cdsousa

bl_info = {
    "name": "Julia console",
    "blender": (4, 0, 0),
    "category": "Scripting",
}

def register():
    # install JuliaCall within Blender's Python environment (if not already installed)
    import importlib
    if importlib.util.find_spec('juliacall') is None:

sharadhr

$HOME, Not So Sweet $HOME

• Preface
• 1 What is $HOME to you?
• 2 Setup
  • 2.1 Linux
    • 2.1.1 $HOME
    • 2.1.2 Dot-files and dot-directories
    • 2.1.3 XDG Base Directories
• 2.1.4 xdg-user-dirs

bohwaz

#!/usr/bin/php
<?php
// Note: this code does not contain any DRM removal, DRM removal is made by https://notabug.org/NewsGuyTor/DeDRM_tools-LCP
//
// Install steps:
// Debian/Ubuntu/Mint: apt install php-cli python3 python3-cryptodome python3-lxml zip unzip
//
// How to use?
// Just run: php lcp_download.php FILE.LCPL PASSWORD
// A new FILE_decrypted.epub will be created in the same directory

alisterburt

from pathlib import Path
from typing import List, Sequence, Tuple

import einops
import mrcfile
import numpy as np
import torch
import typer

cli = typer.Typer(name='raps_3d', no_args_is_help=True, add_completion=False)

PlethoraChutney

#!/usr/bin/env python
import numpy as np
import pandas as pd
import umap
import sys
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.preprocessing import StandardScaler
from cryosparc.dataset import Dataset

hanjinliu

import napari
import numpy as np

class MtModel:
    def __init__(
        self, 
        npf: int = 13, 
        start: int = 3, 
        space: float = 4.0, 
        radius: float = 9.8,

sneakers-the-rat

[
  "FCi27mtaKod38ztmGndn-y8NNz.r.lt6SndqGztz_ztr-ngqQm9aMo9eOnMeJntuNntu",
  "D2ei2mgqJz9b-m.mGmPqRyLNNnwmOlt7.ywiGmt-Kndr9otqRywv8o9ePmtiNmd2Sn92Tma",
  "6U7vcmPuOn9uLnMaGyM7-nLNNntv9lt6RmtaGmweOyMmJnMmSmgmOo9eOnM6LnMaRmM-Tma",
  "lXLf8owyQztiMzwqGnMz7zcNNotb7lwf.m9qGzt6Km.qMngqLndqLo9eOotaNm96Mmt6Tma",
  "FCi27y9qOnd-Ny96GmPmOmcNNzwf-lwj-m9mGztz7ytaMnM78n9v-o9ePmM6Rm9-Qn9eTma",
  "XlEDumMz7nM7-m9iGogmRmLNNyt_8lwiKz9eGm9-Pm.v7ztiLztz_o9eOnMeQnd-Sodm",
  "lXLf8yt-JywmNmPeGm9n9n8NNzgn.lt_8zwqGogz7zgn7zt6SyPr-o9eOnM6Pot2Mn9qTma",
  "FCi27zgf8mdqMmMeGnMmMy8NNz9eQlweNy.eGmMiMm96Qmgr9nMb-o9ePmtuRmt6JotmTma",
  "FCi27nwmKnMeSodeGm.z.y8NNntz.lt-PywmGy9__ngqQmtiPmtb7o9ePmteJotyJoduTma",

sneakers-the-rat

# --------------------------------------------------------------------
# Recursively find pdfs from the directory given as the first argument, 
# otherwise search the current directory.
# Use exiftool and qpdf (both must be installed and locatable on $PATH) 
# to strip all top-level metadata from PDFs.
#
# Note - This only removes file-level metadata, not any metadata
# in embedded images, etc. 
#
# Code is provided as-is, I take no responsibility for its use,

biochem-fan

RELION interoperabiity with Warp and M

This document examines how to use RELION 4.0 (beta2 as of writing) with Warp 1.09 and M 1.09 for single particle analysis.

Special thanks to Alister Burt, Pranav Shah and Dimitry Tegunov for discussion on this Twitter thread.

Download the movies

We use the RELION tutorial dataset (beta-galactosidase collected on JEOL CRYO ARM 200, a subset of EMPIAR-10204).

svpino

import numpy as np

def sigmoid(x):
    return 1 / (1 + np.exp(-x))

def neural_network(X, y):
    learning_rate = 0.1
    W1 = np.random.rand(2, 4)
    W2 = np.random.rand(4, 1)