Generating 3D Volume Projections

This script illustrates using ASPIRE’s Simulation source to generate projections of a Volume using prescribed rotations.

import logging
import os

import numpy as np

from aspire.noise import WhiteNoiseAdder
from aspire.source.simulation import Simulation
from aspire.utils import Rotation
from aspire.volume import Volume

logger = logging.getLogger(__name__)

Configure how many images we’d like to project

n_img = 10

Load our Volume data

This example starts with an mrc, which can be loaded as an ASPIRE Volume.

file_path = os.path.join(
    os.path.dirname(os.getcwd()), "data", "clean70SRibosome_vol_65p.mrc"
)
v = Volume.load(file_path, dtype=np.float64)

# Then we downsample to 60x60x60
v.downsample(60)

1 float64 volumes arranged as a (1,) stack each of size 60x60x60.

Defining rotations

We generate a collection of in-plane rotations about the z-axis.

# First get a list of angles to test
thetas = np.linspace(0, 2 * np.pi, num=n_img, endpoint=False)

# Instantiate ASPIRE's Rotation class with the set of angles.
# This will allow us to use or access the rotations in a variety of ways.
rots = Rotation.about_axis("z", thetas, dtype=np.float64)

Configure Noise

We can define controlled noise and have the Simulation apply it to our projection images.

noise_variance = 1e-10  # Normally this would be derived from a desired SNR.

# Then create a CustomNoiseAdder based on that variance, which is passed to Simulation.
white_noise_adder = WhiteNoiseAdder(var=noise_variance)

Setup Simulation Source

# Simulation will randomly shift and amplify images by default.
# Instead we define the following parameters.
shifts = np.zeros((n_img, 2))
amplitudes = np.ones(n_img)

# Create a Simulation Source object
src = Simulation(
    vols=v,  # our Volume
    L=v.resolution,  # resolution, should match Volume
    n=n_img,  # number of projection images
    angles=rots.angles,  # pass our rotations as Euler angles
    offsets=shifts,  # translations (wrt to origin)
    amplitudes=amplitudes,  # amplification ( 1 is identity)
    seed=12345,  # RNG seed for reproducibility
    dtype=v.dtype,  # match our datatype to the Volume.
    noise_adder=white_noise_adder,  # optionally prescribe noise
)

/opt/hostedtoolcache/Python/3.9.20/x64/lib/python3.9/site-packages/sphinx_gallery/gen_rst.py:783: UserWarning: Gimbal lock detected. Setting third angle to zero since it is not possible to uniquely determine all angles.
  exec(self.code, self.fake_main.__dict__)

Yield projection images from the Simulation Source

# Consume images from the source by providing
# a starting index and number of images.
# Here we generate the first 3 and peek at them.
src.images[:3].show()
src.projections[:3].show()

# Here we return the first n_img images as a numpy array.
dirty_ary = src.images[:n_img].asnumpy()

# And we have access to the clean images
clean_ary = src.projections[:n_img].asnumpy()

# Similary, the angles/rotations/shifts/amplitudes etc.

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