alisterburt

#!/bin/bash
# Set DYNAMO_ROOT and WORKING_DIR
WORKING_DIR=${PWD}
DYNAMO_ROOT="/opt/dynamo/1.1.514"

# Add CUDA installation to LD_LIBRARY_PATH
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64

# Activate dynamo in the current shell environment
cd ${DYNAMO_ROOT}

alisterburt

function dipoles2vesicles(catalogue_name, distance_between_particles)
%%% to be run in the folder which holds your catalogue
%%%
%%% catalogue name - name of catalogue containing your dipoleSet models
%%% distance_between_particles - expected distance between particles in px
%%% (output points will be oversampled relative to this value)
%%%
%%% if you want to restart - !rm */*/*/*/*rawVesicle*.omd
    p = [catalogue_name,'/tomograms/*/models/*.omd'];
    model_files = dir(p);

alisterburt

#!/usr/bin/env python
import click
import starfile
import matplotlib.pyplot as plt
import mplstereonet

@click.command()
@click.option('--star_file', '-s', prompt='Input STAR file', type=click.Path(exists=True))
def star_orientation_distribution(star_file):
    star = starfile.read(star_file)

alisterburt

#!/usr/bin/env python

import click

@click.command()
@click.argument('resolution_angstroms', required=False)
@click.argument('angstroms_per_pixel', required=False)
@click.argument('box_size', required=False)
@click.option('-res',
              '--resolution_angstroms',

alisterburt

#!/usr/bin/env python

import click

@click.command()
@click.argument('fourier_pixel_extent', required=False)
@click.argument('angstroms_per_pixel', required=False)
@click.argument('box_size', required=False)
@click.option('-fpix',
              '--fourier_pixel_extent',

alisterburt

#!/usr/bin/env python
import click
import starfile

@click.command()
@click.option('--star_file', prompt='Input STAR file')
@click.option('--class_idx', type=int, prompt='Class number')
def class_select(star_file, class_idx):
	star = starfile.read(star_file)
	subset = star[star['rlnClassNumber']==class_idx]

alisterburt

function dms2mod(markers_dms_file, model_file, image_file)
    %%%%% Convert Dynamo markers (.dms files) into IMOD format model files (.mod)
    %%%%% Requires MATLAB >= r2019a
    %%%%% Requires Dynamo >= 1.1.478
    %%%%% Requires IMOD >= 4.10.37
    %%% Reading marker file
    m = dread(markers_dms_file);
    
    %%% Extract useful objects
    markers = m.shapes;

alisterburt

function table = vll2table(vll_file)
    %%% Convert a vll file into a table and corresponding tomogram table-map file
    
    % Read volume list file
    volume_list = ptdb.volumelisttext2object(vll_file).volumes;
    
    % Prepare output filenames
    table_file_name = strrep(vll_file, '.vll', '.tbl');
    table_map_file_name = strrep(vll_file, '.vll', '_tablemap.doc');
    

alisterburt

import numpy as np

def align(a, b):
    """
    Find r such that r @ a = b when a and b are normalised vectors
    :param a: normalised vector of length 3
    :param b: normalised vector of length 3
    :return: rotation matrix
    """
    # cross product to find axis about which rotation should occur

alisterburt

def align_vectorised(a: np.ndarray, b: np.ndarray):
    """
    Find array of rotation matrices r such that r @ a = b when a and b are arrays of normalised vectors
    implementation designed to avoid trig calls
    based on https://iquilezles.org/www/articles/noacos/noacos.htm
    :param a: normalised vector(s) of length 3
    :param b: normalised vector(s) of length 3
    :return: rotation matrix
    """
    # setup