alisterburt

# /// script
# dependencies = [
#   "torch",
#   "numpy",
#   "scipy",
#   "mrcfile",
#   "torch-transform-image",
#   "torch-affine-utils",
#   "matplotlib",
# ]

alisterburt

alisterburt

alisterburt

from itertools import combinations

import einops
import numpy as np
import torch
import torch.nn.functional as F
from torch_affine_utils import homogenise_coordinates
from torch_affine_utils.transforms_3d import Rx, Ry, Rz, T
from torch_grid_utils import dft_center
from torch_subpixel_crop import subpixel_crop_2d

alisterburt

from typing import Tuple

import mmdf
import numpy as np
import torch
from fast_histogram import histogramdd
import einops
from scipy.stats import special_ortho_group
from torch_affine_utils.transforms_3d import Rz, Ry, T
from torch_affine_utils import homogenise_coordinates

alisterburt

import datetime
import os
from collections import defaultdict
from typing import Dict, List, Any

import requests


class GitHubContributionsAnalyzer:
    def __init__(self, org_name: str, token: str = None):

alisterburt

# /// script
# requires-python = ">=3.11"
# dependencies = [
#     "numpy",
#     "scipy",
#     "starfile",
#     "napari[pyqt5]",
#     "magicgui",
#     "typer",
# ]

alisterburt

from pathlib import Path

import mrcfile
import numpy as np

image_path = "CountRef_20250327_s004101_75-4_000_Mar27_17.04.37.mrc"
image = mrcfile.read(image_path)
image = np.array(image)
image = image[:, :4031]

alisterburt

import numpy as np
from scipy.spatial.transform import Rotation as R
from torch_fourier_slice import project_3d_to_2d, backproject_2d_to_3d

tilt_angles = np.linspace(-60, 60, 41, endpoint=True)
rotation_matrices = R.from_euler('y', angles=tilt_angles, degrees=True).as_matrix()

volume = simulate_volume()
projections = project_3d_to_2d(volume, rotation_matrices)
simulated_tomogram = backproject_2d_to_3d(projections, rotation_matrices)

alisterburt

import napari
import mrcfile
import torch
from torch_fourier_slice import project_3d_to_2d

volume = torch.tensor(mrcfile.read("run_class001.mrc")).float()
projection = project_3d_to_2d(volume, rotation_matrices=torch.eye(3))

d, h, w = volume.shape