Commit cfddf6a2 authored by Laura, Jason R's avatar Laura, Jason R
Browse files

Updates CSM tests / sensor model i/o return types.

parent e075204d

autocnet/camera/sensor_model.py

+35 −22
Original line number Diff line number Diff line
@@ -82,8 +82,14 @@ class BaseSensor: 
            return x_coords, y_coords

        

    def _flatten_results(self, x, results):

        if isinstance(x, (collections.abc.Sequence, np.ndarray)):

        if isinstance(x, collections.abc.Sequence):

            # Maintain the return type, if a sequence is passed,

            # return a sequence.

            if isinstance(results, np.ndarray):

                return results.tolist()

            return results

        elif isinstance(x, np.ndarray):

            return np.asarray(results)

        else:

            return results[0]
@@ -397,13 +403,15 @@ class CSMSensor(BaseSensor): 


    def xyz2sampline(self, x, y, z):

        x_coords, y_coords, z_coords = self._check_arg(x, y, z)

        results = []

        for coord in zip(x_coords, y_coords, z_coords):

        results = np.empty((len(x_coords),2))

        for i, coord in enumerate(zip(x_coords, y_coords, z_coords)):

            imagept = generate_image_coordinate(coord, self.sensor)

            results+=[imagept.samp, imagept.line]

        return self._flatten_results(x_coords, results)

            results[i,0] = imagept.samp

            results[i,1] = imagept.line

        return (self._flatten_results(x, results[:,0]),

                self._flatten_results(x, results[:,1]))



    def lonlat2sampline(self, lon, lat):

    def lonlat2sampline(self, lon, lat, **kwargs):

        """

        Calculate the sample and line for an csm camera sensor
@@ -426,14 +434,15 @@ class CSMSensor(BaseSensor): 
            lint of point

        """

        x_coords, y_coords = self._check_arg(lon, lat)

        results = []

        heights = []

        for coord in zip(x_coords, y_coords):

            # get_height needs lat, lon ordering

            height = self.dem.get_height(coord[1], coord[0])

            x,y,z = og2xyz(lon, lat, height, self.semi_major, self.semi_minor)

            results += [x,y,z]

        results = self._flatten_results(lat, results)

        return self.xyz2sampline(x,y,z)

            heights.append(self.dem.get_height(coord[1], coord[0]))

        x,y,z = og2xyz(x_coords, y_coords, heights, self.semi_major, self.semi_minor)

        

        return self.xyz2sampline(self._flatten_results(lon, x),

                                 self._flatten_results(lon, y),

                                 self._flatten_results(lon, z))

    

    def sampline2xyz(self, sample, line):

        """
@@ -463,24 +472,28 @@ class CSMSensor(BaseSensor): 
        x,y,z : int(s)

            x,y,z coordinates of the point

        """

        sample, line = self._check_arg(sample, line)

        results = []

        csample, cline = self._check_arg(sample, line)

        results = np.empty((len(csample),3))

        # CSMAPI using line/sample ordering. Swap here.

        for coord in zip(line, sample):

        for i, coord in enumerate(zip(cline, csample)):

            # self.dem is an autocnet surface model dem that has a GeoDataset attribute

            bcbf = generate_ground_point(self.dem, coord, self.sensor)

            results += [bcbf.x, bcbf.y, bcbf.z]



        return self._flatten_results(sample, results)

    

    def sampline2lonlat(self, sample, line):

            results[i,0] = bcbf.x

            results[i,1] = bcbf.y

            results[i,2] = bcbf.z

        return (self._flatten_results(sample, results[:,0]),

                self._flatten_results(sample, results[:,1]),

                self._flatten_results(sample, results[:,2]))

    

    def sampline2lonlat(self, sample, line, **kwargs):

        # sampline2xyz handles the CSM iteration, just pass the array through

        x,y,z = self.sampline2xyz(sample, line)

        lon, lat = xyz2og(x, y, z, self.semi_major, self.semi_minor)

        return lon, lat

        lons, lats = xyz2og(x, y, z, self.semi_major, self.semi_minor)

        return lons, lats

    

    def lonlat2xyz(self, lon, lat):

        # All size checking and response type code is handled in self.lonlat2sampline

        sample, line = self.lonlat2sampline(lon, lat)

        print(sample, line)

        return self.sampline2xyz(sample, line)

autocnet/graph/network.py

+4 −23
Original line number Diff line number Diff line
@@ -56,7 +56,6 @@ from autocnet.matcher import subpixel 
from autocnet.matcher import cross_instrument_matcher as cim

from autocnet.vis.graph_view import plot_graph, cluster_plot

from autocnet.control import control

#from autocnet.spatial.isis import point_info

from knoten.surface import GdalDem, EllipsoidDem

from autocnet.transformation.spatial import reproject, og2oc
@@ -106,7 +105,7 @@ class CandidateGraph(nx.Graph): 
        'keypoint_index' : int

    }



    def __init__(self, *args, basepath=None, node_id_map=None, overlaps=False, **kwargs):

    def __init__(self, *args, basepath=None, node_id_map=None, overlaps=False, cam_type='isis', **kwargs):

        super(CandidateGraph, self).__init__(*args, **kwargs)



        self.graph['creationdate'] = strftime("%Y-%m-%d %H:%M:%S", gmtime())
@@ -132,7 +131,7 @@ class CandidateGraph(nx.Graph): 
                node_id = self.graph['node_counter']

                self.graph['node_counter'] += 1

            n['data'] = self.node_factory(

                image_name=i, image_path=image_path, node_id=node_id)

                image_name=i, image_path=image_path, node_id=node_id, cam_type=cam_type)



            self.graph['node_name_map'][i] = node_id
@@ -1597,12 +1596,6 @@ class NetworkCandidateGraph(CandidateGraph): 
        if self.async_watchers == True:

            self._setup_asynchronous_workers()



        # Setup the DEM

        # I dislike having the DEM on the NCG, but in the short term it

        # is the best solution I think. I don't want to pass the DEM around

        # for the sensor calls.

        self._setup_dem()



    @contextmanager

    def session_scope(self):

     """
@@ -1618,17 +1611,6 @@ class NetworkCandidateGraph(CandidateGraph): 
     finally:

         session.close()



    def _setup_dem(self):

        spatial = self.config['spatial']

        semi_major = spatial.get('semimajor_rad')

        semi_minor = spatial.get('semiminor_rad')

        dem_type = spatial.get('dem_type')

        dem = spatial.get('dem', False)

        if dem:

            self.dem = GdalDem(dem, semi_major, semi_minor, dem_type)

        else:

            self.dem = EllipsoidDem(semi_major, semi_minor)



    @property

    def Session(self):

        return self._Session
@@ -1638,7 +1620,6 @@ class NetworkCandidateGraph(CandidateGraph): 
        self._Session = Session



    def _setup_database(self):

        db = self.config['database']

        # A non-linear timeout if the DB is spinning up or loaded with many connections.

        sleeptime = 2

        retries = 0
@@ -2480,7 +2461,7 @@ class NetworkCandidateGraph(CandidateGraph): 
        if overlaps:

            self._execute_sql(sql.compute_overlaps_sql)



    def from_database(self, query_string=sql.select_pub_image):

    def from_database(self, query_string=sql.select_pub_image, cam_type='isis'):

        """

        This is a constructor that takes the results from an arbitrary query string,

        uses those as a subquery into a standard polygon overlap query and
@@ -2528,7 +2509,7 @@ class NetworkCandidateGraph(CandidateGraph): 
                    adjacency[spath].append(dpath)



        # Add nodes that do not overlap any images

        self.__init__(adjacency, node_id_map=adjacency_lookup)

        self.__init__(adjacency, node_id_map=adjacency_lookup, cam_type=cam_type)



        # Setup the edges

        self._setup_edges()

autocnet/graph/node.py

+18 −13
Original line number Diff line number Diff line
@@ -65,23 +65,22 @@ class Node(dict, MutableMapping): 
                  ISIS compatible serial number

    """



    def __init__(self, image_name=None, image_path=None, node_id=None):

    def __init__(self, 

                 image_name=None, 

                 image_path=None, 

                 node_id=None, 

                 cam_type='isis', 

                 dem=None,

                 dem_type=None):

        self['image_name'] = image_name

        self['image_path'] = image_path

        self['node_id'] = node_id

        self['hash'] = image_name

        self['cam_type'] = cam_type

        self['dem'] = dem

        self['dem_type'] = 'radius' if dem_type is None else dem_type 

        self.masks = pd.DataFrame()



    @property

    def camera(self):

        if not hasattr(self, '_camera'):

            self._camera = None

        return self._camera



    @camera.setter

    def camera(self, camera):

        self._camera = camera



    @property

    def descriptors(self):

        if not hasattr(self, '_descriptors'):
@@ -120,8 +119,11 @@ class Node(dict, MutableMapping): 
        Number Keypoints: {}

        Available Masks : {}

        Type: {}

        Sensor Model Type: {}

        DEM: {}

        """.format(self['node_id'], self['image_name'], self['image_path'],

                   self.nkeypoints, self.masks, self.__class__)

                   self.nkeypoints, self.masks, self.__class__,

                   self['cam_type'], self['dem'])



    def __hash__(self): #pragma: no cover

        return hash(self['node_id'])
@@ -166,7 +168,10 @@ class Node(dict, MutableMapping): 
    @property

    def geodata(self):

        if not hasattr(self, '_geodata'):

            self._geodata = AGeoDataset(self['image_path'])

            self._geodata = AGeoDataset(self['image_path'], 

                                        sensortype = self['cam_type'],

                                        dem=self['dem'],

                                        dem_type=self['dem_type'])

        return self._geodata



    @property

autocnet/graph/tests/test_node.py

+0 −3
Original line number Diff line number Diff line
@@ -33,9 +33,6 @@ class TestNode(object): 
        img = get_path('AS15-M-0297_crop.cub')

        return Node(image_name='AS15-M-0297_crop.cub', image_path=img)

    

    def test_get_camera(self, node):

        assert node.camera == None

    

    def test_create(self):

        assert isinstance(Node.create(None, 1), Node)

        n = Node.create('foo', 1, basepath='/')

autocnet/io/db/model.py

+2 −0
Original line number Diff line number Diff line
@@ -311,6 +311,8 @@ class Images(BaseMixin, Base): 
    _geom = Column("geom", Geometry('MultiPolygon', srid=latitudinal_srid, dimension=2, spatial_index=True))

    footprint_bodyfixed = Column(Geometry('MULTIPOLYGON', dimension=2))

    cam_type = Column(String)

    dem = Column(String)

    dem_type = Column(String)

    #footprint_bodyfixed = Column(Geometry('POLYGON',dimension=3))



    # Relationships