More CI updates

      fail-fast: false

      matrix:

       os: [ubuntu-latest]

       python-version: ["3.7", "3.8", "3.9", "3.10", "3.11"]

       python-version: ["3.7", "3.8", "3.9", "3.10"]

    defaults:

      run:

        shell: bash -l {0}

import os

import pytest

import sys

import pandas as pd

from plio.io.io_controlnetwork import IsisControlNetwork

from autocnet.io.db import model

from autocnet.graph.network import NetworkCandidateGraph

from unittest.mock import patch, PropertyMock, MagicMock

if sys.platform.startswith("darwin"):

    pytest.skip("skipping DB tests for MacOS", allow_module_level=True)

@pytest.fixture()

def cnet():

    return IsisControlNetwork.from_dict({

            'id' : [1, 2, 3],

            'pointType' : [2]*3,

            'pointChoosername' : ['findfeatures']*3,

            'pointDatetime' : ['YYYY-MM-DDT00:00:00']*3,

            'pointEditLock': [False]*3,

            'pointIgnore' : [False]*3,

            'pointJigsawRejected': [False]*3,

            'referenceIndex' : [0]*3,

            'aprioriSurfPointSource': ['ground']*3,

            'aprioriSurfPointSourceFile' : ['ground.file']*3,

            'aprioriRadiusSource' : ['radius']*3, 

            'aprioriRadiusSourceFile' : ['radius.file']*3, 

            'latitudeConstrained' : [False]*3,

            'longitudeConstrained' : [False]*3, 

            'radiusConstrained' : [False]*3,

            'aprioriX' : [1017046.81161667, -1402345.22133465, 103571.17894436],

            'aprioriY' : [1017046.81161667, -1402345.22133465, 103571.17894436],

            'aprioriZ' : [1014022.55349016, -1404707.80219809, 101009.09763132],

            'aprioriCovar' : [[]]*3,

            'adjustedX' : [0]*3,

            'adjustedY' : [0]*3,

            'adjustedZ' : [0]*3,

            'adjustedCovar' : [[]]*3,

            'pointLog' : [[]]*3,

            'serialnumber' : ['SN1345', 'SN2348', 'SN9730'],

            'measureType' : [1]*3,

            'sample' : [2]*3,

            'line' : [1]*3,

            'sampleResidual' : [0.1]*3,

            'lineResidual' : [0.1]*3,

            'measureChoosername' : ['pointreg']*3,

            'measureDatetime' : ['YYYY-MM-DDT00:00:00']*3,

            'measureEditLock' : [False]*3,

            'measureIgnore': [False]*3,

            'measureJigsawRejected': [False]*3,

            'diameter' : [1000]*3,

            'apriorisample' : [0]*3,

            'aprioriline' : [0]*3,

            'samplesigma': [0]*3,

            'linesigma' : [0]*3,

            'measureLog' : [[]]*3

            }) 

"""@pytest.mark.parametrize("image_data, expected_npoints", [({'id':1, 'serial': 'BRUH'}, 1)])

def test_place_points_from_cnet(cnet, image_data, expected_npoints, ncg):

    with ncg.session_scope() as session:

        model.Images.create(session, **image_data)

        ncg.place_points_from_cnet(cnet)

        resp = session.query(model.Points)

        assert len(resp.all()) == expected_npoints

        assert len(resp.all()) == cnet.shape[0]"""

@pytest.mark.xfail

def test_from_filelist(gds_mock, default_configuration, tmp_path, ncg):

    # Written as a list and not parametrized so that the fixture does not automatically clean

    #  up the DB. Needed to test the functionality of the clear_db kwarg.

    for filelist, clear_db in [(['bar1.cub', 'bar2.cub', 'bar3.cub'], False),

                               ([], True),

                               (['bar1.cub', 'bar2.cub', 'bar3.cub'], True)]:

        filelist = [tmp_path/f for f in filelist]

        for file in filelist:

          file.write_text("blah")

        filelist = [f"{f}" for f in filelist]

        # Since we have no overlaps (everything is faked), len(ncg) == 0

        test_ncg = NetworkCandidateGraph.from_filelist(filelist, default_configuration, clear_db=clear_db)

        with test_ncg.session_scope() as session:

            res = session.query(model.Images).all()

            assert len(res) == len(filelist)

def test_global_clear_db(ncg):

    i = model.Images(name='foo', path='/fooland/foo.img')

    with ncg.session_scope() as session:

        session.add(i)

        res = session.query(model.Images).all()

        assert len(res) == 1

    ncg.clear_db()

    with ncg.session_scope() as session:

        res = session.query(model.Images).all()

        assert len(res) == 0

def test_selective_clear_db(ncg):

    i = model.Images(name='foo', path='fooland/foo.img')

    p = model.Points(pointtype=2)

    with ncg.session_scope() as session:

        session.add(i)

        session.add(p)

        res = session.query(model.Images).all()

        assert len(res) == 1

        res =  session.query(model.Points).all()

        assert len(res) == 1

    ncg.clear_db(tables=['Points'])

    with ncg.session_scope() as session:

        res = session.query(model.Images).all()

        assert len(res) == 1

        res = session.query(model.Points).all()

        assert len(res) == 0

def test_cnet_to_db(ncg, cnet):

    # check that the resulting DB DFs have same columns as corresponding Models

    imgs = [model.Images(name='foo1', serial=cnet.iloc[0]['serialnumber']),

            model.Images(name='foo2', serial=cnet.iloc[1]['serialnumber']),

            model.Images(name='foo3', serial=cnet.iloc[2]['serialnumber'])]

    with ncg.session_scope() as session:

        session.add_all(imgs)

    p_df, m_df = ncg.cnet_to_db(cnet)

    point_columns = model.Points.__table__.columns.keys()

    measure_columns = model.Measures.__table__.columns.keys()

    for key in point_columns:

        assert key in p_df.columns, f"column \'{key}\' not in points dataframe"

    for key in measure_columns:

        assert key in m_df.columns, f"column \'{key}\' not in measures dataframe"

# TO DO: test the clear tables functionality on ncg.place_points_from_cnet