def visual_circle_and_ellipse(insert_x, insert_y, width, length,
circle_centre):
t = np.linspace(0, 2 * np.pi)
circle = {
"x": width / 2 * np.sin(t) + circle_centre[0],
"y": width / 2 * np.cos(t) + circle_centre[1],
}
x_shift, y_shift, rotation_angle = visual_alignment_of_equivalent_ellipse(
insert_x, insert_y, width, length, None)
rotation_matrix = np.array([
[np.cos(rotation_angle), -np.sin(rotation_angle)],
[np.sin(rotation_angle),
np.cos(rotation_angle)],
])
ellipse = np.array([length / 2 * np.sin(t), width / 2 * np.cos(t)]).T
rotated_ellipse = ellipse @ rotation_matrix
translated_ellipse = rotated_ellipse + np.array([y_shift, x_shift])
ellipse = {"x": translated_ellipse[:, 1], "y": translated_ellipse[:, 0]}
return circle, ellipse
def do_rotation(x_span, y_span, angle):
"""Generate a meshgrid and rotate it by `angle` degrees."""
radians = angle * np.pi / 180
rotation_matrix = np.array([[np.cos(radians),
np.sin(radians)],
[-np.sin(radians),
np.cos(radians)]])
xx, yy = np.meshgrid(x_span, y_span, indexing="ij")
return np.einsum("ji, mni -> jmn", rotation_matrix, np.dstack([xx, yy]))
def _multi_y_locations(self) -> List:
"""List of x-locations of the sampling profiles"""
y = []
sin = np.sin(self._radians)
# extract profile for each circle radii
for radius in self._radii:
y.append(sin * radius + self.center.y)
return y
def calculate_coordinates_shell_2d(distance, distance_step_size):
"""Create points along the circumference of a circle. The spacing
between points is not larger than the defined distance_step_size
"""
amount_to_check = np.ceil(2 * np.pi * distance / distance_step_size).astype(int) + 1
theta = np.linspace(0, 2 * np.pi, amount_to_check + 1)[:-1:]
x_coords = distance * np.cos(theta)
y_coords = distance * np.sin(theta)
return (x_coords, y_coords)
def calculate_coordinates_shell_3d(distance, distance_step_size):
"""Create points along the surface of a sphere (a shell) where no gap
between points is larger than the defined distance_step_size"""
number_of_rows = np.ceil(np.pi * distance / distance_step_size).astype(int) + 1
elevation = np.linspace(0, np.pi, number_of_rows)
row_radii = distance * np.sin(elevation)
row_circumference = 2 * np.pi * row_radii
amount_in_row = np.ceil(row_circumference / distance_step_size).astype(int) + 1
x_coords = []
y_coords = []
z_coords = []
for i, phi in enumerate(elevation):
azimuth = np.linspace(0, 2 * np.pi, amount_in_row[i] + 1)[:-1:]
x_coords.append(distance * np.sin(phi) * np.cos(azimuth))
y_coords.append(distance * np.sin(phi) * np.sin(azimuth))
z_coords.append(distance * np.cos(phi) * np.ones_like(azimuth))
return (np.hstack(x_coords), np.hstack(y_coords), np.hstack(z_coords))
def rotate_coords(x, y, theta):
x_prime = x * np.cos(theta) + y * np.sin(theta)
y_prime = -x * np.sin(theta) + y * np.cos(theta)
return x_prime, y_prime
def stripes_artefact_func(x, attenuation=0.05, period=1.6):
sin_result = np.sin(x * 2 * np.pi / period)
return 1 - (sin_result + 1) / 2 * attenuation
def y_locations(self):
"""The x-locations of the profile values."""
if self._y_locations is None:
return np.sin(self._radians) * self.radius + self.center.y
else:
return self._y_locations
def image_with_overlays(
fig,
ax,
x,
y,
img,
field_transform,
bb_centre,
field_centre,
bb_diameter,
edge_lengths,
x_field_interp,
y_field_interp,
x_bb_interp,
y_bb_interp,
pixel_value_label,
units="(mm)",
):
rect_crosshair_dx = [
-edge_lengths[0] / 2,
edge_lengths[0],
-edge_lengths[0],
edge_lengths[0],
]
rect_crosshair_dy = [
-edge_lengths[1] / 2, edge_lengths[1], 0, -edge_lengths[1]
]
rect_dx = [-edge_lengths[0] / 2, 0, edge_lengths[0], 0, -edge_lengths[0]]
rect_dy = [-edge_lengths[1] / 2, edge_lengths[1], 0, -edge_lengths[1], 0]
c = ax.contourf(x, y, img, 100)
fig.colorbar(c, ax=ax, label=pixel_value_label)
ax.plot(*draw_by_diff(rect_dx, rect_dy, field_transform), "k", lw=3)
ax.plot(*draw_by_diff(rect_crosshair_dx, rect_crosshair_dy,
field_transform),
"k",
lw=1)
ax.plot(x_field_interp[0], x_field_interp[1], "k", lw=0.5, alpha=0.3)
ax.plot(y_field_interp[0], y_field_interp[1], "k", lw=0.5, alpha=0.3)
if bb_centre is not None:
bb_radius = bb_diameter / 2
bb_crosshair = np.array([-bb_radius, bb_radius])
t = np.linspace(0, 2 * np.pi)
circle_x_origin = bb_diameter / 2 * np.sin(t)
circle_y_origin = bb_diameter / 2 * np.cos(t)
circle_x = circle_x_origin + bb_centre[0]
circle_y = circle_y_origin + bb_centre[1]
ax.plot([bb_centre[0]] * 2, bb_crosshair + bb_centre[1], "k", lw=1)
ax.plot(bb_crosshair + bb_centre[0], [bb_centre[1]] * 2, "k", lw=1)
ax.plot(circle_x, circle_y, "k", lw=3)
ax.plot(x_bb_interp[0], x_bb_interp[1], "k", lw=0.5, alpha=0.3)
ax.plot(y_bb_interp[0], y_bb_interp[1], "k", lw=0.5, alpha=0.3)
ax.plot(
[field_centre[0], bb_centre[0]],
[field_centre[1], bb_centre[1]],
c="C3",
lw=3,
)
ax.axis("equal")
long_edge = np.sqrt(np.sum((np.array(edge_lengths))**2))
long_edge_fraction = long_edge * 0.6
ax.set_xlim([
field_centre[0] - long_edge_fraction,
field_centre[0] + long_edge_fraction
])
ax.set_ylim([
field_centre[1] - long_edge_fraction,
field_centre[1] + long_edge_fraction
])
ax.set_xlabel(f"iView panel absolute x-pos {units}")
ax.set_ylabel(f"iView panel absolute y-pos {units}")