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from .cylinder import cylinder | ||
from .cuboid import cuboid | ||
from .cube import cube | ||
from .cone import cone | ||
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import numpy as np | ||
import einops | ||
import typer | ||
from scipy.ndimage import distance_transform_edt | ||
import mrcfile | ||
from ._cli import cli | ||
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@cli.command(name='cone') | ||
def cone( | ||
sidelength: int = typer.Option(...), | ||
cone_height: float = typer.Option(...), | ||
cone_base_diameter: float = typer.Option(...), | ||
soft_edge_width: int = typer.Option(0), | ||
mrc_voxel_size: float = typer.Option(...), | ||
output: str = typer.Option("cone.mrc") | ||
): | ||
c = sidelength // 2 | ||
center = np.array([c, c, c]) | ||
mask = np.zeros(shape=(sidelength, sidelength, sidelength), dtype=np.float32) | ||
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# 3d positions of all voxels | ||
positions = np.indices([sidelength, sidelength, sidelength]) | ||
positions = einops.rearrange(positions, 'zyx d h w -> d h w zyx') | ||
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centered = positions - center #pixels relative to center point | ||
magnitudes = np.linalg.norm(centered, axis=-1) | ||
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magnitudes = einops.rearrange(magnitudes, 'd h w -> d h w 1') | ||
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# Check for zeros in magnitudes and replace them with a small value to avoid Nan warning | ||
near_zero = 1e-8 | ||
magnitudes = np.where(magnitudes == 0, near_zero, magnitudes) | ||
normalised = centered / magnitudes | ||
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principal_axis = np.array([1, 0, 0]) | ||
dot_product = np.dot(normalised, principal_axis) | ||
angles_radians = np.arccos(dot_product) | ||
angles = np.rad2deg(angles_radians) | ||
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z_distance = centered[:, :, :, 0] # (100, 100, 100) | ||
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# Calculate the angle from the tip of the cone to the edge of the base | ||
cone_base_radius = cone_base_diameter / 2 | ||
cone_angle = np.rad2deg(np.arctan(cone_base_radius / cone_height)) | ||
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within_cone_height = z_distance < cone_height | ||
within_cone_angle = angles < cone_angle | ||
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# mask[within_cone_height] = 1 | ||
mask[np.logical_and(within_cone_height, within_cone_angle)] = 1 | ||
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# Shift the mask in the z-axis by cone_height / 2 | ||
z_shift = -int(cone_height / 2) | ||
mask = np.roll(mask, z_shift, axis=0) | ||
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distance_from_edge = distance_transform_edt(mask == 0) | ||
boundary_pixels = (distance_from_edge <= soft_edge_width) & (distance_from_edge != 0) | ||
normalised_distance_from_edge = (distance_from_edge[boundary_pixels] / soft_edge_width) * np.pi | ||
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mask[boundary_pixels] = (0.5 * np.cos(normalised_distance_from_edge) + 0.5) | ||
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mrcfile.write(output, mask, voxel_size= mrc_voxel_size, overwrite=True) | ||
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