Unverified Commit 7ca49061 authored by Lauren Adoram-Kershner's avatar Lauren Adoram-Kershner Committed by GitHub
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updated NBs plus code mods to get autocnet to work with ISIS4 (#515) 

* updated NBs plus code mods to get autocnet to work with ISIS4

* updated network_generation notebook

* Delete autocnet_intro.ipynb

Did a force push to get my changes up and it brought this file back. Still do not need it.

* reverting subpixel change
parent 18ab9ecf

autocnet/graph/network.py

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@@ -1708,7 +1708,7 @@ class NetworkCandidateGraph(CandidateGraph): 
        isisroot = env['ISISROOT']

        isisdata = env['ISISDATA']



        isissetup = f'export ISISROOT={isisroot} && export ISIS3DATA={isisdata}'

        isissetup = f'export ISISROOT={isisroot} && export ISIS3DATA={isisdata} && export ISISDATA={isisdata}'

        condasetup = f'conda activate {condaenv}'

        job = f'acn_submit -r={rhost} -p={rport} {processing_queue}'

        command = f'{condasetup} && {isissetup} && {job}'

docs/users/workshops/FY21_workshop/autocnet_intro.ipynb

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%% Cell type:code id: tags:



``` python

    The components of the NetworkCandidateGraph



    The database structures



    Apply & cluster processing



    How to generate a control network purely in autocnet (Use the Phobos)



    Sub-pixel registration



    Cross-instrument matching



    How to ingest an ISIS control network



    Overlap analysis



    Outlier detection



    Custom cost functions

```



%% Cell type:markdown id: tags:



# AutoCNet Intro

AutoCNet is a suite of functions that parallelize network generation and analyze the health of networks. Networks within AutoCNet are represented with an [undirected graph](https://en.wikipedia.org/wiki/Graph_(discrete_mathematics)), called a NetworkCandidateGraph.



It leverages a database for presistent storage of the images, points, and measures of a network. The use of this database allows for quick access of each elements geometries and how those geometries relate with one another.



%% Cell type:markdown id: tags:



# Components of The NetworkCandidateGraph



%% Cell type:markdown id: tags:



# Database Table Structures

This includes:

- camera

- costs

- edges

- images

- keypoints

- matches

- measures

- overlay

- points



%% Cell type:code id: tags:



``` python

```

docs/users/workshops/FY21_workshop/network_generation.ipynb

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