More abstracted sensor updates

### Added

- Ability to choose whether to compute overlaps for a network candidate graph

- Integration tests for end-to-end of an equatorial CTX pair and a mid-latitude CTX trio.

- AGeoDataset class that abstracts the plio GeoDataset class. The AGeoDataset includes sensor models on the GeoDataset object. The object automatically instantiates an autocnet surface model using either an EllipsoidDem or a GdalDem. ISIS sensor models use the DEM defined on the cube. CSM sensor models must have a DEM explicitly passed.

### Changed

- CI on the library now uses a mocked sqlalchemy connection. All tests can now run locally without the need for a supplemental postgres container. This changed removed some non-optimal tests that were testing datbase triggers and database instantiation handled by SQLAlchemy.

                                 Cameras, Base, Overlay, Edges,\

                                 Costs, Measures, Points, Measures

from autocnet.io.db.wrappers import DbDataFrame

from autocnet.io.geodataset import AGeoDataset

from plio.io.io_gdal import GeoDataset

from csmapi import csmapi

# set up the logging file

        Estimate a source and destination minimum bounding rectangle, in

        pixel space.

        """

        if not isinstance(self.source.geodata, GeoDataset):

        if not isinstance(self.source.geodata, AGeoDataset):

            smbr = None

            dmbr = None

        else:

from plio.io.io_controlnetwork import to_isis, from_isis

from plio.io import io_hdf, io_json

from plio.utils import utils as io_utils

from plio.io.io_gdal import GeoDataset

from plio.io.isis_serial_number import generate_serial_number

from plio.io import io_controlnetwork as cnet

from plurmy import Slurm

import autocnet

from autocnet.config_parser import parse_config

from autocnet.cg import cg

from autocnet.graph.asynchronous_funcs import watch_insert_queue, watch_update_queue

from autocnet.io.db.model import (Images, Keypoints, Matches, Cameras, Points,

                                  Base, Overlay, Edges, Costs, Measures, CandidateGroundPoints,

                                  JsonEncoder, try_db_creation)

from autocnet.io.db.connection import new_connection, Parent

from autocnet.io.db.connection import new_connection

from autocnet.io.geodataset import AGeoDataset

from autocnet.matcher import subpixel

from autocnet.matcher import cross_instrument_matcher as cim

from autocnet.vis.graph_view import plot_graph, cluster_plot

            filelist = io_utils.file_to_list(filelist)

        # TODO: Reject unsupported file formats + work with more file formats

        if basepath:

            datasets = [GeoDataset(os.path.join(basepath, f))

            datasets = [AGeoDataset(os.path.join(basepath, f))

                        for f in filelist]

        else:

            datasets = [GeoDataset(f) for f in filelist]

            datasets = [AGeoDataset(f) for f in filelist]

        # This is brute force for now, could swap to an RTree at some point.

        adjacency_dict = {}

from osgeo import ogr

import numpy as np

import pandas as pd

from plio.io import io_gdal

from shapely.geometry import Polygon as Poly

from autocnet.matcher import cpu_outlier_detector as od

from autocnet.examples import get_path

from autocnet.graph.network import CandidateGraph

from autocnet.utils.utils import array_to_poly

from autocnet.io.geodataset import AGeoDataset

from .. import edge

from .. import node

        destination = Mock(spec = node.Node)

        e.destination = destination

        e.source = source

        geodata_s = Mock(spec = io_gdal.GeoDataset)

        geodata_d = Mock(spec = io_gdal.GeoDataset)

        geodata_s = Mock(spec = AGeoDataset)

        geodata_d = Mock(spec = AGeoDataset)

        source.geodata = geodata_s

        destination.geodata = geodata_d

        e.source = source_node

        e.destination = destination_node

        source_geodata = PropertyMock(spec=io_gdal.GeoDataset)

        destination_geodata = PropertyMock(spec=io_gdal.GeoDataset)

        source_geodata = PropertyMock(spec=AGeoDataset)

        destination_geodata = PropertyMock(spec=AGeoDataset)

        e.source.geodata = source_geodata

        e.destination.geodata = destination_geodata

import geopandas as gpd

import numpy as np

from osgeo import ogr

from plio.io import io_gdal

from autocnet.examples import get_path

from .. import network

from .. import edge

from .. import node

import warnings

sys.path.insert(0, os.path.abspath('..'))

    good_poly = ogr.CreateGeometryFromWkt('POLYGON ((30 10, 40 40, 20 40, 10 20, 30 10))')

    bad_poly = ogr.CreateGeometryFromWkt('POLYGON ((9999 10, 40 40, 20 40, 10 20, 30 10))')

    with patch('plio.io.io_gdal.GeoDataset.footprint', new_callable=PropertyMock) as patch_fp:

    with patch('autocnet.io.geodataset.AGeoDataset.footprint', new_callable=PropertyMock) as patch_fp:

        patch_fp.return_value = good_poly

        n = network.CandidateGraph.from_filelist(mock_list, get_path('Apollo15'))

        assert n.number_of_nodes() == 6