4970 lines
1.2 MiB
Plaintext
4970 lines
1.2 MiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "b2e0202e-fa47-4462-91f5-a066a2d3c01b",
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"metadata": {},
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"source": [
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"# Segment water in GDL to quantify influence of liquid water on electrochemistry"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2fe5eb68-19b3-4ea6-9a01-d8c6c4c9da25",
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"metadata": {},
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"source": [
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"This is an example notebook how I segmented the water within the cathode GDL. Segmentation of the membrane cavities works analogous with different cropping and label sets.\n",
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"There was an update of dask that broke the code. The feature stack setup and training functionalities have been fixed, but the full volume segmentation has yet to be reviewed. However, there is no reason why this should not work after some adjustments, probably even much better than before."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "18d12790-31e0-4677-8f13-abbf958444a3",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# modules\n",
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"import os\n",
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"import xarray as xr\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import dask\n",
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"import dask.array\n",
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"from scipy import ndimage\n",
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"from skimage import filters, feature, io\n",
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"from skimage.morphology import disk,ball\n",
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"import sys\n",
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"from itertools import combinations_with_replacement\n",
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"import pickle\n",
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"import imageio\n",
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"import json\n",
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"from dask.distributed import Client, LocalCluster\n",
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"import socket\n",
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"import subprocess\n",
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"import gc\n",
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"import h5py\n",
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"\n",
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"# get the ML functions, TODO: make a library once it works/is in a stable state\n",
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"pytrainpath = '/mpc/homes/fische_r/lib/pytrainseg' #path of git repo\n",
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"cwd = os.getcwd()\n",
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"os.chdir(pytrainpath)\n",
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"from filter_functions import image_filter\n",
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"import training_functions as tfs\n",
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"from training_functions import train_segmentation\n",
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"from segmentation import segmentation\n",
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"pytrain_git_sha = subprocess.check_output(['git', 'rev-parse', '--short', 'HEAD']).decode().strip()\n",
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"os.chdir(cwd)\n",
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"\n",
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"#paths\n",
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"host = socket.gethostname()\n",
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"if host == 'mpc2959.psi.ch':\n",
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" gitpath = '/mpc/homes/fische_r/lib/co2ely-tomcat'\n",
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" toppath = '/mpc/homes/fische_r/NAS/DASCOELY'\n",
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" toppathSSD = '/mnt/SSD/fische_r/COELY'\n",
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" temppath = '/mnt/SSD/fische_r/tmp'\n",
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" temppath_2 = '/mpc/homes/fische_r/NAS/tmp'\n",
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" training_path = '/mpc/homes/fische_r/NAS/DASCOELY/processing/05_water_GDL_ML/'\n",
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" memlim = '420GB' #1/2 of available RAM for 2 workers\n",
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"else:\n",
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" print('host '+host+' currently not supported')\n",
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"\n",
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"# fetch githash\n",
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"cwd = os.getcwd()\n",
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"os.chdir(gitpath)\n",
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"git_sha = subprocess.check_output(['git', 'rev-parse', '--short', 'HEAD']).decode().strip()\n",
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"githash = subprocess.check_output(['git', 'rev-parse', 'HEAD']).decode().strip()\n",
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"os.chdir(cwd)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4c87d6c7-b66b-4760-9514-3bd771c1b981",
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"metadata": {},
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"source": [
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"### functionalities for interactive training"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "5e71b819-2866-4d0c-b3ed-01f137baa0a5",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"from ipywidgets import Image\n",
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"from ipywidgets import ColorPicker, IntSlider, link, AppLayout, HBox\n",
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"from ipycanvas import hold_canvas, MultiCanvas #RoughCanvas,Canvas,\n",
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"\n",
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"def on_mouse_down(x, y):\n",
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" global drawing\n",
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" global position\n",
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" global shape\n",
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" drawing = True\n",
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" position = (x, y)\n",
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" shape = [position]\n",
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"\n",
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"def on_mouse_move(x, y):\n",
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" global drawing\n",
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" global position\n",
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" global shape\n",
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" if not drawing:\n",
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" return\n",
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" with hold_canvas():\n",
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" canvas.stroke_line(position[0], position[1], x, y)\n",
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" position = (x, y)\n",
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" shape.append(position)\n",
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"\n",
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"def on_mouse_up(x, y):\n",
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" global drawing\n",
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" global positiondu\n",
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" global shape\n",
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" drawing = False\n",
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" with hold_canvas():\n",
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" canvas.stroke_line(position[0], position[1], x, y)\n",
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" canvas.fill_polygon(shape)\n",
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" shape = []\n",
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" \n",
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"def display_feature(i, TS):\n",
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" print('selected '+TS.feature_names[i])\n",
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" im = TS.current_feat_stack[:,:,i]\n",
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" im8 = im-im.min()\n",
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" im8 = im8/im8.max()*255\n",
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" return im8"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e0cca3d3-dbb1-4064-93cb-996b23edb5c0",
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"metadata": {},
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"source": [
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"### fire up dask"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "0fbdc6da-382c-4123-9fef-e621f9049bf3",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2023-05-16 09:28:37,202 - distributed.diskutils - INFO - Found stale lock file and directory '/mnt/SSD/fische_r/tmp/dask-worker-space/worker-aqx4i1f3', purging\n",
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"/mpc/homes/fische_r/miniconda3/lib/python3.10/contextlib.py:142: UserWarning: Creating scratch directories is taking a surprisingly long time. (3.69s) This is often due to running workers on a network file system. Consider specifying a local-directory to point workers to write scratch data to a local disk.\n",
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" next(self.gen)\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Dashboard at http://127.0.0.1:35000/status\n"
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]
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}
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],
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"source": [
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"dask.config.config['temporary-directory'] = temppath\n",
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"def boot_client():\n",
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" tempfolder = temppath #a big SSD is a major adavantage to allow spill to disk and still be efficient. large dataset might crash with too small SSD or be slow with normal HDD\n",
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"# tempfolder = temppath_2\n",
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"# dask.config.config['distributed']['worker']['memory']['recent-to-old-time'] = '200000s'\n",
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"\n",
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"# here you have the option to use a virtual cluster or even slurm on ra (not attempted yet)\n",
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" cluster = LocalCluster(dashboard_address=':35000', memory_limit = memlim, n_workers=2) #settings optimised for mpc2959, play around if needed, if you know nothing else is using RAM then you can almost go to the limit\n",
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"# # maybe less workers with more threads makes better use of shared memory \n",
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"\n",
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"# # scheduler_port = 'tcp://129.129.188.222:8786' #<-- if scheduler on mpc2959; scheduler on mpc2053 -> 'tcp://129.129.188.248:8786'\n",
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"# # cluster = scheduler_port\n",
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"\n",
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" client = Client(cluster)\n",
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"# # client.amm.start()\n",
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" print('Dashboard at '+client.dashboard_link)\n",
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" return client, cluster"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "476bc714-b361-4569-bbf1-eb037a817e06",
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"metadata": {},
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"outputs": [],
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"source": [
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"def reboot_client(client, cluster):\n",
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" client.shutdown()\n",
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" client = Client(cluster)\n",
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" return client"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c8ed9556-09fb-480d-b670-d8d5f5e81e5f",
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"metadata": {},
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"outputs": [],
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"source": [
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"client, cluster = boot_client()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "005683fe-27b7-419d-9c95-be3c4f59e2a1",
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"metadata": {},
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"source": [
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"## Test ROI selection"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4228967c-0755-4d36-8ba3-504228c1bac8",
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"metadata": {},
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"source": [
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"## Data preparation"
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]
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},
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{
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"cell_type": "markdown",
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"id": "83192312-2e41-4f33-a975-e429faae688d",
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"metadata": {},
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"source": [
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"### create dask array"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "b7a4e7e9-9ea6-4c56-b448-26dbcfe9b1d9",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"sample = '4'\n",
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"file = '02_'+sample+'_registered_3p1D.nc'\n",
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"imagepath = os.path.join(path_02_4D, file)\n",
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"data = xr.open_dataset(imagepath)\n",
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"images = [im for im in data.keys() if im[3:7] == 'imag']\n",
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"images.sort()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "bbf80f40-46cf-459c-abda-2718e90cfb98",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"t_utc = data['t_utc'].data\n",
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"time = data['time'].data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "21b369cd-e7b3-48f1-a203-9bb1d5f26f82",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# define some cropping dimensions\n",
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"\n",
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"\n",
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"# here with obtained cropping data from file\n",
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"jsonpath = os.path.join(training_path, 'cathode_cropping_and_aligning.json')\n",
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"crop_dict = json.load(open(jsonpath, 'r'))\n",
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"\n",
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"(a,b,c,d) = crop_dict[sample]\n",
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"(e,f) = (50,-50)\n",
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"\n",
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"#corrections to crop coordinates\n",
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"# f = e+1750\n",
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"# e = e+100"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9b872278-ed21-4141-be31-ae5c8525325c",
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"metadata": {},
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"source": [
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"##### define border to crop to GDL"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "eacfa329-d767-4c4a-bdfc-b3e4bc182c39",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<matplotlib.image.AxesImage at 0x7f5fa9009b70>"
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]
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},
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"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1600x900 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"GDL_crop = 0\n",
|
|
"plt.figure(figsize=(16,9))\n",
|
|
"plt.imshow(test_im1[600,GDL_crop:, :], vmin =10000, vmax=15000, cmap='gray')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "f646f886-19e4-4028-a861-de0bd61db43e",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"(750, 340, 1916, 71) (750, 340, 1916)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"shp = data[images[4]][a:b, c:d, e:f].shape\n",
|
|
"# shp = data[images[4]][a:b, c+GDL_crop:d, e:f].shape\n",
|
|
"shp = shp + (len(images),)\n",
|
|
"print(shp, test_im1[:,GDL_crop:, :].shape)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
|
"id": "d847d280-7333-4a58-830f-6f3a0b4afe9b",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"data.close()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "4ac048fe-ec41-4d50-b9c7-bc07b27700d7",
|
|
"metadata": {},
|
|
"source": [
|
|
"### let dask load the data\n",
|
|
"needs to be a 4D-hdf5, for example created with xarray as .nc"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "5ff4cbd5-3ca7-459b-a7db-acfad42ee745",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"filename = '02_'+sample+'_registered_4D.nc'\n",
|
|
"imagepath = os.path.join(path_02_4D, filename)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "47fbabf3-49ed-46e5-addf-aae14f615123",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"file = h5py.File(imagepath)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "1284e29a-d99a-45b7-b9e3-4b31d4fb019d",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"da = dask.array.from_array(file['image_data'][a:b, c+GDL_crop:d, e:f], chunks= chunks) #do the cropping within the dask array creation, otherwise dask only adds a graph layer and might crash ?!"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "6b7ee45c-59e9-44de-9aeb-f91018510c72",
|
|
"metadata": {},
|
|
"source": [
|
|
"### get data into image filter class"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 24,
|
|
"id": "a68eb724-7ecc-44e0-a053-71e22166b561",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# TODO: include this routine into pytrainseg\n",
|
|
"\n",
|
|
"IF = image_filter(sigmas = [2,4,6])# sigmas define the kernels to be used for the Gaussian Blurs\n",
|
|
"IF.data = da\n",
|
|
"shp = da.shape\n",
|
|
"coords = {'x': np.arange(shp[0]), 'y': np.arange(shp[1]), 'z': np.arange(shp[2]), 'time': np.arange(shp[3])}\n",
|
|
"IF.original_dataset = xr.Dataset({'tomo': (['x','y','z','time'], da)},\n",
|
|
" coords = coords\n",
|
|
" )\n",
|
|
"# IF.data = IF.data.rechunk('auto')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "512b2d36-9911-4cb8-94e0-37de5efc0a1e",
|
|
"metadata": {},
|
|
"source": [
|
|
"### prepare features"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"id": "43a7e59e-b6d6-4bc7-b175-63e6545de742",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"IF.prepare()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 26,
|
|
"id": "470dbe8f-f3f4-45b6-a829-3a0fe170d23f",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"IF.stack_features()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"id": "9b64faf6-38bb-4d89-9bdf-60672831c5f3",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<table>\n",
|
|
" <tr>\n",
|
|
" <td>\n",
|
|
" <table style=\"border-collapse: collapse;\">\n",
|
|
" <thead>\n",
|
|
" <tr>\n",
|
|
" <td> </td>\n",
|
|
" <th> Array </th>\n",
|
|
" <th> Chunk </th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Bytes </th>\n",
|
|
" <td> 16.15 TiB </td>\n",
|
|
" <td> 25.27 MiB </td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (750, 340, 1916, 71, 64) </td>\n",
|
|
" <td> (36, 36, 36, 71, 1) </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Dask graph </th>\n",
|
|
" <td colspan=\"2\"> 903168 chunks in 465 graph layers </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Data type </th>\n",
|
|
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
" </table>\n",
|
|
" </td>\n",
|
|
" <td>\n",
|
|
" <svg width=\"374\" height=\"153\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
|
|
"\n",
|
|
" <!-- Horizontal lines -->\n",
|
|
" <line x1=\"0\" y1=\"0\" x2=\"41\" y2=\"0\" style=\"stroke-width:2\" />\n",
|
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" <line x1=\"0\" y1=\"2\" x2=\"41\" y2=\"2\" />\n",
|
|
" <line x1=\"0\" y1=\"4\" x2=\"41\" y2=\"4\" />\n",
|
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" <line x1=\"0\" y1=\"6\" x2=\"41\" y2=\"6\" />\n",
|
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" <line x1=\"0\" y1=\"9\" x2=\"41\" y2=\"9\" />\n",
|
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" <line x1=\"0\" y1=\"11\" x2=\"41\" y2=\"11\" />\n",
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"\n",
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" <!-- Text -->\n",
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" <text x=\"197.606718\" y=\"123.255445\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >64</text>\n",
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" <text x=\"233.625200\" y=\"86.921840\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,233.625200,86.921840)\">71</text>\n",
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" <text x=\"136.294118\" y=\"87.961328\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,136.294118,87.961328)\">1916</text>\n",
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"</svg>\n",
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" </td>\n",
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|
" </tr>\n",
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"</table>"
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],
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|
"text/plain": [
|
|
"dask.array<stack, shape=(750, 340, 1916, 71, 64), dtype=float64, chunksize=(36, 36, 36, 71, 1), chunktype=numpy.ndarray>"
|
|
]
|
|
},
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"IF.feature_stack #shows the feature stack"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"id": "211364a8-dc50-41c8-be71-c79c42df2908",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"IF.make_xarray_nc()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "da251274-27b9-4f8e-854d-6f0bec7d173f",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Training"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "e9e2123a-f35f-4edb-84c5-d969ad98daec",
|
|
"metadata": {},
|
|
"source": [
|
|
"### set up objects"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 31,
|
|
"id": "676bffbb-b75a-4b65-bebe-ecdf33cdb881",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"training_path_sample = os.path.join(training_path, sample)\n",
|
|
"if not os.path.exists(training_path_sample):\n",
|
|
" os.mkdir(training_path_sample)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 33,
|
|
"id": "a8d8d911-acaa-49e4-8e8a-6a57e9d7965d",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"TS = train_segmentation(training_path=training_path_sample)\n",
|
|
"TS.client = client\n",
|
|
"IF.client = client\n",
|
|
"TS.cluster = cluster\n",
|
|
"IF.cluster = cluster"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 34,
|
|
"id": "a91b1361-1e5a-4e39-a49c-40c3d999577b",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"TS.import_lazy_feature_data(IF.result, IF.original_dataset)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"id": "829ffdcb-a08b-4474-97c3-db43c082543d",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"IF.combined_feature_names = list(IF.feature_names) + list(IF.feature_names_time_independent)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 36,
|
|
"id": "9c2c411a-18e6-4b7a-8aa1-c3989d4a487d",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"TS.combined_feature_names = IF.combined_feature_names"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c6fcd46d-9e4d-4167-ad48-39feb2d2d8b1",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"### interactive training"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "860f4a50-d113-4f1a-a0e2-3cc24303dcea",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### check for existing training sets\n",
|
|
"these training sets only work if the cropping has not changed"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"id": "a66df7f4-ad56-40ca-8f36-147bf642753d",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"['label_image_x_157_time_5_.tif',\n",
|
|
" 'label_image_x_172_time_17_.tif',\n",
|
|
" 'label_image_x_172_time_2_.tif',\n",
|
|
" 'label_image_x_252_time_0_.tif',\n",
|
|
" 'label_image_x_264_time_29_.tif',\n",
|
|
" 'label_image_x_270_time_50_.tif',\n",
|
|
" 'label_image_x_307_time_25_.tif',\n",
|
|
" 'label_image_x_368_time_45_.tif',\n",
|
|
" 'label_image_x_456_time_0_.tif',\n",
|
|
" 'label_image_x_503_time_15_.tif',\n",
|
|
" 'label_image_x_531_time_50_.tif',\n",
|
|
" 'label_image_y_241_time_0_.tif',\n",
|
|
" 'label_image_y_245_time_8_.tif',\n",
|
|
" 'label_image_y_250_time_23_.tif',\n",
|
|
" 'label_image_y_250_time_33_.tif',\n",
|
|
" 'label_image_y_255_time_20_.tif',\n",
|
|
" 'label_image_y_255_time_40_.tif',\n",
|
|
" 'label_image_y_255_time_64_.tif',\n",
|
|
" 'label_image_y_270_time_47_.tif',\n",
|
|
" 'label_image_y_280_time_57_.tif',\n",
|
|
" 'label_image_y_71_time_27_.tif',\n",
|
|
" 'label_image_z_307_time_0_.tif',\n",
|
|
" 'label_image_z_307_time_10_.tif',\n",
|
|
" 'label_image_z_307_time_25_.tif',\n",
|
|
" 'label_image_z_320_time_10_.tif',\n",
|
|
" 'label_image_z_320_time_30_.tif',\n",
|
|
" 'label_image_z_320_time_45_.tif',\n",
|
|
" 'label_image_z_468_time_11_.tif',\n",
|
|
" 'label_image_z_546_time_0_.tif',\n",
|
|
" 'label_image_z_564_time_0_.tif']"
|
|
]
|
|
},
|
|
"execution_count": 38,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"existing_sets = os.listdir(os.path.join(training_path_sample, 'label_images'))\n",
|
|
"existing_sets.sort()\n",
|
|
"existing_sets"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"id": "a72d39ff-a38c-47d5-a7ad-c015c00fb415",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"'/mpc/homes/fische_r/NAS/DASCOELY/processing/05_water_GDL_ML/'"
|
|
]
|
|
},
|
|
"execution_count": 39,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"training_path"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 40,
|
|
"id": "6ec3f726-7ff1-4a3a-876c-98ec4bf89a79",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# you can load a compatible pickled training dict, check feature names\n",
|
|
"TS.training_dict = pickle.load(open(os.path.join(TS.training_path, pytrain_git_sha+'_training_dict.p'),'rb'))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "f584347a-423e-40f2-a9c3-64ed0504a4d1",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"TS.training_dict"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d96d4538-ba10-40dd-9da5-fea66813bd72",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### re-train with existing label sets. clear the training dictionary if necessary (training_dict)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 41,
|
|
"id": "191820b0-1cf1-4dc3-b0d8-1098cd1f84dc",
|
|
"metadata": {
|
|
"scrolled": true,
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"training with existing label images\n",
|
|
"label_image_z_546_time_0_.tif\n",
|
|
"label_image_y_255_time_40_.tif already done\n",
|
|
"label_image_z_307_time_25_.tif already done\n",
|
|
"label_image_x_157_time_5_.tif already done\n",
|
|
"label_image_y_71_time_27_.tif already done\n",
|
|
"label_image_x_270_time_50_.tif already done\n",
|
|
"label_image_x_456_time_0_.tif already done\n",
|
|
"label_image_z_320_time_10_.tif already done\n",
|
|
"label_image_x_307_time_25_.tif\n",
|
|
"label_image_z_564_time_0_.tif already done\n",
|
|
"label_image_z_320_time_30_.tif already done\n",
|
|
"label_image_x_264_time_29_.tif already done\n",
|
|
"label_image_y_280_time_57_.tif already done\n",
|
|
"label_image_y_250_time_23_.tif already done\n",
|
|
"label_image_x_172_time_17_.tif\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"2023-05-16 09:45:00,371 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:45:14,621 - distributed.utils_perf - WARNING - full garbage collections took 13% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:45:35,188 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:46:04,314 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:49:22,459 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:50:54,694 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:52:31,246 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:53:45,077 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:54:17,198 - distributed.worker - ERROR - Timed out during handshake while connecting to tcp://127.0.0.1:40027 after 30 s\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/comm/tcp.py\", line 225, in read\n",
|
|
" frames_nbytes = await stream.read_bytes(fmt_size)\n",
|
|
"asyncio.exceptions.CancelledError\n",
|
|
"\n",
|
|
"During handling of the above exception, another exception occurred:\n",
|
|
"\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/tasks.py\", line 456, in wait_for\n",
|
|
" return fut.result()\n",
|
|
"asyncio.exceptions.CancelledError\n",
|
|
"\n",
|
|
"The above exception was the direct cause of the following exception:\n",
|
|
"\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/comm/core.py\", line 328, in connect\n",
|
|
" handshake = await asyncio.wait_for(comm.read(), time_left())\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/tasks.py\", line 458, in wait_for\n",
|
|
" raise exceptions.TimeoutError() from exc\n",
|
|
"asyncio.exceptions.TimeoutError\n",
|
|
"\n",
|
|
"The above exception was the direct cause of the following exception:\n",
|
|
"\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/utils.py\", line 741, in wrapper\n",
|
|
" return await func(*args, **kwargs)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/worker.py\", line 1566, in close\n",
|
|
" await r.close_gracefully(reason=reason)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/core.py\", line 1224, in send_recv_from_rpc\n",
|
|
" comm = await self.pool.connect(self.addr)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/core.py\", line 1468, in connect\n",
|
|
" return await connect_attempt\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/core.py\", line 1389, in _connect\n",
|
|
" comm = await connect(\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/comm/core.py\", line 333, in connect\n",
|
|
" raise OSError(\n",
|
|
"OSError: Timed out during handshake while connecting to tcp://127.0.0.1:40027 after 30 s\n",
|
|
"\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/utils.py\", line 741, in wrapper\n",
|
|
" return await func(*args, **kwargs)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/worker.py\", line 1518, in close\n",
|
|
" await self.finished()\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/core.py\", line 494, in finished\n",
|
|
" await self._event_finished.wait()\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/locks.py\", line 214, in wait\n",
|
|
" await fut\n",
|
|
"asyncio.exceptions.CancelledError\n",
|
|
"2023-05-16 09:54:47,223 - distributed.worker - CRITICAL - Error trying close worker in response to broken internal state. Forcibly exiting worker NOW\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/utils.py\", line 741, in wrapper\n",
|
|
" return await func(*args, **kwargs)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/worker.py\", line 1518, in close\n",
|
|
" await self.finished()\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/core.py\", line 494, in finished\n",
|
|
" await self._event_finished.wait()\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/locks.py\", line 214, in wait\n",
|
|
" await fut\n",
|
|
"asyncio.exceptions.CancelledError\n",
|
|
"\n",
|
|
"During handling of the above exception, another exception occurred:\n",
|
|
"\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/tasks.py\", line 456, in wait_for\n",
|
|
" return fut.result()\n",
|
|
"asyncio.exceptions.CancelledError\n",
|
|
"\n",
|
|
"The above exception was the direct cause of the following exception:\n",
|
|
"\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/worker.py\", line 230, in _force_close\n",
|
|
" await asyncio.wait_for(\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/tasks.py\", line 458, in wait_for\n",
|
|
" raise exceptions.TimeoutError() from exc\n",
|
|
"asyncio.exceptions.TimeoutError\n",
|
|
"2023-05-16 09:54:47,590 - distributed.nanny - WARNING - Restarting worker\n",
|
|
"2023-05-16 09:55:24,784 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:55:27,257 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:55:30,068 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:55:33,322 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:55:36,585 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:55:39,938 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:55:43,304 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:55:46,738 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:55:51,772 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:55:56,134 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:00,644 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:06,342 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:11,303 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:17,016 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:22,878 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:29,303 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:36,880 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:43,433 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:50,846 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:56:59,606 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:57:07,562 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:57:16,888 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:57:26,843 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:57:37,066 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:57:47,981 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:57:59,347 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:58:11,759 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:58:25,270 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:58:40,363 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:58:54,131 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:59:11,643 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:59:30,384 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 09:59:49,345 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:00:11,604 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:00:50,460 - distributed.utils_perf - WARNING - full garbage collections took 15% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:01:38,505 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:02:19,995 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:03:03,981 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:03:44,879 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:04:16,568 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:05:04,492 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:06:05,845 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
|
|
"2023-05-16 10:06:44,248 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:07:48,311 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:08:33,565 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:09:17,781 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:10:02,956 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:10:56,186 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:11:48,945 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:13:03,665 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:14:37,086 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:16:28,883 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:17:57,100 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:20:21,831 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
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"2023-05-16 10:40:24,306 - distributed.worker.memory - WARNING - gc.collect() took 11.618s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
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"/mpc/homes/fische_r/lib/pytrainseg/training_functions.py:375: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
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" if not X == 'no labels':\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"label_image_x_503_time_15_.tif\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2023-05-16 11:00:29,991 - distributed.utils_perf - WARNING - full garbage collections took 13% CPU time recently (threshold: 10%)\n",
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"2023-05-16 11:02:55,018 - distributed.utils_perf - WARNING - full garbage collections took 13% CPU time recently (threshold: 10%)\n",
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"2023-05-16 11:04:08,520 - distributed.utils_perf - WARNING - full garbage collections took 13% CPU time recently (threshold: 10%)\n",
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"2023-05-16 11:21:07,596 - distributed.worker.memory - WARNING - gc.collect() took 11.310s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
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"2023-05-16 11:34:20,746 - distributed.worker.memory - WARNING - gc.collect() took 12.740s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"label_image_y_255_time_20_.tif\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2023-05-16 11:58:42,997 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
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"2023-05-16 12:00:56,045 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
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"2023-05-16 12:03:19,904 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
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"2023-05-16 12:05:08,338 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
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"2023-05-16 12:40:23,700 - distributed.worker.memory - WARNING - gc.collect() took 15.942s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
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"2023-05-16 12:54:44,026 - distributed.worker.memory - WARNING - gc.collect() took 16.627s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
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"2023-05-16 13:06:40,104 - distributed.worker.memory - WARNING - gc.collect() took 18.170s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
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"2023-05-16 13:23:04,136 - distributed.worker.memory - WARNING - gc.collect() took 19.639s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
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"2023-05-16 13:39:07,655 - distributed.worker.memory - WARNING - gc.collect() took 25.502s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"label_image_y_250_time_33_.tif\n"
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]
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},
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{
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"ename": "KeyboardInterrupt",
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"evalue": "",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[41], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mTS\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/lib/pytrainseg/training_functions.py:374\u001b[0m, in \u001b[0;36mtrain_segmentation.train\u001b[0;34m(self, clear_dict, redo)\u001b[0m\n\u001b[1;32m 372\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m 373\u001b[0m \u001b[38;5;28mprint\u001b[39m(label_name)\n\u001b[0;32m--> 374\u001b[0m X, y \u001b[38;5;241m=\u001b[39m \u001b[43mtraining_set_per_image\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlabel_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfeat_data\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlazy\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 375\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m X \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mno labels\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 376\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtraining_dict[label_name] \u001b[38;5;241m=\u001b[39m X,y\n",
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"File \u001b[0;32m~/lib/pytrainseg/training_functions.py:138\u001b[0m, in \u001b[0;36mtraining_set_per_image\u001b[0;34m(label_name, trainingpath, feat_data, lazy)\u001b[0m\n\u001b[1;32m 130\u001b[0m \u001b[38;5;66;03m# if lazy:\u001b[39;00m\n\u001b[1;32m 131\u001b[0m \u001b[38;5;66;03m# print('Need to actually calculate the features for each slice, seems inefficient')\u001b[39;00m\n\u001b[1;32m 132\u001b[0m \u001b[38;5;66;03m# # not sure how efficient this is\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;66;03m# feat_stack = feat_stack.compute()\u001b[39;00m\n\u001b[1;32m 136\u001b[0m \u001b[38;5;66;03m# else:\u001b[39;00m\n\u001b[1;32m 137\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(feat_stack) \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m np\u001b[38;5;241m.\u001b[39mndarray:\n\u001b[0;32m--> 138\u001b[0m feat_stack \u001b[38;5;241m=\u001b[39m \u001b[43mfeat_stack\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompute\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 139\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(feat_stack_t_idp) \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m np\u001b[38;5;241m.\u001b[39mndarray:\n\u001b[1;32m 140\u001b[0m feat_stack_t_idp \u001b[38;5;241m=\u001b[39m feat_stack_t_idp\u001b[38;5;241m.\u001b[39mcompute()\n",
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"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/dask/base.py:314\u001b[0m, in \u001b[0;36mDaskMethodsMixin.compute\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 290\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompute\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 291\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Compute this dask collection\u001b[39;00m\n\u001b[1;32m 292\u001b[0m \n\u001b[1;32m 293\u001b[0m \u001b[38;5;124;03m This turns a lazy Dask collection into its in-memory equivalent.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 312\u001b[0m \u001b[38;5;124;03m dask.base.compute\u001b[39;00m\n\u001b[1;32m 313\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 314\u001b[0m (result,) \u001b[38;5;241m=\u001b[39m \u001b[43mcompute\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtraverse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 315\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m result\n",
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"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/dask/base.py:593\u001b[0m, in \u001b[0;36mcompute\u001b[0;34m(traverse, optimize_graph, scheduler, get, *args, **kwargs)\u001b[0m\n\u001b[1;32m 585\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m args\n\u001b[1;32m 587\u001b[0m schedule \u001b[38;5;241m=\u001b[39m get_scheduler(\n\u001b[1;32m 588\u001b[0m scheduler\u001b[38;5;241m=\u001b[39mscheduler,\n\u001b[1;32m 589\u001b[0m collections\u001b[38;5;241m=\u001b[39mcollections,\n\u001b[1;32m 590\u001b[0m get\u001b[38;5;241m=\u001b[39mget,\n\u001b[1;32m 591\u001b[0m )\n\u001b[0;32m--> 593\u001b[0m dsk \u001b[38;5;241m=\u001b[39m \u001b[43mcollections_to_dsk\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcollections\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moptimize_graph\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 594\u001b[0m keys, postcomputes \u001b[38;5;241m=\u001b[39m [], []\n\u001b[1;32m 595\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m collections:\n",
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"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/dask/base.py:366\u001b[0m, in \u001b[0;36mcollections_to_dsk\u001b[0;34m(collections, optimize_graph, optimizations, **kwargs)\u001b[0m\n\u001b[1;32m 364\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m opt, val \u001b[38;5;129;01min\u001b[39;00m groups\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m 365\u001b[0m dsk, keys \u001b[38;5;241m=\u001b[39m _extract_graph_and_keys(val)\n\u001b[0;32m--> 366\u001b[0m dsk \u001b[38;5;241m=\u001b[39m \u001b[43mopt\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdsk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkeys\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 368\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m opt_inner \u001b[38;5;129;01min\u001b[39;00m optimizations:\n\u001b[1;32m 369\u001b[0m dsk \u001b[38;5;241m=\u001b[39m opt_inner(dsk, keys, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
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"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/dask/array/optimization.py:57\u001b[0m, in \u001b[0;36moptimize\u001b[0;34m(dsk, keys, fuse_keys, fast_functions, inline_functions_fast_functions, rename_fused_keys, **kwargs)\u001b[0m\n\u001b[1;32m 54\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m config\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moptimization.fuse.active\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m:\n\u001b[1;32m 55\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m dsk\n\u001b[0;32m---> 57\u001b[0m dependencies \u001b[38;5;241m=\u001b[39m \u001b[43mdsk\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_all_dependencies\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 58\u001b[0m dsk \u001b[38;5;241m=\u001b[39m ensure_dict(dsk)\n\u001b[1;32m 60\u001b[0m \u001b[38;5;66;03m# Low level task optimizations\u001b[39;00m\n",
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"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/dask/highlevelgraph.py:813\u001b[0m, in \u001b[0;36mHighLevelGraph.get_all_dependencies\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 811\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m missing_keys:\n\u001b[1;32m 812\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m layer \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlayers\u001b[38;5;241m.\u001b[39mvalues():\n\u001b[0;32m--> 813\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m \u001b[43mmissing_keys\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m&\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mlayer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkeys\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 814\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkey_dependencies[k] \u001b[38;5;241m=\u001b[39m layer\u001b[38;5;241m.\u001b[39mget_dependencies(k, all_keys)\n\u001b[1;32m 815\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkey_dependencies\n",
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"File \u001b[0;32m~/miniconda3/lib/python3.10/_collections_abc.py:638\u001b[0m, in \u001b[0;36mSet.__and__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 636\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, Iterable):\n\u001b[1;32m 637\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mNotImplemented\u001b[39m\n\u001b[0;32m--> 638\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_from_iterable\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mother\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/miniconda3/lib/python3.10/_collections_abc.py:880\u001b[0m, in \u001b[0;36mKeysView._from_iterable\u001b[0;34m(cls, it)\u001b[0m\n\u001b[1;32m 878\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m 879\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_from_iterable\u001b[39m(\u001b[38;5;28mcls\u001b[39m, it):\n\u001b[0;32m--> 880\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mset\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mit\u001b[49m\u001b[43m)\u001b[49m\n",
|
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"File \u001b[0;32m~/miniconda3/lib/python3.10/_collections_abc.py:638\u001b[0m, in \u001b[0;36m<genexpr>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 636\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, Iterable):\n\u001b[1;32m 637\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mNotImplemented\u001b[39m\n\u001b[0;32m--> 638\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_from_iterable(value \u001b[38;5;28;01mfor\u001b[39;00m value \u001b[38;5;129;01min\u001b[39;00m other \u001b[38;5;28;01mif\u001b[39;00m \u001b[43mvalue\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m)\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/_collections_abc.py:883\u001b[0m, in \u001b[0;36mKeysView.__contains__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 882\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__contains__\u001b[39m(\u001b[38;5;28mself\u001b[39m, key):\n\u001b[0;32m--> 883\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mkey\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_mapping\u001b[49m\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/dask/highlevelgraph.py:540\u001b[0m, in \u001b[0;36mMaterializedLayer.__contains__\u001b[0;34m(self, k)\u001b[0m\n\u001b[1;32m 537\u001b[0m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m(annotations\u001b[38;5;241m=\u001b[39mannotations)\n\u001b[1;32m 538\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmapping \u001b[38;5;241m=\u001b[39m mapping\n\u001b[0;32m--> 540\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__contains__\u001b[39m(\u001b[38;5;28mself\u001b[39m, k):\n\u001b[1;32m 541\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmapping\n\u001b[1;32m 543\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__getitem__\u001b[39m(\u001b[38;5;28mself\u001b[39m, k):\n",
|
|
"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"TS.train()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "2b1e9874-0898-4eed-8264-722540398743",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### import training dict of other samples \n",
|
|
"(replace sample name and repeat for multiple samples), if necessary check features for overlap"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"id": "9ef7faa5-925a-4916-bc13-309364ab3e7c",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"oldsample = '4'\n",
|
|
"oldgitsha = 'ec4415d'\n",
|
|
"if oldsample == '4':\n",
|
|
" training_dict_old = pickle.load(open(os.path.join(toppathSSD, '05_water_GDL_ML', '4', 'ec4415d_training_dict_without_loc_feat.p'), 'rb'))\n",
|
|
"else:\n",
|
|
" training_dict_old = pickle.load(open(os.path.join(training_path, oldsample, oldgitsha+'_training_dict.p'),'rb'))\n",
|
|
"oldfeatures = pickle.load(open(os.path.join(training_path, oldsample, oldgitsha+'_feature_names.p'),'rb'))\n",
|
|
" \n",
|
|
" # pickle.dump(TS.training_dict, open(os.path.join(TS.training_path, pytrain_git_sha+'_training_dict.p'),'wb'))\n",
|
|
"# pickle.dump(TS.feature_names, open(os.path.join(TS.training_path, pytrain_git_sha+'_feature_names.p'),'wb'))\n",
|
|
"\n",
|
|
"for key in training_dict_old.keys():\n",
|
|
" TS.training_dict[oldsample+key] = training_dict_old[key]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "49f80ce0-f19c-4e50-979b-53738597cd66",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### suggest a new training coordinate\n",
|
|
"currently retraining with new feature stack not properly implemented. Workaround: choose from the exiting training sets and train with them (additional labeling optional)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 42,
|
|
"id": "98880a87-86c9-455e-86cd-11c7b7dfc9e6",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"You could try x = 55 and z = 1058\n",
|
|
"However, please sort it like the original xyztimetime_0feature\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"TS.suggest_training_set()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 70,
|
|
"id": "49d6537c-9d9f-437c-836b-656045b694df",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"c1 = 'y'\n",
|
|
"p1 = 240\n",
|
|
"c2 = 'time'\n",
|
|
"p2 = 14"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "7c114290-5f93-4955-a2d8-4904813c03bb",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"TS.load_training_set(c1, p1, c2, p2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c37b3382-5055-43fa-bf71-e7ae622d9906",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"im8 = TS.current_im8 #for canvas"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 73,
|
|
"id": "465d7351-0b65-4e02-ad7c-331529dbde3b",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"feat_data = TS.feat_data\n",
|
|
"[c1,p1,c2,p2] = TS.current_coordinates\n",
|
|
"newslice = True\n",
|
|
"\n",
|
|
"if c1 == 'x' and c2 == 'time':\n",
|
|
" feat_stack = feat_data['feature_stack'].sel(x = p1, time = p2)\n",
|
|
" feat_stack_t_idp = feat_data['feature_stack_time_independent'].sel(x = p1, time_0 = 0)\n",
|
|
"elif c1 == 'x' and c2 == 'y':\n",
|
|
" feat_stack = feat_data['feature_stack'].sel(x = p1, y = p2).data\n",
|
|
" feat_stack_t_idp = feat_data['feature_stack_time_independent'].sel(x = p1, y = p2)\n",
|
|
"elif c1 == 'x' and c2 == 'z':\n",
|
|
" feat_stack = feat_data['feature_stack'].sel(x = p1, z = p2).data\n",
|
|
" feat_stack_t_idp = feat_data['feature_stack_time_independent'].sel(x = p1, z = p2)\n",
|
|
"elif c1 == 'y' and c2 == 'z':\n",
|
|
" feat_stack = feat_data['feature_stack'].sel(y = p1, z = p2).data\n",
|
|
" feat_stack_t_idp = feat_data['feature_stack_time_independent'].sel(y = p1, z = p2)\n",
|
|
"elif c1 == 'y' and c2 == 'time':\n",
|
|
" feat_stack = feat_data['feature_stack'].sel(y = p1, time = p2).data\n",
|
|
" feat_stack_t_idp = feat_data['feature_stack_time_independent'].sel(y = p1, time_0 = 0)\n",
|
|
"elif c1 == 'z' and c2 == 'time':\n",
|
|
" feat_stack = feat_data['feature_stack'].sel(z = p1, time = p2).data\n",
|
|
" feat_stack_t_idp = feat_data['feature_stack_time_independent'].sel(z = p1, time_0 = 0)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "19de7857-88b7-4787-a24a-2b16119aaa29",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### calculate the feature stack of the current slice for training"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "f90b47bf-e91d-4c72-be81-147f07134828",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# time dependent features\n",
|
|
"if type(feat_stack) is not np.ndarray:\n",
|
|
" fut = client.scatter(feat_stack)\n",
|
|
" fut = fut.result()\n",
|
|
" fut = fut.compute()\n",
|
|
" feat_stack = fut\n",
|
|
" client.restart()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "43a91739-a8ce-4905-8ff1-c8fd28d6b9af",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### reboot cluster if workers do not return"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "15c45866-4b94-48f9-b8e4-b7ec0f0f42a3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"len(client.cluster.workers)\n",
|
|
"\n",
|
|
"if not len(client.cluster.workers)>0: \n",
|
|
" client = reboot_client(client, cluster)\n",
|
|
" TS.client = client\n",
|
|
" IF.client = client"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "ebe6703f-3369-41a2-865d-8fb517db724e",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# time independent features\n",
|
|
"if type(feat_stack_t_idp) is not np.ndarray:\n",
|
|
" fut = client.scatter(feat_stack_t_idp)\n",
|
|
" fut = fut.result()\n",
|
|
" fut = fut.compute()\n",
|
|
" feat_stack_t_idp = fut\n",
|
|
" client.restart()\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "f8477dd4-531b-47cb-adb3-2cdc139f0847",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"if not len(client.cluster.workers)>0:\n",
|
|
" client = reboot_client(client, cluster)\n",
|
|
" TS.client = client\n",
|
|
" IF.client = client"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c1e80e3c-8093-4bdb-8985-31f0416f9024",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# put features together\n",
|
|
"feat_stack = np.concatenate([feat_stack, feat_stack_t_idp], axis = 2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "66f0c2ce-faf7-4818-9841-aa0fe7e075c7",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"TS.current_feat_stack = feat_stack\n",
|
|
"if type(TS.current_feat_stack) is not np.ndarray:\n",
|
|
" TS.current_computed = False\n",
|
|
"else:\n",
|
|
" TS.current_computed = True"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "554c0ff3-0c2c-4370-b037-be197b5bcc27",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### canvas for labeling"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 92,
|
|
"id": "c0fe6bf7-4040-4e4a-b235-601dae6e489a",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"original shape: (750, 1916)\n",
|
|
"diyplay shape : (749, 1915) at: (0, 0)\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "c8a41d82a96046c38c15db0f71e71fff",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"text/plain": [
|
|
"HBox(children=(MultiCanvas(height=749, width=1915), ColorPicker(value='#ff0000', description='Color:')))"
|
|
]
|
|
},
|
|
"execution_count": 92,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"alpha = 0.15\n",
|
|
"# zoom1 = (-500,-1)\n",
|
|
"# zoom2 = (600,1400)\n",
|
|
"\n",
|
|
"# zoom1 = (0, -1)\n",
|
|
"# zoom2 = (0, -1)\n",
|
|
"\n",
|
|
"# im8 = TS.current_im8\n",
|
|
"#trick: use gaussian_time_4_0 to label static phases ()\n",
|
|
"# im8 = display_feature(-2, TS)\n",
|
|
"# im8 = display_feature(-20, TS)\n",
|
|
"# print(IF.combined_feature_names[-20])\n",
|
|
"print('original shape: ',im8.shape)\n",
|
|
"im8_display = im8.copy() #[zoom1[0]:zoom1[1], zoom2[0]:zoom2[1]]\n",
|
|
"# print('diyplay shape : ',im8_display.shape,' at: ', (zoom1[0], zoom2[0]))\n",
|
|
"\n",
|
|
"resultim = TS.current_result.copy()\n",
|
|
"\n",
|
|
"resultim_display = resultim #[zoom1[0]:zoom1[1], zoom2[0]:zoom2[1]]\n",
|
|
"\n",
|
|
"\n",
|
|
"width = im8_display.shape[1]\n",
|
|
"height = im8_display.shape[0]\n",
|
|
"Mcanvas = MultiCanvas(4, width=width, height=height)\n",
|
|
"background = Mcanvas[0]\n",
|
|
"resultdisplay = Mcanvas[2]\n",
|
|
"truthdisplay = Mcanvas[1]\n",
|
|
"canvas = Mcanvas[3]\n",
|
|
"canvas.sync_image_data = True\n",
|
|
"drawing = False\n",
|
|
"position = None\n",
|
|
"shape = []\n",
|
|
"image_data = np.stack((im8_display, im8_display, im8_display), axis=2)\n",
|
|
"background.put_image_data(image_data, 0, 0)\n",
|
|
"slidealpha = IntSlider(description=\"Result overlay\", value=0.15)\n",
|
|
"resultdisplay.global_alpha = alpha #slidealpha.value\n",
|
|
"if np.any(resultim>0):\n",
|
|
" result_data = np.stack(((resultim_display==0), (resultim_display==1),(resultim_display==2)), axis=2)*255\n",
|
|
" mask3 = resultim_display==3\n",
|
|
" result_data[mask3,0] = 255\n",
|
|
" result_data[mask3,1] = 255\n",
|
|
"else:\n",
|
|
" result_data = np.stack((0*resultim, 0*resultim, 0*resultim), axis=2)\n",
|
|
"resultdisplay.put_image_data(result_data, 0, 0)\n",
|
|
"canvas.on_mouse_down(on_mouse_down)\n",
|
|
"canvas.on_mouse_move(on_mouse_move)\n",
|
|
"canvas.on_mouse_up(on_mouse_up)\n",
|
|
"picker = ColorPicker(description=\"Color:\", value=\"#ff0000\") #red\n",
|
|
"# picker = ColorPicker(description=\"Color:\", value=\"#0000ff\") #blue\n",
|
|
"# picker = ColorPicker(description=\"Color:\", value=\"#00ff00\") #green\n",
|
|
"\n",
|
|
"link((picker, \"value\"), (canvas, \"stroke_style\"))\n",
|
|
"link((picker, \"value\"), (canvas, \"fill_style\"))\n",
|
|
"link((slidealpha, \"value\"), (resultdisplay, \"global_alpha\"))\n",
|
|
"\n",
|
|
"HBox((Mcanvas,picker))\n",
|
|
"# HBox((Mcanvas,)) #picker "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 81,
|
|
"id": "0e32c35a-e644-4dfd-b52e-be2a1bd1e940",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# crude method to adjust brightness and contrast\n",
|
|
"tfs.plot_im_histogram(im8)\n",
|
|
"# im8 = TS.current_im8\n",
|
|
"# im8 = tfs.adjust_image_contrast(im8,20,200)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5d51d5d9-398d-4ee9-b50a-98ba94a0b6f7",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### inspect labels and training progress"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 93,
|
|
"id": "733006e0-b8c5-4de8-9b23-80df9e53e1c2",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 2000x1000 with 6 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"fig, axes = plt.subplots(1,6, figsize=(20,10))\n",
|
|
"axes[0].imshow(TS.current_result, 'gray')\n",
|
|
"axes[1].imshow(TS.current_im8, 'gray')\n",
|
|
"\n",
|
|
"# TS.current_diff_im = TS.current_im-TS.current_first_im\n",
|
|
"# TS.current_diff_im = TS.current_diff_im/TS.current_diff_im.max()*255\n",
|
|
"axes[2].imshow(-TS.current_diff_im)#,vmin=6e4)\n",
|
|
"# axes[3].imshow(im8old, 'gray')\n",
|
|
"axes[3].imshow(TS.current_first_im, 'gray')\n",
|
|
"axes[4].imshow(TS.current_truth)\n",
|
|
"if TS.current_computed:\n",
|
|
" axes[5].imshow(TS.current_feat_stack[:,:,-10])\n",
|
|
"else:\n",
|
|
" axes[5].imshow(TS.current_result, 'gray')\n",
|
|
"\n",
|
|
"for ax in axes:\n",
|
|
" ax.set_xticks([])\n",
|
|
" ax.set_yticks([])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c81a6e0c-33c5-4d82-8cd3-0a258015e95d",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### update training set if labels are ok"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 84,
|
|
"id": "11b8cbbc-6873-4c93-97c5-f91416ab5abc",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"label_set = canvas.get_image_data()\n",
|
|
"\n",
|
|
"test = TS.current_truth.copy()\n",
|
|
"\n",
|
|
"test[np.bitwise_and(label_set[:,:,0]>0,np.bitwise_xor(label_set[:,:,0]>0,label_set[:,:,1]>0))] = 1\n",
|
|
"test[label_set[:,:,1]>0] = 2\n",
|
|
"test[label_set[:,:,2]>0] = 4 #order of 4&3 flipped for legacy reasons (existing training labels)\n",
|
|
"test[np.bitwise_and(label_set[:,:,0]>0,label_set[:,:,1]>0)] = 3\n",
|
|
"\n",
|
|
"TS.current_truth = test.copy()\n",
|
|
"imageio.imsave(TS.current_truthpath, TS.current_truth)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d994e7f8-8809-4b3b-910a-2b55d36db397",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### train!"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 87,
|
|
"id": "0a243dc8-89c0-43cd-a32d-89f1a9abbade",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"now actually calculating the features\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"2023-03-29 10:43:42,902 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)\n",
|
|
"2023-03-29 10:46:50,886 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
|
|
"2023-03-29 10:47:32,421 - distributed.worker.memory - WARNING - gc.collect() took 1.027s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
|
|
"2023-03-29 10:49:51,644 - distributed.worker.memory - WARNING - gc.collect() took 1.240s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
|
|
"2023-03-29 10:49:52,590 - distributed.worker.memory - WARNING - gc.collect() took 1.523s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
|
|
"2023-03-29 10:50:09,993 - distributed.worker.memory - WARNING - gc.collect() took 1.379s. This is usually a sign that some tasks handle too many Python objects at the same time. Rechunking the work into smaller tasks might help.\n",
|
|
"2023-03-29 10:52:55,347 - tornado.application - ERROR - Uncaught exception GET /status/ws (::1)\n",
|
|
"HTTPServerRequest(protocol='http', host='127.0.0.1:35000', method='GET', uri='/status/ws', version='HTTP/1.1', remote_ip='::1')\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/tornado/websocket.py\", line 942, in _accept_connection\n",
|
|
" open_result = handler.open(*handler.open_args, **handler.open_kwargs)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/tornado/web.py\", line 3208, in wrapper\n",
|
|
" return method(self, *args, **kwargs)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/bokeh/server/views/ws.py\", line 149, in open\n",
|
|
" raise ProtocolError(\"Token is expired.\")\n",
|
|
"bokeh.protocol.exceptions.ProtocolError: Token is expired.\n",
|
|
"ERROR:tornado.application:Uncaught exception GET /status/ws (::1)\n",
|
|
"HTTPServerRequest(protocol='http', host='127.0.0.1:35000', method='GET', uri='/status/ws', version='HTTP/1.1', remote_ip='::1')\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/tornado/websocket.py\", line 942, in _accept_connection\n",
|
|
" open_result = handler.open(*handler.open_args, **handler.open_kwargs)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/tornado/web.py\", line 3208, in wrapper\n",
|
|
" return method(self, *args, **kwargs)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/bokeh/server/views/ws.py\", line 149, in open\n",
|
|
" raise ProtocolError(\"Token is expired.\")\n",
|
|
"bokeh.protocol.exceptions.ProtocolError: Token is expired.\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"feat_stack is not a numpy array! check why\n",
|
|
"training and classifying\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# TODO: see, if training gets slow for many label sets, currently stored in training_dict and read as loop. or if it is just the larger amount of data\n",
|
|
"TS.train_slice()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 421,
|
|
"id": "efab4c56-7108-44ac-adf2-f9ee89a40562",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# # load exisiting classifier and segment one slice\n",
|
|
"# clf = pickle.load(open(os.path.join(training_path, 'classifier.p'), 'rb'))\n",
|
|
"# feat = TS.current_feat_stack.compute()\n",
|
|
"# shp = feat[...,0].shape\n",
|
|
"# num_feat = feat.shape[-1]\n",
|
|
"# feat = feat.reshape(-1,num_feat)\n",
|
|
"# seg = clf.predict(feat)\n",
|
|
"# seg = seg.reshape(shp).astype(np.uint8)\n",
|
|
"# plt.figure(figsize=(16,9))\n",
|
|
"# plt.imshow(seg, cmap='gray_r')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 422,
|
|
"id": "519d7e1f-afde-4088-b2aa-d0899a171bb5",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# plt.figure(figsize=(16,9))\n",
|
|
"# plt.imshow(im8, cmap='gray')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d1496223-a96b-43cd-996b-75d3b2befba5",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### go back until happy"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "af84a18a-7416-4636-a63c-82959a47c09c",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### check on training progress by plausible feature importance"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 94,
|
|
"id": "c63cb1db-d578-4560-9211-deb3fc7b3065",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0, 0.5, 'importance')"
|
|
]
|
|
},
|
|
"execution_count": 94,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1600x900 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(16,9))\n",
|
|
"plt.stem(TS.combined_feature_names, TS.clf.feature_importances_,'x')\n",
|
|
"plt.xticks(rotation=90)\n",
|
|
"plt.ylabel('importance') \n",
|
|
"# plt.xticks(rotation = 60)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "611ed636-ff8c-4c16-af1f-6528ff9f5b5a",
|
|
"metadata": {},
|
|
"source": [
|
|
"### when done, maybe save the classifier and optional the training dict (avoids recalculating the training sets, but might be large)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 43,
|
|
"id": "e8bbe689-6711-48f5-b805-2324ed47ecca",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# TS.pickle_classifier()\n",
|
|
"pickle.dump(TS.training_dict, open(os.path.join(TS.training_path, pytrain_git_sha+'_training_dict.p'),'wb'))\n",
|
|
"pickle.dump(TS.combined_feature_names, open(os.path.join(TS.training_path, pytrain_git_sha+'_feature_names.p'),'wb'))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 46,
|
|
"id": "fd67ff7f-4ab7-46e5-8a11-428af3dfcded",
|
|
"metadata": {
|
|
"collapsed": true,
|
|
"jupyter": {
|
|
"outputs_hidden": true
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"{'label_image_y_255_time_40_.tif': (array([[-1.46428571e+02, -4.71285714e+02, 1.71676120e-01, ...,\n",
|
|
" 1.11674225e+04, 1.06050000e+04, 1.70411936e-01],\n",
|
|
" [ 1.54714286e+02, -1.69714286e+02, 1.72399418e-01, ...,\n",
|
|
" 1.13587042e+04, 1.08410000e+04, 1.71066865e-01],\n",
|
|
" [-1.65000000e+02, -3.60142857e+02, 1.71660520e-01, ...,\n",
|
|
" 1.10823803e+04, 1.03730000e+04, 1.70895247e-01],\n",
|
|
" ...,\n",
|
|
" [ 1.56428571e+02, 2.81285714e+02, 1.78094529e-01, ...,\n",
|
|
" 1.19940141e+04, 1.14850000e+04, 1.78078066e-01],\n",
|
|
" [ 1.63285714e+02, 1.47000000e+02, 1.77728446e-01, ...,\n",
|
|
" 1.19303803e+04, 1.13000000e+04, 1.77728446e-01],\n",
|
|
" [-2.08571429e+02, -3.50142857e+02, 1.76900536e-01, ...,\n",
|
|
" 1.15639014e+04, 1.10180000e+04, 1.76805548e-01]]),\n",
|
|
" array([0., 0., 0., ..., 2., 2., 2.])),\n",
|
|
" 'label_image_z_307_time_25_.tif': (array([[-2.46142857e+02, -3.74142857e+02, 1.76275724e-01, ...,\n",
|
|
" 1.18232958e+04, 1.10610000e+04, 1.74925798e-01],\n",
|
|
" [-3.42000000e+02, -4.85857143e+02, 1.76316241e-01, ...,\n",
|
|
" 1.18405352e+04, 1.11300000e+04, 1.75319188e-01],\n",
|
|
" [-1.90428571e+02, -3.74857143e+02, 1.77512776e-01, ...,\n",
|
|
" 1.21114930e+04, 1.14260000e+04, 1.76005940e-01],\n",
|
|
" ...,\n",
|
|
" [-1.81714286e+02, 4.80285714e+02, 1.76016286e-01, ...,\n",
|
|
" 1.10960563e+04, 1.01840000e+04, 1.74601599e-01],\n",
|
|
" [ 9.84285714e+01, 6.54285714e+02, 1.75308977e-01, ...,\n",
|
|
" 1.09472676e+04, 1.03020000e+04, 1.73986060e-01],\n",
|
|
" [ 3.74714286e+02, 1.56428571e+02, 1.76564722e-01, ...,\n",
|
|
" 1.16763662e+04, 1.06990000e+04, 1.75170552e-01]]),\n",
|
|
" array([0., 0., 0., ..., 2., 2., 2.])),\n",
|
|
" 'label_image_x_157_time_5_.tif': (array([[ 6.12714286e+02, 4.12000000e+02, 1.81691079e-01, ...,\n",
|
|
" 1.18927465e+04, 1.12010000e+04, 1.80019835e-01],\n",
|
|
" [ 2.26857143e+02, -1.45142857e+02, 1.81563116e-01, ...,\n",
|
|
" 1.18323099e+04, 1.09740000e+04, 1.79961364e-01],\n",
|
|
" [ 4.12428571e+02, 2.41142857e+02, 1.81434953e-01, ...,\n",
|
|
" 1.18325352e+04, 1.08200000e+04, 1.79912975e-01],\n",
|
|
" ...,\n",
|
|
" [ 4.61285714e+02, 1.17900000e+03, 1.82986851e-01, ...,\n",
|
|
" 1.16421831e+04, 1.06770000e+04, 1.76633232e-01],\n",
|
|
" [ 2.95285714e+02, 1.14028571e+03, 1.82246264e-01, ...,\n",
|
|
" 1.15427042e+04, 1.07200000e+04, 1.76239893e-01],\n",
|
|
" [ 2.36571429e+02, 1.05700000e+03, 1.81376676e-01, ...,\n",
|
|
" 1.14711549e+04, 1.06250000e+04, 1.76194815e-01]]),\n",
|
|
" array([0., 0., 0., ..., 2., 2., 2.])),\n",
|
|
" 'label_image_y_71_time_27_.tif': (array([[-1.35857143e+02, 1.11428571e+01, 1.93519196e-01, ...,\n",
|
|
" 1.29737324e+04, 1.19270000e+04, 1.91659363e-01],\n",
|
|
" [ 1.04714286e+02, 1.25000000e+02, 1.93022896e-01, ...,\n",
|
|
" 1.29130563e+04, 1.20690000e+04, 1.91258373e-01],\n",
|
|
" [ 2.80000000e+01, 1.83000000e+02, 1.92580109e-01, ...,\n",
|
|
" 1.28927042e+04, 1.18410000e+04, 1.90972621e-01],\n",
|
|
" ...,\n",
|
|
" [ 1.77571429e+02, 9.50000000e+01, 1.82714666e-01, ...,\n",
|
|
" 1.17465211e+04, 1.13000000e+04, 1.81494558e-01],\n",
|
|
" [ 1.76714286e+02, 2.65714286e+02, 1.83214647e-01, ...,\n",
|
|
" 1.17702676e+04, 1.11810000e+04, 1.81948427e-01],\n",
|
|
" [ 9.18571429e+01, 2.36428571e+02, 1.83764860e-01, ...,\n",
|
|
" 1.17896901e+04, 1.12550000e+04, 1.82611815e-01]]),\n",
|
|
" array([1., 1., 1., ..., 2., 2., 2.])),\n",
|
|
" 'label_image_x_270_time_50_.tif': (array([[ 7.62285714e+02, 3.66285714e+02, 1.77352465e-01, ...,\n",
|
|
" 1.17248873e+04, 1.08400000e+04, 1.76199144e-01],\n",
|
|
" [ 5.79571429e+02, 1.56857143e+02, 1.77569550e-01, ...,\n",
|
|
" 1.21831408e+04, 1.15700000e+04, 1.76699324e-01],\n",
|
|
" [ 1.67714286e+02, -1.69857143e+02, 1.77088113e-01, ...,\n",
|
|
" 1.21293662e+04, 1.14650000e+04, 1.76558669e-01],\n",
|
|
" ...,\n",
|
|
" [ 1.76571429e+02, 3.25571429e+02, 1.78726329e-01, ...,\n",
|
|
" 1.17209718e+04, 1.11370000e+04, 1.78671522e-01],\n",
|
|
" [-1.60285714e+02, 5.28571429e+01, 1.78158173e-01, ...,\n",
|
|
" 1.14837465e+04, 1.09890000e+04, 1.78069821e-01],\n",
|
|
" [-4.00000000e+02, -9.31428571e+01, 1.77880470e-01, ...,\n",
|
|
" 1.14104507e+04, 1.08650000e+04, 1.77633669e-01]]),\n",
|
|
" array([0., 0., 0., ..., 2., 2., 2.])),\n",
|
|
" 'label_image_x_456_time_0_.tif': (array([[2.07142857e+02, 1.14642857e+03, 1.90178932e-01, ...,\n",
|
|
" 1.22672817e+04, 1.08070000e+04, 1.77169381e-01],\n",
|
|
" [2.49714286e+02, 1.03714286e+03, 1.91092602e-01, ...,\n",
|
|
" 1.24148451e+04, 1.11670000e+04, 1.79968294e-01],\n",
|
|
" [2.52714286e+02, 8.14428571e+02, 1.92194164e-01, ...,\n",
|
|
" 1.25856901e+04, 1.17740000e+04, 1.83731002e-01],\n",
|
|
" ...,\n",
|
|
" [2.74285714e+02, 1.28857143e+02, 1.75245020e-01, ...,\n",
|
|
" 1.16030423e+04, 1.10330000e+04, 1.74652647e-01],\n",
|
|
" [1.13857143e+02, 2.27142857e+02, 1.75125835e-01, ...,\n",
|
|
" 1.12481831e+04, 1.06070000e+04, 1.74509806e-01],\n",
|
|
" [3.50428571e+02, 4.15428571e+02, 1.75175942e-01, ...,\n",
|
|
" 1.12752817e+04, 1.07240000e+04, 1.74449912e-01]]),\n",
|
|
" array([0., 0., 0., ..., 2., 2., 2.])),\n",
|
|
" 'label_image_z_320_time_10_.tif': (array([[8.92857143e+01, 1.87571429e+02, 1.82469480e-01, ...,\n",
|
|
" 1.22107042e+04, 1.11800000e+04, 1.81068155e-01],\n",
|
|
" [6.86000000e+02, 4.32857143e+02, 1.80689966e-01, ...,\n",
|
|
" 1.20154648e+04, 1.09530000e+04, 1.79250545e-01],\n",
|
|
" [3.05285714e+02, 1.21428571e+01, 1.79607390e-01, ...,\n",
|
|
" 1.19377746e+04, 1.04670000e+04, 1.77957822e-01],\n",
|
|
" ...,\n",
|
|
" [1.13571429e+02, 2.35428571e+02, 1.76514598e-01, ...,\n",
|
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" 1.14960563e+04, 1.07940000e+04, 1.74584281e-01],\n",
|
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" [2.81000000e+02, 4.33000000e+02, 1.76417716e-01, ...,\n",
|
|
" 1.15155493e+04, 1.07560000e+04, 1.74400619e-01],\n",
|
|
" [1.56428571e+02, 1.06857143e+02, 1.76227649e-01, ...,\n",
|
|
" 1.15197183e+04, 1.08520000e+04, 1.74042724e-01]]),\n",
|
|
" array([0., 0., 0., ..., 1., 1., 1.])),\n",
|
|
" 'label_image_z_564_time_0_.tif': (array([[ 3.13285714e+02, 2.64285714e+02, 1.96006687e-01, ...,\n",
|
|
" 1.27615915e+04, 1.21920000e+04, 1.94477154e-01],\n",
|
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" [-8.00000000e+01, -1.59285714e+02, 1.95622355e-01, ...,\n",
|
|
" 1.27900704e+04, 1.22220000e+04, 1.94649750e-01],\n",
|
|
" [-9.24285714e+01, -1.13000000e+02, 1.95298843e-01, ...,\n",
|
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" 1.27974789e+04, 1.22600000e+04, 1.94626234e-01],\n",
|
|
" ...,\n",
|
|
" [-4.71428571e+00, 2.92857143e+02, 1.79363554e-01, ...,\n",
|
|
" 1.12649577e+04, 1.05480000e+04, 1.73660473e-01],\n",
|
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" [ 4.69857143e+02, 7.61000000e+02, 1.79049298e-01, ...,\n",
|
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" 1.11457746e+04, 1.03290000e+04, 1.72011410e-01],\n",
|
|
" [ 4.55142857e+02, 7.02285714e+02, 1.78584209e-01, ...,\n",
|
|
" 1.10580845e+04, 1.04030000e+04, 1.70629070e-01]]),\n",
|
|
" array([0., 0., 0., ..., 2., 2., 2.])),\n",
|
|
" 'label_image_z_320_time_30_.tif': (array([[ 2.14857143e+02, 1.52285714e+02, 2.01065715e-01, ...,\n",
|
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" 1.33168028e+04, 1.19130000e+04, 1.96774246e-01],\n",
|
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" [-3.23714286e+02, 1.71428571e+00, 2.01161255e-01, ...,\n",
|
|
" 1.33518310e+04, 1.18630000e+04, 1.96969844e-01],\n",
|
|
" [-3.62714286e+02, -9.71428571e+00, 2.01125502e-01, ...,\n",
|
|
" 1.33800563e+04, 1.20740000e+04, 1.96864119e-01],\n",
|
|
" ...,\n",
|
|
" [-1.48485714e+03, -6.54714286e+02, 1.77340966e-01, ...,\n",
|
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" 1.15403099e+04, 1.06520000e+04, 1.76559372e-01],\n",
|
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" [-1.58242857e+03, -6.48857143e+02, 1.79606184e-01, ...,\n",
|
|
" 1.18334648e+04, 1.09120000e+04, 1.78930439e-01],\n",
|
|
" [-7.85000000e+02, 1.34000000e+02, 1.82066069e-01, ...,\n",
|
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" 1.23317606e+04, 1.13080000e+04, 1.81227066e-01]]),\n",
|
|
" array([0., 0., 0., ..., 1., 1., 1.])),\n",
|
|
" 'label_image_x_264_time_29_.tif': (array([[-8.55714286e+01, 4.90000000e+01, 1.95446785e-01, ...,\n",
|
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" 1.27986338e+04, 1.23040000e+04, 1.93879462e-01],\n",
|
|
" [ 1.22857143e+02, 2.16428571e+02, 1.95580021e-01, ...,\n",
|
|
" 1.27709296e+04, 1.20220000e+04, 1.93749050e-01],\n",
|
|
" [ 1.40000000e+01, 2.14285714e+01, 1.95790805e-01, ...,\n",
|
|
" 1.28141268e+04, 1.21830000e+04, 1.93688263e-01],\n",
|
|
" ...,\n",
|
|
" [-4.59857143e+02, -3.76000000e+02, 1.76360268e-01, ...,\n",
|
|
" 1.13471831e+04, 1.02530000e+04, 1.70212563e-01],\n",
|
|
" [-2.67285714e+02, -5.01000000e+02, 1.76233976e-01, ...,\n",
|
|
" 1.13495915e+04, 1.02230000e+04, 1.70287334e-01],\n",
|
|
" [ 9.31428571e+01, -1.57714286e+02, 1.75952877e-01, ...,\n",
|
|
" 1.13085915e+04, 1.02450000e+04, 1.70298715e-01]]),\n",
|
|
" array([0., 0., 0., ..., 2., 2., 2.])),\n",
|
|
" 'label_image_y_280_time_57_.tif': (array([[-8.58571429e+01, 7.68571429e+01, 1.82389721e-01, ...,\n",
|
|
" 1.20554085e+04, 1.14720000e+04, 1.81354376e-01],\n",
|
|
" [-2.18000000e+02, 1.72000000e+02, 1.82640049e-01, ...,\n",
|
|
" 1.22886620e+04, 1.16720000e+04, 1.81573052e-01],\n",
|
|
" [ 3.24000000e+02, 3.61428571e+02, 1.82303870e-01, ...,\n",
|
|
" 1.19934366e+04, 1.13380000e+04, 1.81405977e-01],\n",
|
|
" ...,\n",
|
|
" [ 9.55714286e+01, 2.29714286e+02, 1.71066023e-01, ...,\n",
|
|
" 1.12507606e+04, 9.87400000e+03, 1.69633661e-01],\n",
|
|
" [ 1.79000000e+02, 3.07428571e+02, 1.71033091e-01, ...,\n",
|
|
" 1.12309014e+04, 1.01770000e+04, 1.69707987e-01],\n",
|
|
" [ 2.13714286e+02, 1.01428571e+01, 1.70781424e-01, ...,\n",
|
|
" 1.11918310e+04, 9.93100000e+03, 1.69562468e-01]]),\n",
|
|
" array([0., 0., 0., ..., 1., 1., 1.])),\n",
|
|
" 'label_image_y_250_time_23_.tif': (array([[ 6.29571429e+02, 2.80571429e+02, 1.83566668e-01, ...,\n",
|
|
" 1.19565634e+04, 1.11340000e+04, 1.81957534e-01],\n",
|
|
" [ 2.94000000e+02, 9.17142857e+01, 1.83483545e-01, ...,\n",
|
|
" 1.19102113e+04, 1.11850000e+04, 1.81933184e-01],\n",
|
|
" [-2.17428571e+02, -4.80142857e+02, 1.83503721e-01, ...,\n",
|
|
" 1.19503380e+04, 1.11650000e+04, 1.81941278e-01],\n",
|
|
" ...,\n",
|
|
" [-5.99142857e+02, -3.23000000e+02, 1.75209452e-01, ...,\n",
|
|
" 1.13515493e+04, 1.06300000e+04, 1.73828147e-01],\n",
|
|
" [-2.53428571e+02, 3.61428571e+01, 1.76540683e-01, ...,\n",
|
|
" 1.16698169e+04, 1.10110000e+04, 1.76169142e-01],\n",
|
|
" [ 3.13714286e+02, 4.45285714e+02, 1.77460691e-01, ...,\n",
|
|
" 1.18957606e+04, 1.12630000e+04, 1.76957676e-01]]),\n",
|
|
" array([0., 0., 0., ..., 2., 2., 2.]))}"
|
|
]
|
|
},
|
|
"execution_count": 46,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"TS.training_dict_full"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 103,
|
|
"id": "d1232485-1632-4a77-83fc-47ab30584d01",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"'/mpc/homes/fische_r/NAS/DASCOELY/processing/05_water_GDL_ML/1'"
|
|
]
|
|
},
|
|
"execution_count": 103,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"TS.training_path"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 50,
|
|
"id": "6b27074a-2385-46a8-bb40-aabfc1a187c0",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"'ec4415d'"
|
|
]
|
|
},
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"pytrain_git_sha"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d2c2235f-c2f1-4b28-8489-55fc81a25f7e",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"## Segmentation of full data set\n",
|
|
"\n",
|
|
"segmentation has not yet be checked for functionality after dask update!\n",
|
|
"probably needs major restructuring but should work eventually"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"id": "fc88e550-abba-47cf-bfdb-eb310aa3fc73",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"from segmentation import segmentation"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"id": "23511242-75c9-4546-8a83-4ce54915c067",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"classifier_path=os.path.join(training_path, 'classifier.p')\n",
|
|
"SM = segmentation(training_path = training_path, classifier_path=classifier_path)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"id": "7223408a-63f1-4ff1-a6df-29f9e9f872e8",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# SM.import_lazy_feature_data(IF.result)\n",
|
|
"# SM.import_classifier(TS.clf)\n",
|
|
"SM.clf = pickle.load(open(os.path.join(training_path, 'classifier.p'), 'rb'))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 40,
|
|
"id": "2db024b7-c3ea-4b8e-9c09-6de7db817b67",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"clf = SM.clf\n",
|
|
"clf.n_jobs = 64\n",
|
|
"\n",
|
|
"if host == 'mpc2053.psi.ch':\n",
|
|
" clf.n_jobs = 20"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 41,
|
|
"id": "78f94235-47ad-4018-8d8a-56df08f5d8c6",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"#TODO create result as a stream for every feature set of chunks, i.e stack of 67 feature chunks\n",
|
|
"# clf = TS.clf\n",
|
|
"# clf.n_jobs = 32"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 42,
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|
"id": "0d4110bc-e263-428a-a231-b3c47c72d184",
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|
"metadata": {
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|
"tags": []
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},
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"outputs": [],
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"source": [
|
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"# loc_feats = [-4, -5, -6]\n",
|
|
"# ids = np.ones(72, dtype=bool)\n",
|
|
"# for f in loc_feats:\n",
|
|
"# ids[f] = False"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 43,
|
|
"id": "c693f04b-fc16-45a3-8074-e63fcdc1c780",
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|
"metadata": {
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"tags": []
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|
},
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"outputs": [],
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"source": [
|
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"# ids"
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|
]
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|
},
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{
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"cell_type": "markdown",
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"id": "197aa63c-812a-4a0c-aa51-724fcc83e39f",
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|
"metadata": {},
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|
"source": [
|
|
"### merge time-independent features"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 44,
|
|
"id": "f8a0c7b6-163e-4b9b-8599-dd7f91c5e174",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
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|
"name": "stderr",
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"output_type": "stream",
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"text": [
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"2023-04-28 08:57:28,625 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
|
|
"2023-04-28 08:57:33,885 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"test = dask.array.stack([TS.feat_data['feature_stack_time_independent'][:,:,:,0,:]]*da.shape[-1], axis=-2)"
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|
]
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|
},
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{
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"cell_type": "code",
|
|
"execution_count": 45,
|
|
"id": "f601fff6-e14b-4861-8788-b2ad7836ca05",
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|
"metadata": {
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"tags": []
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},
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"outputs": [
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" <tr>\n",
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" <td> </td>\n",
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" <th> Array </th>\n",
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" <th> Chunk </th>\n",
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" </tr>\n",
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" \n",
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" <th> Bytes </th>\n",
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" <td> 543.37 GiB </td>\n",
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"text/plain": [
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"dask.array<stack, shape=(750, 130, 1700, 88, 5), dtype=float64, chunksize=(32, 32, 32, 1, 1), chunktype=numpy.ndarray>"
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]
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},
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},
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"execution_count": 46,
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"id": "b7453b61-86d3-4767-bfc9-00e8f3e12594",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2023-04-28 08:57:55,416 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 08:58:41,121 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 08:59:32,401 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:00:31,800 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
|
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"2023-04-28 09:01:44,643 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:03:17,745 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n"
|
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]
|
|
}
|
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],
|
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"source": [
|
|
"feat = dask.array.concatenate([TS.feat_data['feature_stack'], test], axis=-1)"
|
|
]
|
|
},
|
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{
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|
"cell_type": "code",
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"execution_count": 47,
|
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"id": "4e94d408-8659-40b0-8034-fd162f3e8fa3",
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"metadata": {
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"tags": []
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},
|
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"outputs": [],
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"source": [
|
|
"# feat = feat[...,ids]"
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|
]
|
|
},
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{
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|
"cell_type": "code",
|
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"execution_count": 48,
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"id": "f8815953-be31-4ef3-b2fb-f247c4daddaf",
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"metadata": {
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"tags": []
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},
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"outputs": [
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" <tr>\n",
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" <td> </td>\n",
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" <th> Array </th>\n",
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" <th> Chunk </th>\n",
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" </tr>\n",
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"text/plain": [
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"dask.array<concatenate, shape=(750, 130, 1700, 88, 69), dtype=float64, chunksize=(32, 32, 32, 1, 1), chunktype=numpy.ndarray>"
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]
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},
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"execution_count": 48,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"feat"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9175532e-5cc4-4867-bd5d-bbf51ea4ca71",
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"metadata": {},
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"source": [
|
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"### check aligment of chunks and select suitable \"super-chunk\" shape to split calculation in parts, example below"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 49,
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"id": "8fe48b5f-20e2-4b87-9894-ca6f4c5eae02",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"1724.9999999999998"
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]
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},
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"execution_count": 49,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"750*2.3"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 50,
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"id": "721a5cf7-84b7-4f21-9035-a04b24ddb9c1",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"7.0"
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]
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},
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"execution_count": 50,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"350/50"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 51,
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"id": "fddb3805-230d-4267-abcc-46f99d2e1191",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<table>\n",
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" <table style=\"border-collapse: collapse;\">\n",
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" <thead>\n",
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" <tr>\n",
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" <td> </td>\n",
|
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" <th> Array </th>\n",
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" <th> Chunk </th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" \n",
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" <tr>\n",
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" <th> Bytes </th>\n",
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" <td> 0 B </td>\n",
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" <td> 0 B </td>\n",
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" </tr>\n",
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" \n",
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" <tr>\n",
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" <th> Shape </th>\n",
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" <td> (0, 130, 0, 88, 69) </td>\n",
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" <td> (0, 32, 0, 1, 1) </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th> Dask graph </th>\n",
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" <td colspan=\"2\"> 36432 chunks in 451 graph layers </td>\n",
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" </tr>\n",
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" <tr>\n",
|
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" <th> Data type </th>\n",
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" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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" </tr>\n",
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" </tbody>\n",
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" </table>\n",
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" </td>\n",
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" <td>\n",
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" \n",
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" </td>\n",
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" </tr>\n",
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"</table>"
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],
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"text/plain": [
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"dask.array<getitem, shape=(0, 130, 0, 88, 69), dtype=float64, chunksize=(0, 32, 0, 1, 1), chunktype=numpy.ndarray>"
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]
|
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},
|
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"execution_count": 51,
|
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
|
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"i = 12\n",
|
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"j = i\n",
|
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"# j = 3\n",
|
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"dim1 = 64#better use multiple of chunk size !?\n",
|
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"dim2 = int(2.3*dim1)\n",
|
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"feat[i*dim1:(i+1)*dim1,:,j*dim2:(j+1)*dim2,:,:] #select all features and all time steps, but you are free in space; als large as possible and as small as necessary. limit is the available RAM to collect the dask result"
|
|
]
|
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},
|
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{
|
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"cell_type": "code",
|
|
"execution_count": 52,
|
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"id": "94193631-c6c8-4a6b-a527-ef98f3e6d77d",
|
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"metadata": {
|
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"tags": []
|
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},
|
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"outputs": [
|
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{
|
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"name": "stderr",
|
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"output_type": "stream",
|
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"text": [
|
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"2023-04-28 09:06:48,538 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
|
|
"2023-04-28 09:07:43,656 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
|
|
"2023-04-28 09:07:45,739 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)\n",
|
|
"2023-04-28 09:07:48,023 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
|
|
"2023-04-28 09:07:50,311 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
|
|
"2023-04-28 09:07:52,682 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
|
|
"2023-04-28 09:07:55,129 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
|
|
"2023-04-28 09:07:57,693 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
|
|
"2023-04-28 09:08:00,064 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n",
|
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"2023-04-28 09:08:02,809 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# segs = np.zeros(feat.shape[:4], dtype=np.uint8)\n",
|
|
"segs = pickle.load(open(os.path.join(training_path,'segs.p'), 'rb'))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 53,
|
|
"id": "fd3f3e68-c279-4857-a196-a416b807aca5",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
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{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
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"text": [
|
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"2023-04-28 09:08:05,439 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)\n",
|
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"2023-04-28 09:08:25,753 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n"
|
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]
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},
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{
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"data": {
|
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"text/plain": [
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"101"
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]
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},
|
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"execution_count": 53,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# import gc\n",
|
|
"client.run(gc.collect)\n",
|
|
"gc.collect()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 54,
|
|
"id": "e90052a9-d05c-418b-9daa-6831b7af5b3f",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import ctypes\n",
|
|
"def trim_memory() -> int:\n",
|
|
" libc = ctypes.CDLL(\"libc.so.6\")\n",
|
|
" return libc.malloc_trim(0)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 55,
|
|
"id": "47bda30a-a93a-437f-8025-422b76c3a682",
|
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"metadata": {
|
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"tags": []
|
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},
|
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"outputs": [
|
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{
|
|
"name": "stderr",
|
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"output_type": "stream",
|
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"text": [
|
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"2023-04-28 09:08:27,911 - distributed.utils_perf - WARNING - full garbage collections took 13% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:08:32,501 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:08:36,089 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:08:39,271 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:08:43,344 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
|
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"2023-04-28 09:08:47,329 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:22:29,074 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:23:10,350 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:23:49,683 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:24:34,795 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:25:14,922 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:25:59,410 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:26:56,132 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"text": [
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"wrap results\n",
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"(107627520,)\n"
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"text": [
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"1\n"
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"2023-04-28 09:46:00,337 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 09:48:51,714 - distributed.utils_perf - WARNING - full garbage collections took 15% CPU time recently (threshold: 10%)\n"
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{
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"segmenting 2\n",
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"wrap results\n",
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"(107627520,)\n"
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"output_type": "stream",
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"text": [
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"2\n"
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"2023-04-28 10:02:33,796 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
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"2023-04-28 10:03:20,597 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
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"2023-04-28 10:05:16,109 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
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"2023-04-28 10:07:28,457 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n"
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{
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"segmenting 2\n",
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"wrap results\n",
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"output_type": "stream",
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"text": [
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"3\n"
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"2023-04-28 10:21:12,471 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
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"2023-04-28 10:22:00,256 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
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"2023-04-28 10:23:44,218 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n",
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"2023-04-28 10:26:08,975 - distributed.utils_perf - WARNING - full garbage collections took 15% CPU time recently (threshold: 10%)\n"
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},
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{
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"segmenting 2\n",
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"wrap results\n",
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"(107627520,)\n"
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"text": [
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"4\n"
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"2023-04-28 10:40:42,002 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 10:42:35,835 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"segmenting 2\n",
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"wrap results\n",
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"text": [
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"5\n"
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"2023-04-28 11:00:35,482 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"create part 1\n",
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"segmenting 1\n",
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"wrap results\n",
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"segmenting 1\n",
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"2023-04-28 13:27:12,810 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n",
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"2023-04-28 13:28:02,144 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n",
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"2023-04-28 13:31:36,336 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n"
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"create part 1\n",
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"2023-04-28 14:05:04,603 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
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"2023-04-28 14:06:43,267 - distributed.utils_perf - WARNING - full garbage collections took 19% CPU time recently (threshold: 10%)\n",
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"2023-04-28 14:10:13,672 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n"
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"2023-04-28 14:13:35,523 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"2023-04-28 14:13:40,258 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n"
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"4\n"
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"2023-04-28 14:32:29,962 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"5\n"
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"2023-04-28 14:51:25,857 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"text": [
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"6\n"
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"2023-04-28 14:58:22,673 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 14:59:01,253 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 14:59:40,928 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:00:20,946 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:01:05,100 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:01:49,891 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:02:39,776 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:03:32,132 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:07:10,902 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"segmenting 2\n",
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"wrap results\n",
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"(107627520,)\n"
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"2023-04-28 15:10:36,955 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:10:41,352 - distributed.utils_perf - WARNING - full garbage collections took 16% CPU time recently (threshold: 10%)\n"
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"7\n"
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"2023-04-28 15:14:34,270 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:16:13,034 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:16:49,559 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:17:24,824 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:18:03,753 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:18:43,737 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:19:24,557 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:20:08,061 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:20:53,711 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:21:41,409 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:22:41,104 - distributed.utils_perf - WARNING - full garbage collections took 18% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:26:02,808 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n"
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},
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{
|
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"create part 1\n",
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"create part 2\n",
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"segmenting 1\n",
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"segmenting 2\n",
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"wrap results\n",
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"(107627520,)\n"
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2023-04-28 15:29:26,309 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
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"2023-04-28 15:29:30,723 - distributed.utils_perf - WARNING - full garbage collections took 17% CPU time recently (threshold: 10%)\n"
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"output_type": "stream",
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"text": [
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"8\n"
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"output_type": "stream",
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"text": [
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"2023-04-28 15:33:25,978 - distributed.core - ERROR - Timed out during handshake while connecting to tcp://127.0.0.1:36551 after 30 s\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/runners.py\", line 44, in run\n",
|
|
" return loop.run_until_complete(main)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/base_events.py\", line 636, in run_until_complete\n",
|
|
" self.run_forever()\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/base_events.py\", line 603, in run_forever\n",
|
|
" self._run_once()\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/base_events.py\", line 1868, in _run_once\n",
|
|
" event_list = self._selector.select(timeout)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/selectors.py\", line 469, in select\n",
|
|
" fd_event_list = self._selector.poll(timeout, max_ev)\n",
|
|
"KeyboardInterrupt\n",
|
|
"\n",
|
|
"During handling of the above exception, another exception occurred:\n",
|
|
"\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/comm/tcp.py\", line 225, in read\n",
|
|
" frames_nbytes = await stream.read_bytes(fmt_size)\n",
|
|
"asyncio.exceptions.CancelledError\n",
|
|
"\n",
|
|
"During handling of the above exception, another exception occurred:\n",
|
|
"\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/tasks.py\", line 456, in wait_for\n",
|
|
" return fut.result()\n",
|
|
"asyncio.exceptions.CancelledError\n",
|
|
"\n",
|
|
"The above exception was the direct cause of the following exception:\n",
|
|
"\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/comm/core.py\", line 328, in connect\n",
|
|
" handshake = await asyncio.wait_for(comm.read(), time_left())\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/asyncio/tasks.py\", line 458, in wait_for\n",
|
|
" raise exceptions.TimeoutError() from exc\n",
|
|
"asyncio.exceptions.TimeoutError\n",
|
|
"\n",
|
|
"The above exception was the direct cause of the following exception:\n",
|
|
"\n",
|
|
"Traceback (most recent call last)2023-04-28 15:33:28,390 - distributed.utils_perf - WARNING - full garbage collections took 14% CPU time recently (threshold: 10%)\n",
|
|
":\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/utils.py\", line 741, in wrapper\n",
|
|
" return await func(*args, **kwargs)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/worker.py\", line 1566, in close\n",
|
|
" await r.close_gracefully(reason=reason)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/core.py\", line 1224, in send_recv_from_rpc\n",
|
|
" comm = await self.pool.connect(self.addr)\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/core.py\", line 1468, in connect\n",
|
|
" return await connect_attempt\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/core.py\", line 1389, in _connect\n",
|
|
" comm = await connect(\n",
|
|
" File \"/mpc/homes/fische_r/miniconda3/lib/python3.10/site-packages/distributed/comm/core.py\", line 333, in connect\n",
|
|
" raise OSError(\n",
|
|
"OSError: Timed out during handshake while connecting to tcp://127.0.0.1:36551 after 30 s\n"
|
|
]
|
|
},
|
|
{
|
|
"ename": "KeyboardInterrupt",
|
|
"evalue": "",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
|
|
"Cell \u001b[0;32mIn[55], line 29\u001b[0m\n\u001b[1;32m 27\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhit the edge (one dimension 0), ignore\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 28\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[0;32m---> 29\u001b[0m part \u001b[38;5;241m=\u001b[39m \u001b[43mpart\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompute\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 30\u001b[0m \u001b[38;5;66;03m# try to release old unmanaged memory\u001b[39;00m\n\u001b[1;32m 31\u001b[0m client\u001b[38;5;241m.\u001b[39mrun(gc\u001b[38;5;241m.\u001b[39mcollect)\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/dask/base.py:314\u001b[0m, in \u001b[0;36mDaskMethodsMixin.compute\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 290\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompute\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 291\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Compute this dask collection\u001b[39;00m\n\u001b[1;32m 292\u001b[0m \n\u001b[1;32m 293\u001b[0m \u001b[38;5;124;03m This turns a lazy Dask collection into its in-memory equivalent.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 312\u001b[0m \u001b[38;5;124;03m dask.base.compute\u001b[39;00m\n\u001b[1;32m 313\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 314\u001b[0m (result,) \u001b[38;5;241m=\u001b[39m \u001b[43mcompute\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtraverse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 315\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m result\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/dask/base.py:599\u001b[0m, in \u001b[0;36mcompute\u001b[0;34m(traverse, optimize_graph, scheduler, get, *args, **kwargs)\u001b[0m\n\u001b[1;32m 596\u001b[0m keys\u001b[38;5;241m.\u001b[39mappend(x\u001b[38;5;241m.\u001b[39m__dask_keys__())\n\u001b[1;32m 597\u001b[0m postcomputes\u001b[38;5;241m.\u001b[39mappend(x\u001b[38;5;241m.\u001b[39m__dask_postcompute__())\n\u001b[0;32m--> 599\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[43mschedule\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdsk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkeys\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 600\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m repack([f(r, \u001b[38;5;241m*\u001b[39ma) \u001b[38;5;28;01mfor\u001b[39;00m r, (f, a) \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(results, postcomputes)])\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/distributed/client.py:3136\u001b[0m, in \u001b[0;36mClient.get\u001b[0;34m(self, dsk, keys, workers, allow_other_workers, resources, sync, asynchronous, direct, retries, priority, fifo_timeout, actors, **kwargs)\u001b[0m\n\u001b[1;32m 3134\u001b[0m should_rejoin \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 3135\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3136\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgather\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpacked\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43masynchronous\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43masynchronous\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdirect\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdirect\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3137\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m 3138\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m f \u001b[38;5;129;01min\u001b[39;00m futures\u001b[38;5;241m.\u001b[39mvalues():\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/distributed/client.py:2305\u001b[0m, in \u001b[0;36mClient.gather\u001b[0;34m(self, futures, errors, direct, asynchronous)\u001b[0m\n\u001b[1;32m 2303\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 2304\u001b[0m local_worker \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m-> 2305\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msync\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2306\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_gather\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2307\u001b[0m \u001b[43m \u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2308\u001b[0m \u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2309\u001b[0m \u001b[43m \u001b[49m\u001b[43mdirect\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdirect\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2310\u001b[0m \u001b[43m \u001b[49m\u001b[43mlocal_worker\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlocal_worker\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2311\u001b[0m \u001b[43m \u001b[49m\u001b[43masynchronous\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43masynchronous\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2312\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/distributed/utils.py:338\u001b[0m, in \u001b[0;36mSyncMethodMixin.sync\u001b[0;34m(self, func, asynchronous, callback_timeout, *args, **kwargs)\u001b[0m\n\u001b[1;32m 336\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m future\n\u001b[1;32m 337\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 338\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43msync\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 339\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallback_timeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback_timeout\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m 340\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/distributed/utils.py:401\u001b[0m, in \u001b[0;36msync\u001b[0;34m(loop, func, callback_timeout, *args, **kwargs)\u001b[0m\n\u001b[1;32m 399\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 400\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m e\u001b[38;5;241m.\u001b[39mis_set():\n\u001b[0;32m--> 401\u001b[0m \u001b[43mwait\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 403\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m error:\n\u001b[1;32m 404\u001b[0m typ, exc, tb \u001b[38;5;241m=\u001b[39m error\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/distributed/utils.py:390\u001b[0m, in \u001b[0;36msync.<locals>.wait\u001b[0;34m(timeout)\u001b[0m\n\u001b[1;32m 388\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwait\u001b[39m(timeout):\n\u001b[1;32m 389\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 390\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43me\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwait\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 391\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyboardInterrupt\u001b[39;00m:\n\u001b[1;32m 392\u001b[0m loop\u001b[38;5;241m.\u001b[39madd_callback(cancel)\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/threading.py:607\u001b[0m, in \u001b[0;36mEvent.wait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 605\u001b[0m signaled \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_flag\n\u001b[1;32m 606\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m signaled:\n\u001b[0;32m--> 607\u001b[0m signaled \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_cond\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwait\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 608\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m signaled\n",
|
|
"File \u001b[0;32m~/miniconda3/lib/python3.10/threading.py:324\u001b[0m, in \u001b[0;36mCondition.wait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 322\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 323\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m timeout \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m--> 324\u001b[0m gotit \u001b[38;5;241m=\u001b[39m \u001b[43mwaiter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43macquire\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 325\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 326\u001b[0m gotit \u001b[38;5;241m=\u001b[39m waiter\u001b[38;5;241m.\u001b[39macquire(\u001b[38;5;28;01mFalse\u001b[39;00m)\n",
|
|
"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"limit = 12\n",
|
|
"# TODO: Workaround: write intermediates to disk and restart dask client/scheduler/workers to get rid of unmanaged memory\n",
|
|
"# possible solution: do data handling on mpc2053 and calculations on mpc2959 -> leaves some RAM --> gc.collect() not necessary anymore\n",
|
|
"# appearantly starts to become critical after 12 iteratons\n",
|
|
"# from i=7, j=10 already done\n",
|
|
"# TODO write i and j to file to track progress even when closing jupyter\n",
|
|
"for i in range(1,limit):\n",
|
|
" pickle.dump(segs, open(os.path.join(training_path,'segs_temp.p'), 'wb'))\n",
|
|
" \n",
|
|
" print(str(i+1)+'/'+str(limit))\n",
|
|
" # plt.figure()\n",
|
|
" # plt.imshow(segs[:,100,:, 50])\n",
|
|
" # plt.savefig(os.path.join(training_path, sample+'_'+str(i)+'_progress.png'))\n",
|
|
" # client.run(gc.collect)\n",
|
|
" # client.run(trim_memory)\n",
|
|
" start = 0\n",
|
|
" if i == 1:\n",
|
|
" start = 8\n",
|
|
" for j in range(start,limit):\n",
|
|
" gc.collect() \n",
|
|
" client.run(gc.collect)\n",
|
|
" client.run(trim_memory)\n",
|
|
" print(j)\n",
|
|
" #with joblib.parallel_backend('dask'):\n",
|
|
" part = feat[i*dim1:(i+1)*dim1,:,j*dim2:(j+1)*dim2,:,:] #.persist() #compute() may blow up the memory ?! https://stackoverflow.com/questions/73770527/dask-compute-uses-twice-the-expected-memory\n",
|
|
" if 0 in part.shape:\n",
|
|
" print('hit the edge (one dimension 0), ignore')\n",
|
|
" continue\n",
|
|
" part = part.compute()\n",
|
|
" # try to release old unmanaged memory\n",
|
|
" client.run(gc.collect)\n",
|
|
" client.run(trim_memory)\n",
|
|
"\n",
|
|
" shp = part.shape\n",
|
|
" num_feat = part.shape[-1] \n",
|
|
" part = part.reshape(-1,num_feat)\n",
|
|
"\n",
|
|
" psplit = int(part.shape[0]/2)\n",
|
|
"\n",
|
|
" print('create part 1')\n",
|
|
" part1 = part[:psplit,:]\n",
|
|
" print('create part 2')\n",
|
|
" part2 = part[psplit:,:]\n",
|
|
" print('segmenting 1')\n",
|
|
"\n",
|
|
" # with joblib.parallel_backend('dask'):\n",
|
|
" seg1 = clf.predict(part1).astype(np.uint8)\n",
|
|
" del part1\n",
|
|
" print('segmenting 2')\n",
|
|
" # with joblib.parallel_backend('dask'):\n",
|
|
" seg2 = clf.predict(part2).astype(np.uint8)\n",
|
|
" print('wrap results')\n",
|
|
" del part2\n",
|
|
" del part\n",
|
|
" # gc.collect()\n",
|
|
"\n",
|
|
" seg = np.concatenate([seg1,seg2])\n",
|
|
" print(seg.shape)\n",
|
|
" del seg1\n",
|
|
" del seg2\n",
|
|
"\n",
|
|
" seg = seg.reshape(shp[:4]) #this step needs a lot of RAM ?! appearantly not\n",
|
|
" \n",
|
|
" # not sure if this switch cases are necessary\n",
|
|
" if i < limit-1 and j < limit-1:\n",
|
|
" segs[i*dim1:(i+1)*dim1,:,j*dim2:(j+1)*dim2,:] = seg\n",
|
|
" elif not i < limit-1 and j < limit-1:\n",
|
|
" segs[i*dim1:,:,j*dim2:(j+1)*dim2,:] = seg\n",
|
|
" elif not j < limit-1 and i < limit-1:\n",
|
|
" segs[i*dim1:(i+1)*dim1,:,j*dim2:,:] = seg\n",
|
|
" else:\n",
|
|
" segs[i*dim1:,:,j*dim2:,:] = seg\n",
|
|
" \n",
|
|
" del seg"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 58,
|
|
"id": "86258b73-db78-48c3-afed-b27cfce640cc",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"1"
|
|
]
|
|
},
|
|
"execution_count": 58,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"i"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 59,
|
|
"id": "e9c0bfab-54a5-4148-ab0d-50fefd15c191",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"8"
|
|
]
|
|
},
|
|
"execution_count": 59,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"j"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 57,
|
|
"id": "f3080841-2ec5-4191-81af-46c120485999",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.image.AxesImage at 0x7f61a8872200>"
|
|
]
|
|
},
|
|
"execution_count": 57,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.imshow(segs[:,50,:, 20])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 56,
|
|
"id": "e4a42896-cbca-4d8e-821b-219005a5cc5f",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"2023-04-28 15:34:27,314 - distributed.nanny - WARNING - Worker process still alive after 3.199999389648438 seconds, killing\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"pickle.dump(segs, open(os.path.join(training_path,'segs.p'), 'wb'))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c0648ac1-d7da-4133-ab59-c200556c9db1",
|
|
"metadata": {},
|
|
"source": [
|
|
"### save result to disk"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 62,
|
|
"id": "bf4ba5e8-f36a-4da5-acd8-ca02d1249dfa",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# TODO: include metadata in segmented nc and\n",
|
|
"\n",
|
|
"shp = segs.shape\n",
|
|
"segdata = xr.Dataset({'segmented': (['x','y','z','timestep'], segs),\n",
|
|
" 't_utc': ('timestep', t_utc),\n",
|
|
" 'time': ('timestep', time)},\n",
|
|
" coords = {'x': np.arange(shp[0]),\n",
|
|
" 'y': np.arange(shp[1]),\n",
|
|
" 'z': np.arange(shp[2]),\n",
|
|
" 'timestep': np.arange(shp[3]),\n",
|
|
" 'feature': TS.combined_feature_names}\n",
|
|
" )\n",
|
|
"segdata.attrs = data.attrs.copy()\n",
|
|
"segdata.attrs['05_ML_cropping'] = [a,b,c,d,e,f]\n",
|
|
"segdata.attrs['pytrain_git'] = pytrain_git_sha\n",
|
|
"segdata.attrs['05_coely_gitsha'] = git_sha\n",
|
|
"segdata.attrs['GDL_crop'] = GDL_crop"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 63,
|
|
"id": "51c993a5-14d0-4de4-a8cf-184ac08d713b",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"segpath = os.path.join(training_path_sample, sample+'water_segmentation.nc')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 64,
|
|
"id": "15a620c3-5aa0-4b39-ab7a-69b2a56a2ebe",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"segdata.to_netcdf(segpath)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 75,
|
|
"id": "c4a7dcb2-61db-4ba7-aa04-6f15dd4da86e",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# load intermediate result\n",
|
|
"seg_data = xr.load_dataset(segpath)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"id": "43fe30f1-1f0d-4a34-ab11-b82f3f25fc85",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"segs = seg_data['segmented'].data"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 61,
|
|
"id": "832a3333-8002-42fc-8300-165ec4f09642",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
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" width: auto;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dt {\n",
|
|
" font-weight: normal;\n",
|
|
" grid-column: 1;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dt:hover span {\n",
|
|
" display: inline-block;\n",
|
|
" background: var(--xr-background-color);\n",
|
|
" padding-right: 10px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dd {\n",
|
|
" grid-column: 2;\n",
|
|
" white-space: pre-wrap;\n",
|
|
" word-break: break-all;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-icon-database,\n",
|
|
".xr-icon-file-text2,\n",
|
|
".xr-no-icon {\n",
|
|
" display: inline-block;\n",
|
|
" vertical-align: middle;\n",
|
|
" width: 1em;\n",
|
|
" height: 1.5em !important;\n",
|
|
" stroke-width: 0;\n",
|
|
" stroke: currentColor;\n",
|
|
" fill: currentColor;\n",
|
|
"}\n",
|
|
"</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n",
|
|
"Dimensions: (x: 750, y: 340, z: 1916, timestep: 31, feature: 69)\n",
|
|
"Coordinates:\n",
|
|
" * x (x) int64 0 1 2 3 4 5 6 7 8 ... 742 743 744 745 746 747 748 749\n",
|
|
" * y (y) int64 0 1 2 3 4 5 6 7 8 ... 332 333 334 335 336 337 338 339\n",
|
|
" * z (z) int64 0 1 2 3 4 5 6 7 ... 1909 1910 1911 1912 1913 1914 1915\n",
|
|
" * timestep (timestep) int64 0 1 2 3 4 5 6 7 8 ... 22 23 24 25 26 27 28 29 30\n",
|
|
" * feature (feature) <U27 'diff_to_first_' ... 'full_temp_min_Gauss_2.0'\n",
|
|
"Data variables:\n",
|
|
" segmented (x, y, z, timestep) uint8 0 0 0 2 2 2 0 0 0 ... 0 0 0 0 0 0 0 0 0\n",
|
|
" t_utc (timestep) float64 1.667e+09 1.667e+09 ... 1.667e+09 1.667e+09\n",
|
|
" time (timestep) float64 7.036 6.218 66.42 126.6 ... 759.3 819.5 879.7\n",
|
|
"Attributes: (12/20)\n",
|
|
" name: 1\n",
|
|
" voxel size: 2.75 um\n",
|
|
" voxel: 2.75e-06\n",
|
|
" post rotation cropping coordinates [a:b,c:d,e:f]: [ 120 1062 320 972 ...\n",
|
|
" rotation angle 1: -22\n",
|
|
" rotation angle 2: -22\n",
|
|
" ... ...\n",
|
|
" 05_crop_githash: 761a49fa1ea416a28344b9...\n",
|
|
" git_sha_registration: 612e92b\n",
|
|
" githash_registration: 612e92b28895745f6b422c...\n",
|
|
" 05_ML_cropping: [120, 870, 10, 350, 50...\n",
|
|
" pytrain_git: e5b2d83\n",
|
|
" 05_coely_gitsha: 1c033ce</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e36dcb2e-b2a9-4843-8737-62e5534ca76c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e36dcb2e-b2a9-4843-8737-62e5534ca76c' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 750</li><li><span class='xr-has-index'>y</span>: 340</li><li><span class='xr-has-index'>z</span>: 1916</li><li><span class='xr-has-index'>timestep</span>: 31</li><li><span class='xr-has-index'>feature</span>: 69</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0b22b7a8-7e96-484a-9cf7-46f4ebb41d94' class='xr-section-summary-in' type='checkbox' checked><label for='section-0b22b7a8-7e96-484a-9cf7-46f4ebb41d94' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 745 746 747 748 749</div><input id='attrs-599bd993-f0f8-4cad-9f61-b76721b23491' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-599bd993-f0f8-4cad-9f61-b76721b23491' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4cbc03a-8d98-47af-b349-144a85f1ecdc' class='xr-var-data-in' type='checkbox'><label for='data-e4cbc03a-8d98-47af-b349-144a85f1ecdc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, ..., 747, 748, 749])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 335 336 337 338 339</div><input id='attrs-ed60b4f1-e078-4c74-9d26-6ad3942f49eb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ed60b4f1-e078-4c74-9d26-6ad3942f49eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa7b2d62-6c1f-4b4c-a521-c7f5173d54f9' class='xr-var-data-in' type='checkbox'><label for='data-aa7b2d62-6c1f-4b4c-a521-c7f5173d54f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, ..., 337, 338, 339])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1912 1913 1914 1915</div><input id='attrs-b52ee9bc-1c95-485d-8d77-d4893d52c941' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b52ee9bc-1c95-485d-8d77-d4893d52c941' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6825c668-d4b8-4729-9200-6ee3c4f783f9' class='xr-var-data-in' type='checkbox'><label for='data-6825c668-d4b8-4729-9200-6ee3c4f783f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, ..., 1913, 1914, 1915])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>timestep</span></div><div class='xr-var-dims'>(timestep)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 25 26 27 28 29 30</div><input id='attrs-27dbb65f-c491-4451-857d-962836d4d66d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-27dbb65f-c491-4451-857d-962836d4d66d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7deac5bf-b1ba-4c8b-ac11-df1f3fefe916' class='xr-var-data-in' type='checkbox'><label for='data-7deac5bf-b1ba-4c8b-ac11-df1f3fefe916' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
|
|
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>feature</span></div><div class='xr-var-dims'>(feature)</div><div class='xr-var-dtype'><U27</div><div class='xr-var-preview xr-preview'>'diff_to_first_' ... 'full_temp_...</div><input id='attrs-d0312fe9-7d85-4376-969b-6d8d031dd4af' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0312fe9-7d85-4376-969b-6d8d031dd4af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c770ce5-026c-4c80-b759-3c158dba3e42' class='xr-var-data-in' type='checkbox'><label for='data-7c770ce5-026c-4c80-b759-3c158dba3e42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(['diff_to_first_', 'diff_to_last_', 'Gaussian_4D_Blur_0.0',\n",
|
|
" 'Gaussian_4D_Blur_2.0', 'Gaussian_4D_Blur_4.0',\n",
|
|
" 'diff_of_gauss_4D_2.0_0.0', 'diff_of_gauss_4D_4.0_0.0',\n",
|
|
" 'diff_of_gauss_4D_4.0_2.0', 'Gradient_sigma_0.0_0',\n",
|
|
" 'Gradient_sigma_0.0_1', 'Gradient_sigma_0.0_2', 'Gradient_sigma_0.0_3',\n",
|
|
" 'hessian_sigma_0.0_00', 'hessian_sigma_0.0_01', 'hessian_sigma_0.0_02',\n",
|
|
" 'hessian_sigma_0.0_03', 'hessian_sigma_0.0_11', 'hessian_sigma_0.0_12',\n",
|
|
" 'hessian_sigma_0.0_13', 'hessian_sigma_0.0_22', 'hessian_sigma_0.0_23',\n",
|
|
" 'hessian_sigma_0.0_33', 'Gradient_sigma_2.0_0', 'Gradient_sigma_2.0_1',\n",
|
|
" 'Gradient_sigma_2.0_2', 'Gradient_sigma_2.0_3', 'hessian_sigma_2.0_00',\n",
|
|
" 'hessian_sigma_2.0_01', 'hessian_sigma_2.0_02', 'hessian_sigma_2.0_03',\n",
|
|
" 'hessian_sigma_2.0_11', 'hessian_sigma_2.0_12', 'hessian_sigma_2.0_13',\n",
|
|
" 'hessian_sigma_2.0_22', 'hessian_sigma_2.0_23', 'hessian_sigma_2.0_33',\n",
|
|
" 'Gradient_sigma_4.0_0', 'Gradient_sigma_4.0_1', 'Gradient_sigma_4.0_2',\n",
|
|
" 'Gradient_sigma_4.0_3', 'hessian_sigma_4.0_00', 'hessian_sigma_4.0_01',\n",
|
|
" 'hessian_sigma_4.0_02', 'hessian_sigma_4.0_03', 'hessian_sigma_4.0_11',\n",
|
|
" 'hessian_sigma_4.0_12', 'hessian_sigma_4.0_13', 'hessian_sigma_4.0_22',\n",
|
|
" 'hessian_sigma_4.0_23', 'hessian_sigma_4.0_33', 'Gaussian_time_0.0',\n",
|
|
" 'Gaussian_time_2.0', 'Gaussian_time_4.0', 'diff_of_gauss_time_2.0_0.0',\n",
|
|
" 'diff_of_gauss_time_4.0_0.0', 'diff_of_gauss_time_4.0_2.0',\n",
|
|
" 'Gaussian_space_0.0', 'Gaussian_space_2.0', 'Gaussian_space_4.0',\n",
|
|
" 'diff_of_gauss_space_2.0_0.0', 'diff_of_gauss_space_4.0_0.0',\n",
|
|
" 'diff_of_gauss_space_4.0_2.0', 'diff_to_min_',\n",
|
|
" 'diff_temp_min_Gauss_2.0', 'first_', 'last_', 'full_temp_mean_',\n",
|
|
" 'full_temp_min_', 'full_temp_min_Gauss_2.0'], dtype='<U27')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4de8148f-c0f9-481d-a687-141cc60a53f8' class='xr-section-summary-in' type='checkbox' checked><label for='section-4de8148f-c0f9-481d-a687-141cc60a53f8' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>segmented</span></div><div class='xr-var-dims'>(x, y, z, timestep)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 2 2 2 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-f0097090-0f7c-425d-8864-6691efd058e8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f0097090-0f7c-425d-8864-6691efd058e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f1a6689-b156-44e3-92fd-cff8f1e88c6f' class='xr-var-data-in' type='checkbox'><label for='data-2f1a6689-b156-44e3-92fd-cff8f1e88c6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[0, 0, 0, ..., 1, 1, 1],\n",
|
|
" [0, 0, 0, ..., 1, 1, 1],\n",
|
|
" [0, 0, 0, ..., 1, 1, 1],\n",
|
|
" ...,\n",
|
|
" [2, 2, 2, ..., 1, 1, 1],\n",
|
|
" [2, 2, 2, ..., 1, 1, 1],\n",
|
|
" [2, 2, 0, ..., 1, 1, 1]],\n",
|
|
"\n",
|
|
" [[0, 0, 0, ..., 1, 1, 1],\n",
|
|
" [0, 0, 0, ..., 1, 1, 1],\n",
|
|
" [0, 0, 0, ..., 1, 1, 1],\n",
|
|
" ...,\n",
|
|
" [2, 2, 2, ..., 1, 1, 1],\n",
|
|
" [2, 2, 2, ..., 1, 1, 1],\n",
|
|
" [2, 2, 0, ..., 1, 1, 1]],\n",
|
|
"\n",
|
|
" [[2, 2, 0, ..., 1, 1, 1],\n",
|
|
" [2, 2, 0, ..., 1, 1, 1],\n",
|
|
" [2, 2, 0, ..., 1, 1, 1],\n",
|
|
" ...,\n",
|
|
"...\n",
|
|
" ...,\n",
|
|
" [0, 0, 0, ..., 2, 0, 0],\n",
|
|
" [0, 0, 0, ..., 2, 0, 0],\n",
|
|
" [0, 0, 0, ..., 0, 0, 0]],\n",
|
|
"\n",
|
|
" [[0, 0, 0, ..., 0, 0, 0],\n",
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
" ...,\n",
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
" [0, 0, 0, ..., 0, 0, 0]],\n",
|
|
"\n",
|
|
" [[0, 0, 0, ..., 0, 0, 0],\n",
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
" ...,\n",
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
" [0, 2, 0, ..., 0, 0, 0],\n",
|
|
" [2, 0, 0, ..., 0, 0, 0]]]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t_utc</span></div><div class='xr-var-dims'>(timestep)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.667e+09 1.667e+09 ... 1.667e+09</div><input id='attrs-9596668f-c8fb-4b9d-aa4c-d87abffbb74c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9596668f-c8fb-4b9d-aa4c-d87abffbb74c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2e2ee0b-2c78-4eca-aeee-316fabd98262' class='xr-var-data-in' type='checkbox'><label for='data-f2e2ee0b-2c78-4eca-aeee-316fabd98262' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.66722001e+09, 1.66722040e+09, 1.66722046e+09, 1.66722052e+09,\n",
|
|
" 1.66722058e+09, 1.66722064e+09, 1.66722070e+09, 1.66722076e+09,\n",
|
|
" 1.66722082e+09, 1.66722088e+09, 1.66722095e+09, 1.66722101e+09,\n",
|
|
" 1.66722107e+09, 1.66722113e+09, 1.66722119e+09, 1.66722125e+09,\n",
|
|
" 1.66722142e+09, 1.66722148e+09, 1.66722154e+09, 1.66722160e+09,\n",
|
|
" 1.66722166e+09, 1.66722172e+09, 1.66722178e+09, 1.66722184e+09,\n",
|
|
" 1.66722190e+09, 1.66722196e+09, 1.66722202e+09, 1.66722209e+09,\n",
|
|
" 1.66722215e+09, 1.66722221e+09, 1.66722227e+09])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>(timestep)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.036 6.218 66.42 ... 819.5 879.7</div><input id='attrs-6ccf0fb9-e144-43d3-9ef4-cf939aab1377' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ccf0fb9-e144-43d3-9ef4-cf939aab1377' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd69a095-bfa6-4160-a706-8df873966f3d' class='xr-var-data-in' type='checkbox'><label for='data-dd69a095-bfa6-4160-a706-8df873966f3d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 7.0355083, 6.2176226, 66.424704 , 126.6437905, 186.8748772,\n",
|
|
" 247.0959636, 307.2980496, 367.5261356, 427.75722 , 487.9903053,\n",
|
|
" 548.1683904, 608.3904758, 668.6175608, 728.8406441, 789.0717297,\n",
|
|
" 849.2918141, 36.6449636, 96.8650426, 157.0971262, 217.3022106,\n",
|
|
" 277.5122954, 337.7453791, 397.9744636, 458.1985478, 518.4136323,\n",
|
|
" 578.6417168, 638.8698003, 699.1018843, 759.3249683, 819.5310523,\n",
|
|
" 879.7401363])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a5edcbd5-c783-4c83-ade6-198d4e2ba382' class='xr-section-summary-in' type='checkbox' ><label for='section-a5edcbd5-c783-4c83-ade6-198d4e2ba382' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1147dd78-10b3-4a44-ba6d-770db05ecc16' class='xr-index-data-in' type='checkbox'/><label for='index-1147dd78-10b3-4a44-ba6d-770db05ecc16' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,\n",
|
|
" ...\n",
|
|
" 740, 741, 742, 743, 744, 745, 746, 747, 748, 749],\n",
|
|
" dtype='int64', name='x', length=750))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4ad68dba-a6b4-4193-b2c3-3ab12f0b70c1' class='xr-index-data-in' type='checkbox'/><label for='index-4ad68dba-a6b4-4193-b2c3-3ab12f0b70c1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,\n",
|
|
" ...\n",
|
|
" 330, 331, 332, 333, 334, 335, 336, 337, 338, 339],\n",
|
|
" dtype='int64', name='y', length=340))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>z</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-609aab03-abd8-4c1b-9dc7-70fc4577099a' class='xr-index-data-in' type='checkbox'/><label for='index-609aab03-abd8-4c1b-9dc7-70fc4577099a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,\n",
|
|
" ...\n",
|
|
" 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915],\n",
|
|
" dtype='int64', name='z', length=1916))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>timestep</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9fda7851-b6d6-4efe-bcc4-96695610138b' class='xr-index-data-in' type='checkbox'/><label for='index-9fda7851-b6d6-4efe-bcc4-96695610138b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,\n",
|
|
" 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],\n",
|
|
" dtype='int64', name='timestep'))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>feature</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1eaf92ef-dbf4-4526-80a6-d5de02ca235d' class='xr-index-data-in' type='checkbox'/><label for='index-1eaf92ef-dbf4-4526-80a6-d5de02ca235d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index(['diff_to_first_', 'diff_to_last_', 'Gaussian_4D_Blur_0.0',\n",
|
|
" 'Gaussian_4D_Blur_2.0', 'Gaussian_4D_Blur_4.0',\n",
|
|
" 'diff_of_gauss_4D_2.0_0.0', 'diff_of_gauss_4D_4.0_0.0',\n",
|
|
" 'diff_of_gauss_4D_4.0_2.0', 'Gradient_sigma_0.0_0',\n",
|
|
" 'Gradient_sigma_0.0_1', 'Gradient_sigma_0.0_2', 'Gradient_sigma_0.0_3',\n",
|
|
" 'hessian_sigma_0.0_00', 'hessian_sigma_0.0_01', 'hessian_sigma_0.0_02',\n",
|
|
" 'hessian_sigma_0.0_03', 'hessian_sigma_0.0_11', 'hessian_sigma_0.0_12',\n",
|
|
" 'hessian_sigma_0.0_13', 'hessian_sigma_0.0_22', 'hessian_sigma_0.0_23',\n",
|
|
" 'hessian_sigma_0.0_33', 'Gradient_sigma_2.0_0', 'Gradient_sigma_2.0_1',\n",
|
|
" 'Gradient_sigma_2.0_2', 'Gradient_sigma_2.0_3', 'hessian_sigma_2.0_00',\n",
|
|
" 'hessian_sigma_2.0_01', 'hessian_sigma_2.0_02', 'hessian_sigma_2.0_03',\n",
|
|
" 'hessian_sigma_2.0_11', 'hessian_sigma_2.0_12', 'hessian_sigma_2.0_13',\n",
|
|
" 'hessian_sigma_2.0_22', 'hessian_sigma_2.0_23', 'hessian_sigma_2.0_33',\n",
|
|
" 'Gradient_sigma_4.0_0', 'Gradient_sigma_4.0_1', 'Gradient_sigma_4.0_2',\n",
|
|
" 'Gradient_sigma_4.0_3', 'hessian_sigma_4.0_00', 'hessian_sigma_4.0_01',\n",
|
|
" 'hessian_sigma_4.0_02', 'hessian_sigma_4.0_03', 'hessian_sigma_4.0_11',\n",
|
|
" 'hessian_sigma_4.0_12', 'hessian_sigma_4.0_13', 'hessian_sigma_4.0_22',\n",
|
|
" 'hessian_sigma_4.0_23', 'hessian_sigma_4.0_33', 'Gaussian_time_0.0',\n",
|
|
" 'Gaussian_time_2.0', 'Gaussian_time_4.0', 'diff_of_gauss_time_2.0_0.0',\n",
|
|
" 'diff_of_gauss_time_4.0_0.0', 'diff_of_gauss_time_4.0_2.0',\n",
|
|
" 'Gaussian_space_0.0', 'Gaussian_space_2.0', 'Gaussian_space_4.0',\n",
|
|
" 'diff_of_gauss_space_2.0_0.0', 'diff_of_gauss_space_4.0_0.0',\n",
|
|
" 'diff_of_gauss_space_4.0_2.0', 'diff_to_min_',\n",
|
|
" 'diff_temp_min_Gauss_2.0', 'first_', 'last_', 'full_temp_mean_',\n",
|
|
" 'full_temp_min_', 'full_temp_min_Gauss_2.0'],\n",
|
|
" dtype='object', name='feature'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d755de90-46f4-4704-9586-42b17ecb02f9' class='xr-section-summary-in' type='checkbox' ><label for='section-d755de90-46f4-4704-9586-42b17ecb02f9' class='xr-section-summary' >Attributes: <span>(20)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>1</dd><dt><span>voxel size :</span></dt><dd>2.75 um</dd><dt><span>voxel :</span></dt><dd>2.75e-06</dd><dt><span>post rotation cropping coordinates [a:b,c:d,e:f] :</span></dt><dd>[ 120 1062 320 972 0 2016]</dd><dt><span>rotation angle 1 :</span></dt><dd>-22</dd><dt><span>rotation angle 2 :</span></dt><dd>-22</dd><dt><span>git_sha_rotation :</span></dt><dd>2e4dec6</dd><dt><span>githash_rotation :</span></dt><dd>2e4dec6a6358ec0b6c95cac935d9648b716189a9</dd><dt><span>image_data_names :</span></dt><dd><scan>_iamge_data_<time_step>, e.g. 02_image_data_00 is the first time step of scan 02</dd><dt><span>03_crop_git_sha :</span></dt><dd>761a49f</dd><dt><span>03_crop_githash :</span></dt><dd>761a49fa1ea416a28344b9f2e885a2e83f94996c</dd><dt><span>04_crop_git_sha :</span></dt><dd>761a49f</dd><dt><span>04_crop_githash :</span></dt><dd>761a49fa1ea416a28344b9f2e885a2e83f94996c</dd><dt><span>05_crop_git_sha :</span></dt><dd>761a49f</dd><dt><span>05_crop_githash :</span></dt><dd>761a49fa1ea416a28344b9f2e885a2e83f94996c</dd><dt><span>git_sha_registration :</span></dt><dd>612e92b</dd><dt><span>githash_registration :</span></dt><dd>612e92b28895745f6b422c556fb8aa7ad376baeb</dd><dt><span>05_ML_cropping :</span></dt><dd>[120, 870, 10, 350, 50, -50]</dd><dt><span>pytrain_git :</span></dt><dd>e5b2d83</dd><dt><span>05_coely_gitsha :</span></dt><dd>1c033ce</dd></dl></div></li></ul></div></div>"
|
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],
|
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"text/plain": [
|
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"<xarray.Dataset>\n",
|
|
"Dimensions: (x: 750, y: 340, z: 1916, timestep: 31, feature: 69)\n",
|
|
"Coordinates:\n",
|
|
" * x (x) int64 0 1 2 3 4 5 6 7 8 ... 742 743 744 745 746 747 748 749\n",
|
|
" * y (y) int64 0 1 2 3 4 5 6 7 8 ... 332 333 334 335 336 337 338 339\n",
|
|
" * z (z) int64 0 1 2 3 4 5 6 7 ... 1909 1910 1911 1912 1913 1914 1915\n",
|
|
" * timestep (timestep) int64 0 1 2 3 4 5 6 7 8 ... 22 23 24 25 26 27 28 29 30\n",
|
|
" * feature (feature) <U27 'diff_to_first_' ... 'full_temp_min_Gauss_2.0'\n",
|
|
"Data variables:\n",
|
|
" segmented (x, y, z, timestep) uint8 0 0 0 2 2 2 0 0 0 ... 0 0 0 0 0 0 0 0 0\n",
|
|
" t_utc (timestep) float64 1.667e+09 1.667e+09 ... 1.667e+09 1.667e+09\n",
|
|
" time (timestep) float64 7.036 6.218 66.42 126.6 ... 759.3 819.5 879.7\n",
|
|
"Attributes: (12/20)\n",
|
|
" name: 1\n",
|
|
" voxel size: 2.75 um\n",
|
|
" voxel: 2.75e-06\n",
|
|
" post rotation cropping coordinates [a:b,c:d,e:f]: [ 120 1062 320 972 ...\n",
|
|
" rotation angle 1: -22\n",
|
|
" rotation angle 2: -22\n",
|
|
" ... ...\n",
|
|
" 05_crop_githash: 761a49fa1ea416a28344b9...\n",
|
|
" git_sha_registration: 612e92b\n",
|
|
" githash_registration: 612e92b28895745f6b422c...\n",
|
|
" 05_ML_cropping: [120, 870, 10, 350, 50...\n",
|
|
" pytrain_git: e5b2d83\n",
|
|
" 05_coely_gitsha: 1c033ce"
|
|
]
|
|
},
|
|
"execution_count": 61,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"segdata"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "4d280b19-516e-4393-a009-9e5d4781379d",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.12"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|