provided columns
names = [column.name for column in columns_as_list]
log.debug('Parsing columns: %r' % names)
cells_expected = [name in names for name in self.CELLS_CG_EXPECTED]
nuclei_expected = [name in names for name in self.NUCLEI_CG_EXPECTED]
if (False in cells_expected) and (False in nuclei_expected):
log.warn("Missing CGs for InCell dataset: %r" % names)
log.warn('Removing resultant empty ROI column.')
for column in columns_as_list:
if RoiColumn == column.__class__:
columns_as_list.remove(column)
return
# Reconstruct a column name to column map
columns = dict()
for column in columns_as_list:
columns[column.name] = column
image_ids = columns['Image'].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = \
self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = \
FileAnnotationI(self.file_annotation.id.val, False)
# Parse and append ROI
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
if False in nuclei_expected:
# Cell centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Cell: cgX'].values[i]))
shape.cy = rdouble(float(columns['Cell: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
elif False in cells_expected:
# Nucleus centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Nucleus: cgX'].values[i]))
shape.cy = rdouble(float(columns['Nucleus: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
else:
raise MeasurementError('Not a nucleus or cell ROI')
if len(rois) == self.ROI_UPDATE_LIMIT:
thread_pool.add_task(self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
thread_pool.add_task(self.update_rois, rois, batches, batch_no)
thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns['ROI'].values += batches[k]
def create_image(image_id, with_pixels=False):
image_format = FormatI(1L)
image_format.value = rstring("PNG")
image = ImageI()
image.id = rlong(image_id)
image.acquisitionDate = rtime(1L)
image.archived = rbool(False)
image.description = rstring("image_description_%d" % image_id)
image.name = rstring("image_name_%d" % image_id)
image.partial = rbool(False)
image.series = rint(0)
image.format = image_format
if not with_pixels:
return image
dimension_order = DimensionOrderI(1L)
dimension_order.value = rstring("XYZCT")
pixels_type = PixelsTypeI(1L)
pixels_type.value = "bit"
pixels = PixelsI(1L)
pixels.methodology = rstring("methodology")
pixels.physicalSizeX = LengthI(1.0, UnitsLength.MICROMETER)
pixels.physicalSizeY = LengthI(2.0, UnitsLength.MICROMETER)
pixels.physicalSizeZ = LengthI(3.0, UnitsLength.MICROMETER)
pixels.sha1 = rstring("61ee8b5601a84d5154387578466c8998848ba089")
pixels.significantBits = rint(16)
pixels.sizeX = rint(1)
pixels.sizeY = rint(2)
pixels.sizeZ = rint(3)
pixels.sizeC = rint(4)
pixels.sizeT = rint(5)
pixels.timeIncrement = TimeI(1.0, UnitsTime.MILLISECOND)
pixels.waveIncrement = rdouble(2.0)
pixels.waveStart = rint(1)
pixels.dimensionOrder = dimension_order
pixels.pixelsType = pixels_type
image.addPixels(pixels)
contrast_method = ContrastMethodI(8L)
contrast_method.value = rstring("Fluorescence")
illumination = IlluminationI(1L)
illumination.value = rstring("Transmitted")
acquisition_mode = AcquisitionModeI(1L)
acquisition_mode.value = rstring("WideField")
photometric_interpretation = PhotometricInterpretationI(1L)
photometric_interpretation.value = rstring("RGB")
channel_1 = ChannelI(1L)
channel_1.alpha = rint(255)
channel_1.blue = rint(0)
channel_1.green = rint(255)
channel_1.red = rint(0)
channel_1.lookupTable = rstring("rainbow")
logical_channel_1 = LogicalChannelI(1L)
logical_channel_1.emissionWave = LengthI(509.0, UnitsLength.NANOMETER)
logical_channel_1.excitationWave = LengthI(488.0, UnitsLength.NANOMETER)
logical_channel_1.fluor = rstring("GFP")
logical_channel_1.name = rstring("GFP/488")
logical_channel_1.ndFilter = rdouble(1.0)
logical_channel_1.pinHoleSize = LengthI(1.0, UnitsLength.NANOMETER)
logical_channel_1.pockelCellSetting = rint(0)
logical_channel_1.samplesPerPixel = rint(2)
logical_channel_1.contrastMethod = contrast_method
logical_channel_1.illumination = illumination
logical_channel_1.mode = acquisition_mode
logical_channel_1.photometricInterpretation = photometric_interpretation
channel_1.logicalChannel = logical_channel_1
channel_2 = ChannelI(2L)
channel_2.alpha = rint(255)
channel_2.blue = rint(255)
channel_2.green = rint(0)
channel_2.red = rint(0)
channel_2.lookupTable = rstring("rainbow")
logical_channel_2 = LogicalChannelI(2L)
logical_channel_2.emissionWave = LengthI(470.0, UnitsLength.NANOMETER)
logical_channel_2.excitationWave = LengthI(405.0, UnitsLength.NANOMETER)
logical_channel_2.fluor = rstring("DAPI")
logical_channel_2.name = rstring("DAPI/405")
logical_channel_2.ndFilter = rdouble(1.0)
logical_channel_2.pinHoleSize = LengthI(2.0, UnitsLength.NANOMETER)
logical_channel_2.pockelCellSetting = rint(0)
logical_channel_2.samplesPerPixel = rint(2)
logical_channel_2.contrastMethod = contrast_method
logical_channel_2.illumination = illumination
logical_channel_2.mode = acquisition_mode
logical_channel_2.photometricInterpretation = photometric_interpretation
channel_2.logicalChannel = logical_channel_2
pixels.addChannel(channel_1)
pixels.addChannel(channel_2)
return image