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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: |
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#!/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 |
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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) |
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#!/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 |
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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, |
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[ | |
"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", |
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# -------------------------------------------------------------------- | |
# 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, |
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.
We use the RELION tutorial dataset (beta-galactosidase collected on JEOL CRYO ARM 200, a subset of EMPIAR-10204).
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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) |
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