alexlib

from time import sleep

import napari
import numpy as np
from napari.qt.threading import thread_worker

viewer = napari.Viewer()
bbox_layer = viewer.add_points(
    [[-1, -1], [-1, 1], [1, -1], [1, 1]], face_color='green')
points_layer = viewer.add_points([0, 0], face_color='magenta')

alexlib

from time import sleep
from enum import Enum

import napari
import numpy as np
import psygnal
from napari.qt.threading import thread_worker

BOARD_SIZE = 14
INITIAL_SNAKE_LENGTH = 4

alexlib

alexlib

from pathlib import Path

import mrcfile
import napari
import numpy as np
from magicgui import magicgui

OUTPUT_DIRECTORY = 'picking'
Path(OUTPUT_DIRECTORY).mkdir(exist_ok=True, parents=True)

alexlib

from pathlib import Path
from typing import Dict
from enum import Enum

import napari
import numpy as np
import mrcfile
import pandas as pd
import starfile
import eulerangles

alexlib

import numpy as np
import mrcfile
import starfile
from eulerangles import euler2matrix, invert_rotation_matrices
import napari
from fuzzywuzzy import fuzz, process

# Read in data
particle_file = 'particles_10.00Apx.star'
volume_file = 'TS_01.mrc_10.00Apx.mrc'

alexlib

name: CI

on:
  push:
    branches:
    - main
  pull_request:
    branches:
    - main

alexlib

Packing Conda Environments

You must be using conda for this approach. You will need conda installed on the Source machine and the Target machine. The Source machine must have an internet connection, the Target does not. The OS in both environments must match; no going from macOS to Win10 for example.

1. (Source) Install conda-pack in your base python environment.

conda install -c conda-forge conda-pack

alexlib

import numpy as np
import pandas as pd


# dropping tennis ball
def problem1():

    dt = 1

    F = np.matrix([[1, dt, dt**2/2],

alexlib

"""
Different functions to get pairwise distance in cubic box with PBC

Args:
    positions: the positions of particles, shape (N, dim)
    box (int or float): the size of the box

Return:
    np.ndarray: the pair-wise distances, shape (N, N)
"""