Skip to main content

donato lab [ca] imaging tools

Project description

manifolds project @ Donato lab

Installation

Recommended steps

  1. Open a command-line interface preferably inside the conda enviroment on your operating system (Windows, Mac)

  2. Use command-line to make a conda enviorment for running manifolds project:

conda create -n manifolds python=3.8

  1. Activate environment:

conda activate manifolds

  1. Install dependencies (might have to do them 1 at a time; eventually will have a script for this)

pip install: matplotlib, os, numpy, scipy, tqdm, sklearn, pickle, parmap, networkx, pandas, cv2

  1. Install jupyter notebook

conda install -c anaconda jupyter

  1. Download and unzip the Donatolab binarization repo (https://github.com/donatolab/manifolds, click onthe green "Code" button)

  2. Start jupyer notebook by typing it in at the command line

jupyter notebook

  1. Navigate to the folder where the code unzipped and click on this file to start the jupyter notebook:

"Binarize_Suite2p_Inscopix.ipynb"

  1. Run the first cell and then input the location of your suite2p folder in 2nd cell. Run the rest of the notebook.

  2. The code will save 2 files: binarized_traces.npz (a python numpy file) and binarized_traces.mat (a matlab file).

10(Optional) You can then use the last cell to visualize the traces and binarized versions for any specific cell.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

donlabtools-0.22.tar.gz (14.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

donlabtools-0.22-py3-none-any.whl (14.2 kB view details)

Uploaded Python 3

File details

Details for the file donlabtools-0.22.tar.gz.

File metadata

  • Download URL: donlabtools-0.22.tar.gz
  • Upload date:
  • Size: 14.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 colorama/0.4.4 importlib-metadata/4.6.4 keyring/23.5.0 pkginfo/1.8.2 readme-renderer/34.0 requests-toolbelt/0.9.1 requests/2.25.1 rfc3986/1.5.0 tqdm/4.57.0 urllib3/1.26.5 CPython/3.10.6

File hashes

Hashes for donlabtools-0.22.tar.gz
Algorithm Hash digest
SHA256 031777f70a5b0d9de00d60a1220822fd2c65aea24f1385a3a277261440d9553e
MD5 61fa133129e56355c272f36b841792db
BLAKE2b-256 77604a052a02c28561b6deb4e9ac83e23c4228c1ed36046174ef60200a93ef1c

See more details on using hashes here.

File details

Details for the file donlabtools-0.22-py3-none-any.whl.

File metadata

  • Download URL: donlabtools-0.22-py3-none-any.whl
  • Upload date:
  • Size: 14.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 colorama/0.4.4 importlib-metadata/4.6.4 keyring/23.5.0 pkginfo/1.8.2 readme-renderer/34.0 requests-toolbelt/0.9.1 requests/2.25.1 rfc3986/1.5.0 tqdm/4.57.0 urllib3/1.26.5 CPython/3.10.6

File hashes

Hashes for donlabtools-0.22-py3-none-any.whl
Algorithm Hash digest
SHA256 091d0ebce3c5d578a52654a0dc202f34aab81b5417260678b6987ec7f5d35113
MD5 7931ae5ecfb8f94df673d66ce6c9c4ce
BLAKE2b-256 06c33bce5144ca54b4f0eba83fbcdb07bd900b4145b0794ddcb35fa34680f0d0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page