def __init__(
self,
data_source,
conditionals,
ds=None,
field_parameters=None,
base_object=None,
locals=None,
):
if locals is None:
locals = {}
validate_object(data_source, YTSelectionContainer)
validate_sequence(conditionals)
for condition in conditionals:
validate_object(condition, str)
validate_object(ds, Dataset)
validate_object(field_parameters, dict)
validate_object(base_object, YTSelectionContainer)
self.conditionals = list(always_iterable(conditionals))
if isinstance(data_source, YTCutRegion):
# If the source is also a cut region, add its conditionals
# and set the source to be its source.
# Preserve order of conditionals.
self.conditionals = data_source.conditionals + self.conditionals
data_source = data_source.base_object
super().__init__(
data_source.center, ds, field_parameters, data_source=data_source
)
self.filter_fields = self._check_filter_fields()
self.base_object = data_source
self.locals = locals
self._selector = None
def __init__(self,
axis,
coords,
ds=None,
field_parameters=None,
data_source=None):
validate_axis(ds, axis)
validate_sequence(coords)
for c in coords:
validate_float(c)
validate_object(ds, Dataset)
validate_object(field_parameters, dict)
validate_object(data_source, YTSelectionContainer)
super().__init__(ds, field_parameters, data_source)
self.axis = fix_axis(axis, self.ds)
xax = self.ds.coordinates.x_axis[self.axis]
yax = self.ds.coordinates.y_axis[self.axis]
self.px_ax = xax
self.py_ax = yax
# Even though we may not be using x,y,z we use them here.
self.px_dx = f"d{'xyz'[self.px_ax]}"
self.py_dx = f"d{'xyz'[self.py_ax]}"
# Convert coordinates to code length.
if isinstance(coords[0], YTQuantity):
self.px = self.ds.quan(coords[0]).to("code_length")
else:
self.px = self.ds.quan(coords[0], "code_length")
if isinstance(coords[1], YTQuantity):
self.py = self.ds.quan(coords[1]).to("code_length")
else:
self.py = self.ds.quan(coords[1], "code_length")
self.sort_by = "xyz"[self.axis]
def __init__(
self,
center,
normal,
radius,
height,
fields=None,
ds=None,
field_parameters=None,
data_source=None,
):
validate_center(center)
validate_3d_array(normal)
validate_float(radius)
validate_float(height)
validate_sequence(fields)
validate_object(ds, Dataset)
validate_object(field_parameters, dict)
validate_object(data_source, YTSelectionContainer)
YTSelectionContainer3D.__init__(self, center, ds, field_parameters,
data_source)
self._norm_vec = np.array(normal) / np.sqrt(np.dot(normal, normal))
self.set_field_parameter("normal", self._norm_vec)
self.set_field_parameter("center", self.center)
self.height = fix_length(height, self.ds)
self.radius = fix_length(radius, self.ds)
self._d = -1.0 * np.dot(self._norm_vec, self.center)
def __init__(
self,
center,
left_edge,
right_edge,
fields=None,
ds=None,
field_parameters=None,
data_source=None,
):
if center is not None:
validate_center(center)
validate_3d_array(left_edge)
validate_3d_array(right_edge)
validate_sequence(fields)
validate_object(ds, Dataset)
validate_object(field_parameters, dict)
validate_object(data_source, YTSelectionContainer)
YTSelectionContainer3D.__init__(self, center, ds, field_parameters, data_source)
if not isinstance(left_edge, YTArray):
self.left_edge = self.ds.arr(left_edge, "code_length", dtype="float64")
else:
# need to assign this dataset's unit registry to the YTArray
self.left_edge = self.ds.arr(left_edge.copy(), dtype="float64")
if not isinstance(right_edge, YTArray):
self.right_edge = self.ds.arr(right_edge, "code_length", dtype="float64")
else:
# need to assign this dataset's unit registry to the YTArray
self.right_edge = self.ds.arr(right_edge.copy(), dtype="float64")
def __init__(self, data_objects, ds=None, field_parameters=None, data_source=None):
validate_sequence(data_objects)
for obj in data_objects:
validate_object(obj, YTSelectionContainer)
validate_object(ds, Dataset)
validate_object(field_parameters, dict)
validate_object(data_source, YTSelectionContainer)
YTSelectionContainer3D.__init__(self, None, ds, field_parameters, data_source)
self.data_objects = list(always_iterable(data_objects))
def __init__(self,
obj_list,
ds=None,
field_parameters=None,
data_source=None,
center=None):
validate_sequence(obj_list)
validate_object(ds, Dataset)
validate_object(field_parameters, dict)
validate_object(data_source, YTSelectionContainer)
if center is not None:
validate_center(center)
YTSelectionContainer3D.__init__(self, center, ds, field_parameters,
data_source)
self._obj_ids = np.array([o.id - o._id_offset for o in obj_list],
dtype="int64")
self._obj_list = obj_list
def __init__(
self,
center,
A,
B,
C,
e0,
tilt,
fields=None,
ds=None,
field_parameters=None,
data_source=None,
):
validate_center(center)
validate_float(A)
validate_float(B)
validate_float(C)
validate_3d_array(e0)
validate_float(tilt)
validate_sequence(fields)
validate_object(ds, Dataset)
validate_object(field_parameters, dict)
validate_object(data_source, YTSelectionContainer)
YTSelectionContainer3D.__init__(self, center, ds, field_parameters, data_source)
# make sure the magnitudes of semi-major axes are in order
if A < B or B < C:
raise YTEllipsoidOrdering(ds, A, B, C)
# make sure the smallest side is not smaller than dx
self._A = self.ds.quan(A, "code_length")
self._B = self.ds.quan(B, "code_length")
self._C = self.ds.quan(C, "code_length")
if self._C < self.index.get_smallest_dx():
raise YTSphereTooSmall(self.ds, self._C, self.index.get_smallest_dx())
self._e0 = e0 = e0 / (e0 ** 2.0).sum() ** 0.5
self._tilt = tilt
# find the t1 angle needed to rotate about z axis to align e0 to x
t1 = np.arctan(e0[1] / e0[0])
# rotate e0 by -t1
RZ = get_rotation_matrix(t1, (0, 0, 1)).transpose()
r1 = (e0 * RZ).sum(axis=1)
# find the t2 angle needed to rotate about y axis to align e0 to x
t2 = np.arctan(-r1[2] / r1[0])
"""
calculate the original e1
given the tilt about the x axis when e0 was aligned
to x after t1, t2 rotations about z, y
"""
RX = get_rotation_matrix(-tilt, (1, 0, 0)).transpose()
RY = get_rotation_matrix(-t2, (0, 1, 0)).transpose()
RZ = get_rotation_matrix(-t1, (0, 0, 1)).transpose()
e1 = ((0, 1, 0) * RX).sum(axis=1)
e1 = (e1 * RY).sum(axis=1)
e1 = (e1 * RZ).sum(axis=1)
e2 = np.cross(e0, e1)
self._e1 = e1
self._e2 = e2
self.set_field_parameter("A", A)
self.set_field_parameter("B", B)
self.set_field_parameter("C", C)
self.set_field_parameter("e0", e0)
self.set_field_parameter("e1", e1)
self.set_field_parameter("e2", e2)
