Satrajit Ghosh satra

I hereby claim:

To claim this, I am signing this object:

	from dandi.dandiapi import DandiAPIClient
	from dandischema.models import Resource, RelationType
	from getpass import getpass
	import pandas as pd
	import json

	token = getpass() # Enter dandi api token when prompted

	df = pd.read_csv("dandi_assets_l1.csv")

	{
	"title": "Biosample",
	"description": "Schema for submitting a biosample.",
	"comment": "For cultured samples this object represents unique growths or culture harvests.",
	"id": "/profiles/biosample.json",
	"$schema": "http://json-schema.org/draft-04/schema#",
	"type": "object",
	"required": [
	"award",
	"lab",

	import math
	import numpy as np
	import nibabel as nb
	import zarr
	from numcodecs import Blosc
	from ome_zarr.writer import write_multiscale
	from skimage.transform import pyramid_gaussian

	img = nb.load("sub-S01_T2w.nii.gz")
	data = img.get_fdata()

	from numcodecs import Blosc
	import numpy as np
	from pathlib import Path
	from rechunker import rechunk
	import sys
	from tempfile import TemporaryDirectory
	import zarr
	import click
	from pydra.mark import task, annotate
	import pydra as pyd

	# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,

	from selenium import webdriver
	import chromedriver_binary
	from selenium.webdriver.common.by import By
	from selenium.webdriver.support.ui import WebDriverWait
	from selenium.webdriver.support import expected_conditions as EC
	from selenium.common.exceptions import TimeoutException
	from getpass import getpass


	class DANDILogin:

	docker run -it --rm kaczmarj/neurodocker:master generate docker \
	--base neurodebian:stretch \
	--pkg-manager apt \
	--install graphviz tree git-annex-standalone vim \
	emacs-nox nano less ncdu tig sed build-essential \
	libsm-dev libx11-dev libxt-dev libxext-dev libglu1-mesa \
	--freesurfer version=6.0.0-min \
	--ants version=b43df4bfc8 method=source cmake_opts='-DBUILD_SHARED_LIBS=ON' make_opts='-j 4'\
	--run 'ln -s /usr/lib/x86_64-linux-gnu /usr/lib64' \
	--miniconda \


	import sklearn
	from sklearn.base import BaseEstimator
	from sklearn.base import TransformerMixin

	class CustFsNoiseWinnow(BaseEstimator, TransformerMixin):
	"""Remove features with less importance than a noise feature"""
	import scipy
	import scipy.stats
	import numpy as np