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fanc-fly-2.0.4
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مشاهده بیشترتوضیحات
Tools for the Female Adult Nerve Cord Drosophila EM dataset
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | fanc-fly-2.0.4 |
| نام | fanc-fly |
| نسخه کتابخانه | 2.0.4 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Jasper Phelps |
| ایمیل نویسنده | jasper.s.phelps@gmail.com |
| آدرس صفحه اصلی | https://github.com/htem/FANC_auto_recon |
| آدرس اینترنتی | https://pypi.org/project/fanc-fly/ |
| مجوز | - |
# FANC_auto_recon
FANC (pronounced "fancy") is the Female Adult Nerve Cord, a GridTape-TEM dataset of an adult _Drosophila melanogaster_'s ventral nerve cord. The dataset was first published in [Phelps, Hildebrand, Graham et al. 2021 _Cell_](https://www.lee.hms.harvard.edu/phelps-hildebrand-graham-et-al-2021), after which we applied automated methods for reconstructing neurons, synapses, and nuclei to accelerate reconstruction of the ventral nerve cord connectome. This repository contains a python package for interacting with the connectome (see the folder [`fanc`](fanc)) as well as other supporting files.
Have any questions? Please [open an issue](https://github.com/htem/FANC_auto_recon/issues/new) or contact [Jasper Phelps (jasper.s.phelps@gmail.com)](https://github.com/jasper-tms).
## Installing and configuring the `fanc` python package
### Before you start
As is always the case in python, consider making a virtual environment (using your preference of virtualenv/virtualenvwrapper or conda) before installing.
### Installation option 1: pip install from PyPI
pip install fanc-fly
### Installation option 2: pip install directly from GitHub
The code on GitHub will sometimes be slightly more up to date than the version on PyPI
pip install git+https://github.com/htem/FANC_auto_recon.git
### Installation option 3: Clone then install
This is the best option if you want to make changes yourself to the code
cd ~/repos # or wherever you keep your repos
git clone https://github.com/htem/FANC_auto_recon.git
cd FANC_auto_recon
pip install -e .
### Provide credentials
Access to the latest reconstruction of FANC is restricted to authorized users. If you are a member of the FANC community (see [Collaborative community](../../wiki#collaborative-community) on this repo's wiki) and have been granted access, you can generate an API key by visiting [https://global.daf-apis.com/auth/api/v1/create_token](https://global.daf-apis.com/auth/api/v1/create_token) and logging in with your FANC-authorized google account. Copy the key that is displayed, then run the following commands in python to save your key to the appropriate file:
```python
import fanc
fanc.save_cave_credentials("THE API KEY YOU COPIED")
```
Alternatively, you can manually do what the command above accomplishes, which is to create a text file at `~/.cloudvolume/secrets/cave-secret.json` with these contents:
{
"token": "THE API KEY YOU COPIED",
"fanc_production_mar2021": "THE API KEY YOU COPIED"
}
You can verify that your API key has been saved successfully by running:
```python
import fanc
client = fanc.get_caveclient()
```
### Optional installation steps for additional functionality
#### Install Elastix to transform neurons into alignment with the VNC template
The mesh manipulation and coordinate transform code requires `pytransformix`, which is itself a Python wrapper for Elastix. Therefore, Elastix must be installed and its lib and bin paths must be appended to the `LD_LIBRARY_PATH` and `PATH` environment variables. See [`pytransformix` documentation](https://github.com/jasper-tms/pytransformix#installation) for specific instructions.
#### Provide CATMAID credentials to pull data from CATMAID
You can get your CATMAID API key by logging into https://radagast.hms.harvard.edu/catmaidvnc then hovering over "You are [Your Name]" in the top-right corner, then clicking "Get API token".
Save your CATMAID API key by running:
```python
import fanc
fanc.catmaid.save_catmaid_credentials("YOUR CATMAID API KEY")
```
You can verify that your API key has been saved successfully by running:
```python
import fanc
fanc.catmaid.connect()
```
## Documentation
- First go through [`fanc_python_package_examples.ipynb`](https://github.com/htem/FANC_auto_recon/blob/main/example_notebooks/fanc_python_package_examples.ipynb)
- Then check out other notebooks in [`example_notebooks/`](https://github.com/htem/FANC_auto_recon/tree/main/example_notebooks)
- Finally you can [browse the code](https://github.com/htem/FANC_auto_recon/tree/main/fanc), check out modules that have names that interest you, and read the docstrings.
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy |
| - | matplotlib |
| - | cloud-volume |
| - | python-catmaid |
| - | meshparty |
| - | navis |
| - | flybrains |
| - | transformix |
| - | nglui |
| - | pyperclip |
| - | numpyimage |
| - | pandas |
| - | connected-components-3d |
| - | fill-voids |
| - | task-queue |
| - | caveclient |
| - | cloud-files |
| - | urllib3 |
| - | trimesh |
| - | pcg-skel |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl fanc-fly-2.0.4:
pip install fanc-fly-2.0.4.whl
نصب پکیج tar.gz fanc-fly-2.0.4:
pip install fanc-fly-2.0.4.tar.gz