Commit 2c4576b9 authored by Laura, Jason R's avatar Laura, Jason R
Browse files

Updates tests

parent cfddf6a2

autocnet/matcher/subpixel.py

+1 −4
Original line number Diff line number Diff line
@@ -882,7 +882,6 @@ def subpixel_register_point_smart(point, 
    # match to the source node.

    source = measures[reference_index]

    reference_index_id = source.imageid

    

    log.info(f'Using measure {source.id} on image {source.imageid}/{source.serial} as the reference.')

    log.info(f'Measure reference index is: {reference_index}')
@@ -1362,9 +1361,7 @@ def smart_register_point(point, 
    if not isinstance(point, Points):

        point = session.query(Points).filter(Points.id == point).one()



    print('Initial')

    measure_results = subpixel_register_point_smart(point, session, parameters=parameters, **shared_kwargs)

    print('Decider')

    measures_to_update, measures_to_set_false = decider(measure_results)

    log.info(f'Found {len(measures_to_update)} measures that found subpixel registration consensus. Running validation now...')

    # Validate that the new position has consensus

autocnet/transformation/affine.py

+1 −5
Original line number Diff line number Diff line
@@ -67,9 +67,7 @@ def estimate_affine_from_sensors(reference_image, 
    y_coords = [base_starty, base_stopy, base_stopy, base_starty, bcenter_y]

    # Dispatch to the sensor to get the a priori pixel location in the input image

    lons, lats = reference_image.sensormodel.sampline2lonlat(x_coords, y_coords, allowoutside=True)

    print(lons, lats)

    xs, ys = moving_image.sensormodel.lonlat2sampline(lons, lats, allowoutside=True)

    print(xs, ys)

    log.debug(f'Lon/Lats for affine estimate are: {list(zip(lons, lats))}')

    log.debug(f'Image X / Image Y for affine estimate are: {list(zip(xs, ys))}')
@@ -82,7 +80,7 @@ def estimate_affine_from_sensors(reference_image, 
            base_gcps.append((base_x, base_y))

            

    if len(dst_gcps) < 3:

        raise ValueError(f'Unable to find enough points to compute an affine transformation. Found {len(dst_corners)} points, but need at least 3.')

        raise ValueError(f'Unable to find enough points to compute an affine transformation. Found {len(dst_gcps)} points, but need at least 3.')



    log.debug(f'Number of GCPs for affine estimation: {len(dst_gcps)}')
@@ -117,8 +115,6 @@ def estimate_local_affine(reference_roi, moving_roi): 
    size_x = 60 # reference_roi.size_x + roi_buffer

    size_y = 60 # reference_roi.size_y + roi_buffer

    

    print('REF: ', reference_roi.x, reference_roi.y)



    affine_transform = estimate_affine_from_sensors(reference_roi.data, 

                                                    moving_roi.data, 

                                                    reference_roi.x,

autocnet/transformation/roi.py

+1 −0
Original line number Diff line number Diff line
@@ -273,6 +273,7 @@ class Roi(): 
        # series of checks to make sure all pixels inside image limits

        raster_xsize, raster_ysize = self.data.raster_size

        if min_x < 0 or min_y < 0 or min_x+x_read_length > raster_xsize or min_y+y_read_length > raster_ysize:

            print('FAILURE: ', self.data.file_name, min_x, min_y, x_read_length, y_read_length)

            raise IndexError('Image coordinates plus read buffer are outside of the available data. Please select a smaller ROI and/or a smaller read buffer.')



        pixels = [min_x, min_y, x_read_length, y_read_length]

tests/test_ctx_csm_3image_subpixel.py→tests/test_ctx_csm_3image_subpixel2.py

+47 −44
Original line number Diff line number Diff line
@@ -19,53 +19,55 @@ def isis_mola_radius_dem(): 
    return path



@pytest.fixture

def g17(isis_mola_radius_dem):

def b10(isis_mola_radius_dem):

    # Start is sample:2000 line:5700

    return {'id':0,

            'name':'G17_024823_2204_XI_40N109W.crop.cub',

            'path':get_path('G17_024823_2204_XI_40N109W.crop.cub'),

            'serial':'MRO/CTX/1005587208:239',

            'name':'B10_013615_2178_XI_37N117W.crop.cub',

            'path':get_path('B10_013615_2178_XI_37N117W.crop.cub'),

            'serial':'MRO/CTX/0930130710:231',

            'cam_type':'csm',

            'dem':isis_mola_radius_dem,

            'dem_type':'radius'}



@pytest.fixture

def n11(isis_mola_radius_dem):

def n12(isis_mola_radius_dem):

    return {'id':1,

            'name':'N11_066770_2192_XN_39N109W.crop.cub',

            'path':get_path('N11_066770_2192_XN_39N109W.crop.cub'),

            'serial':'MRO/CTX/1287982533:042',

            'name':'N12_067021_2177_XN_37N117W.crop.cub',

            'path':get_path('N12_067021_2177_XN_37N117W.crop.cub'),

            'serial':'MRO/CTX/1289671564:206',

            'cam_type':'csm',

            'dem':isis_mola_radius_dem,

            'dem_type':'radius'}



@pytest.fixture

def p10(isis_mola_radius_dem):

def k12(isis_mola_radius_dem):

    # Start is sample:1600 line:4950

    return {'id':2,

            'name':'P10_005031_2197_XI_39N109W.crop.cub',

            'path':get_path('P10_005031_2197_XI_39N109W.crop.cub'),

            'serial':'MRO/CTX/0872335765:217',

            'name':'K12_058001_2177_XI_37N117W.crop.cub',

            'path':get_path('K12_058001_2177_XI_37N117W.crop.cub'),

            'serial':'MRO/CTX/1228947495:234',

            'cam_type':'csm',

            'dem':isis_mola_radius_dem,

            'dem_type':'radius'}



@pytest.fixture

def g17_image(g17):

    return Images(**g17)

def n12_image(n12):

    return Images(**n12)



@pytest.fixture

def n11_image(n11):

    return Images(**n11)

def b10_image(b10):

    return Images(**b10)



@pytest.fixture

def p10_image(p10):

    return Images(**p10)

def k12_image(k12):

    return Images(**k12)



@pytest.fixture

def measure_0():

    data = [

        {'id':0, 'imageid':0,'apriorisample':384.768,'aprioriline':278.000,'sample':384.768,'line':278.000,'pointid':0, 'measuretype':3},

        {'id':1, 'imageid':1,'apriorisample':521.905,'aprioriline':209.568,'sample':521.905,'line':209.568, 'pointid':0, 'measuretype':3},

        {'id':2, 'imageid':2,'apriorisample':355.483,'aprioriline':234.296,'sample':355.483,'line':234.296, 'pointid':0, 'measuretype':3}

        {'id':0, 'imageid':0,'apriorisample':442.7200012207031,'aprioriline':218.4800033569336,'sample':442.7200012207031,'line':218.4800033569336,'pointid':0, 'measuretype':3},

        {'id':1, 'imageid':1,'apriorisample':755.95042324367,'aprioriline':1207.3857527191,'sample':755.95042324367,'line':1207.3857527191, 'pointid':0, 'measuretype':3},

        {'id':2, 'imageid':2,'apriorisample':830.95897898574,'aprioriline':1549.7867781121,'sample':830.95897898574,'line':1549.7867781121, 'pointid':0, 'measuretype':3}

        ]

    return [Measures(**d) for d in data]
@@ -82,7 +84,7 @@ def points(measure_0): 
    return pts



@pytest.fixture

def session(measure_0,g17_image,n11_image,p10_image):

def session(measure_0,n12_image,b10_image,k12_image):



    # Mocked DB session with calls and responses.

    session = UnifiedAlchemyMagicMock(data=[
@@ -104,23 +106,23 @@ def session(measure_0,g17_image,n11_image,p10_image): 
        ),(

            [mock.call.query(Images),

                mock.call.filter(Images.id == 0)],

                [g17_image]

                [b10_image]

        ),(

            [mock.call.query(Images),

                mock.call.filter(Images.id == 1)],

                [n11_image]

                [n12_image]

        ),(

            [mock.call.query(Images),

                mock.call.filter(Images.id == 2)],

                [p10_image]

                [k12_image]

        ),

        ])

    return session

    

def test_ctx_pair_to_df(session,

                        g17_image,

                        n11_image,

                        p10_image,

                        n12_image,

                        b10_image,

                        k12_image,

                        measure_0,

                        points):

    """
@@ -159,29 +161,30 @@ def test_ctx_pair_to_df(session, 
                                                                         session,

                                                                         parameters=parameters,

                                                                         shared_kwargs=shared_kwargs)



        print(measures_to_update)

        print(measures_to_set_false)

        assert measures_to_set_false == []



        m0 = measures_to_update[0]

        assert m0['sample'] == 528.0616518160688

        assert m0['line'] == 210.8722056871887

        assert m0['template_metric'] == 0.8538808822631836

        assert m0['ignore'] == False

        assert m0['template_shift'] == 445.17368002294427

        # assert m0['sample'] == 528.0616518160688

        # assert m0['line'] == 210.8722056871887

        # assert m0['template_metric'] == 0.8538808822631836

        # assert m0['ignore'] == False

        # assert m0['template_shift'] == 445.17368002294427

        

        m1 = measures_to_update[1]

        assert m1['sample'] == 357.3392609551714

        assert m1['line'] == 230.29507805238129

        assert m1['template_metric'] == 0.6922665238380432

        assert m1['ignore'] == False

        assert m1['template_shift'] == 175.5325037366171

        # assert m1['sample'] == 357.3392609551714

        # assert m1['line'] == 230.29507805238129

        # assert m1['template_metric'] == 0.6922665238380432

        # assert m1['ignore'] == False

        # assert m1['template_shift'] == 175.5325037366171



        dfs = []

        with mock.patch('pandas.read_sql') as db_response:

            db_cnet = pd.DataFrame([

                [0, 0, g17_image.serial,measure_0[0].sample, measure_0[0].line, point.pointtype, measure_0[0].measuretype, 'test'],

                [1, 0, n11_image.serial,m0['sample'], m0['line'], point.pointtype, measure_0[1].measuretype, 'test'],

                [1, 0, p10_image.serial,m1['sample'], m1['line'], point.pointtype, measure_0[2].measuretype, 'test'],

                [0, 0, b10_image.serial,measure_0[0].sample, measure_0[0].line, point.pointtype, measure_0[0].measuretype, 'test'],

                [1, 0, n12_image.serial,m0['sample'], m0['line'], point.pointtype, measure_0[1].measuretype, 'test'],

                [1, 0, k12_image.serial,m1['sample'], m1['line'], point.pointtype, measure_0[2].measuretype, 'test'],

                                    ],

                                columns=['id','pointid', 'serialnumber', 'sample', 'line', 

                                            'pointtype', 'measuretype','identifier'])
@@ -194,6 +197,6 @@ def test_ctx_pair_to_df(session, 
    df.rename(columns={'pointtype':'pointType',

                        'measuretype':'measureType'},

                        inplace=True)

    to_isis(df, 'tests/artifacts/ctx_csm_trio_to_df.cnet', targetname='Mars')

    write_filelist([g17_image.path, n11_image.path, p10_image.path], 'tests/artifacts/ctx_csm_trio_to_df.lis')

    to_isis(df, 'tests/artifacts/ctx_csm_trio_to_df2.cnet', targetname='Mars')

    write_filelist([n12_image.path, b10_image.path, k12_image.path], 'tests/artifacts/ctx_csm_trio_to_df2.lis')

    assert False
 
 No newline at end of file

tests/test_ctx_isis_3image_subpixel2.py

0 → 100644
+193 −0
Original line number Diff line number Diff line 
import os

import pandas as pd

import pytest

import mock

from mock_alchemy.mocking import UnifiedAlchemyMagicMock



from plio.io.io_controlnetwork import to_isis, write_filelist



from autocnet.matcher.subpixel import smart_register_point

from autocnet.io.db.model import Points, Measures, Images

from autocnet.io.db.controlnetwork import db_to_df

from autocnet.examples import get_path



@pytest.fixture

def b10():

    # Start is sample:2000 line:5700

    return {'id':0,

            'name':'B10_013615_2178_XI_37N117W.crop.cub',

            'path':get_path('B10_013615_2178_XI_37N117W.crop.cub'),

            'serial':'MRO/CTX/0930130710:231',

            'cam_type':'isis'}



@pytest.fixture

def n12():

    return {'id':1,

            'name':'N12_067021_2177_XN_37N117W.crop.cub',

            'path':get_path('N12_067021_2177_XN_37N117W.crop.cub'),

            'serial':'MRO/CTX/1289671564:206',

            'cam_type':'isis'}



@pytest.fixture

def k12():

    return {'id':2,

            'name':'K12_058001_2177_XI_37N117W.crop.cub',

            'path':get_path('K12_058001_2177_XI_37N117W.crop.cub'),

            'serial':'MRO/CTX/1228947495:234',

            'cam_type':'isis'}



@pytest.fixture

def n12_image(n12):

    return Images(**n12)



@pytest.fixture

def b10_image(b10):

    return Images(**b10)



@pytest.fixture

def k12_image(k12):

    return Images(**k12)



@pytest.fixture

def measure_0():

    data = [

        {'id':0, 'imageid':0,'apriorisample':442.7200012207031,'aprioriline':218.4800033569336,'sample':442.7200012207031,'line':218.4800033569336,'pointid':0, 'measuretype':3},

        {'id':1, 'imageid':1,'apriorisample':755.95042324367,'aprioriline':1207.3857527191,'sample':755.95042324367,'line':1207.3857527191, 'pointid':0, 'measuretype':3},

        {'id':2, 'imageid':2,'apriorisample':830.95897898574,'aprioriline':1549.7867781121,'sample':830.95897898574,'line':1549.7867781121, 'pointid':0, 'measuretype':3}

        ]

    return [Measures(**d) for d in data]



@pytest.fixture

def points(measure_0):

    data = [{'id':0,'reference_index':0,'pointtype':2,'measures':[],'_apriori':''},

             #{'id':1,'reference_index':1,'pointtype':2,'measures':[],'_apriori':''},

             #{'id':2,'reference_index':1,'pointtype':2,'measures':[],'_apriori':''},

             #{'id':3,'reference_index':1,'pointtype':2,'measures':[],'_apriori':''},

             #{'id':4,'reference_index':1,'pointtype':2,'measures':[],'_apriori':''}

      ]

    pts = [Points(**d) for d in data]

    pts[0].measures = measure_0

    return pts



@pytest.fixture

def session(measure_0,n12_image,b10_image,k12_image):



    # Mocked DB session with calls and responses.

    session = UnifiedAlchemyMagicMock(data=[

        (

            [mock.call.query(Measures),

                mock.call.filter(Measures.pointid == 0),

                mock.call.order_by(Measures.id)],

                measure_0

        ),(

            [mock.call.query(Measures),

             mock.call.filter(Measures.id == 0),

             mock.call.order_by(Measures.id)],

             [measure_0[0]]

        ),(

            [mock.call.query(Measures),

             mock.call.filter(Measures.id == 1),

             mock.call.order_by(Measures.id)],

             [measure_0[1]]

        ),(

            [mock.call.query(Measures),

             mock.call.filter(Measures.id == 2),

             mock.call.order_by(Measures.id)],

             [measure_0[2]]

        ),(

            [mock.call.query(Images),

                mock.call.filter(Images.id == 0)],

                [b10_image]

        ),(

            [mock.call.query(Images),

                mock.call.filter(Images.id == 1)],

                [n12_image]

        ),(

            [mock.call.query(Images),

                mock.call.filter(Images.id == 2)],

                [k12_image]

        ),

        ])

    return session

    

def test_ctx_pair_to_df(session,

                        n12_image,

                        b10_image,

                        k12_image,

                        measure_0,

                        points):

    """

    This is an integration test that takes a pair of ISIS cube files and

    processes them through the smart_subpixel_matcher. This is the same

    matcher that was used by the CTX control project. The test sets up

    a session mock with the appropriate data. This directly of indirectly

    tests the following:



    - subpixel.smart_register_point

    - subpixel.subpixel_register_point_smart

    - subpixel.decider

    - subpixel.check_for_shift_consensus

    - subpixel.validate_candidate_measure

    - transformation.roi.Roi

    - transformation.affine.estimate_affine_transform

    """

    # Pulled directly from CTX control project.

    parameters = [

        {'match_kwargs': {'image_size':(60,60), 'template_size':(30,30)}},

        {'match_kwargs': {'image_size':(75,75), 'template_size':(33,33)}},

        {'match_kwargs': {'image_size':(90,90), 'template_size':(36,36)}},

        {'match_kwargs': {'image_size':(110,110), 'template_size':(40,40)}},

        {'match_kwargs': {'image_size':(125,125), 'template_size':(44,44)}},

        {'match_kwargs': {'image_size':(140,140), 'template_size':(48,48)}}

    ]



    shared_kwargs = {'cost_func':lambda x,y:y,

                     'chooser':'smart_subpixel_registration'}

    for point in points:



        # Somewhere in subpixel, need to add the offsets back to samp/line based

        # on which image is being used. Every samp/line, patch time.



        measures_to_update, measures_to_set_false = smart_register_point(point, 

                                                                         session,

                                                                         parameters=parameters,

                                                                         shared_kwargs=shared_kwargs)

        print(measures_to_update)

        print(measures_to_set_false)

        assert measures_to_set_false == []



        m0 = measures_to_update[0]

        # assert m0['sample'] == 528.0616518160688

        # assert m0['line'] == 210.8722056871887

        # assert m0['template_metric'] == 0.8538808822631836

        # assert m0['ignore'] == False

        # assert m0['template_shift'] == 445.17368002294427

        

        m1 = measures_to_update[1]

        # assert m1['sample'] == 357.3392609551714

        # assert m1['line'] == 230.29507805238129

        # assert m1['template_metric'] == 0.6922665238380432

        # assert m1['ignore'] == False

        # assert m1['template_shift'] == 175.5325037366171



        dfs = []

        with mock.patch('pandas.read_sql') as db_response:

            db_cnet = pd.DataFrame([

                [0, 0, b10_image.serial,measure_0[0].sample, measure_0[0].line, point.pointtype, measure_0[0].measuretype, 'test'],

                [1, 0, n12_image.serial,m0['sample'], m0['line'], point.pointtype, measure_0[1].measuretype, 'test'],

                [1, 0, k12_image.serial,m1['sample'], m1['line'], point.pointtype, measure_0[2].measuretype, 'test'],

                                    ],

                                columns=['id','pointid', 'serialnumber', 'sample', 'line', 

                                            'pointtype', 'measuretype','identifier'])

            db_response.return_value = db_cnet



            df = db_to_df(session)

            dfs.append(df)

    

    df = pd.concat(dfs)

    df.rename(columns={'pointtype':'pointType',

                        'measuretype':'measureType'},

                        inplace=True)

    to_isis(df, 'tests/artifacts/ctx_isis_trio_to_df2.cnet', targetname='Mars')

    write_filelist([n12_image.path, b10_image.path, k12_image.path], 'tests/artifacts/ctx_isis_trio_to_df2.lis')

    assert False
 
 No newline at end of file