Exemple #1
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    def testing(self):
        attributes = {"mo": array(["money", "soup"]), "SITE_CLASS": array(["E", "C"])}
        latitude = [10, 20]
        longitude = [1, 2]
        sites = Sites(latitude, longitude, **attributes)
        site_class2Vs30 = {"C": 30, "E": 40}
        sites.set_Vs30(site_class2Vs30)

        actual = array(latitude)
        self.assert_(allclose(sites.latitude, actual, 0.001))
        actual = array(longitude)
        self.assert_(allclose(sites.longitude, actual, 0.001))
        actual = array(["money", "soup"])
        for (att, act) in map(None, sites.attributes["mo"], actual):
            self.assert_(att == act)
        actual = array([40, 30])
        self.assert_(allclose(sites.attributes["Vs30"], actual, 0.001))

        site_class2Vs30 = {"C": 30}
        try:
            sites.set_Vs30(site_class2Vs30)
        except KeyError:
            pass
        else:
            self.failUnless(False, "KeyError not raised")
Exemple #2
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    def __init__(self, latitude, longitude, **attributes):
        """Contruct a Bridges object.

        latitude    a vector (tuple, list, ...) of latitude values
        longitude   a vector (tuple, list, ...) of longitude values
        attributes  a dictionary of bridge attributes
        """

        Sites.__init__(self, latitude, longitude, **attributes)
    def __init__(self, latitude, longitude, vulnerability_set, **attributes):
        """Create an object holding all Structures data for user defined
        vulnerability curves
        """

        # inherit setup from Sites, add building parameters
        Sites.__init__(self, latitude, longitude, **attributes)
        self.vulnerability_set = vulnerability_set

        # Validate that the curves match this set
        self.validate_vulnerability_set()
    def __init__(self, latitude, longitude, building_parameters, **attributes):
        """Create an object holding all Structures data.

        Inherits from Sites which handles lat, lon and attributes.  Structures
        adds the 'building_parameters' attribute which must be handled
        specially.  Compare this with the handling of 'extra' classification
        data in the Bridges class.

        TODO: make extra data here be handled in a similar way as in Bridges?
        """

        # inherit setup from Sites, add building parameters
        Sites.__init__(self, latitude, longitude, **attributes)
        self.building_parameters = building_parameters
Exemple #5
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    def test_closest_site(self):
        # Test data from GA website
        # http://www.ga.gov.au/earth-monitoring/geodesy/geodetic-techniques/distance-calculation-algorithms.html
        latitude = [-31, -31, -32, -33, -34, -35, -40, -50, -60, -70, -80]
        longitude = [150, 151, 151, 151, 151, 151, 151, 151, 151, 151, 151]
        sites = Sites(latitude, longitude)

        # Point A from website
        point_lat = -30
        point_lon = 150

        closest_site = sites.closest_site(point_lat, point_lon)

        assert sites.latitude[closest_site] == latitude[0]
        assert sites.longitude[closest_site] == longitude[0]
    def __init__(self,
                 latitude,
                 longitude,
                 vulnerability_set,
                 **attributes):
        """Create an object holding all Structures data for user defined
        vulnerability curves
        """

        # inherit setup from Sites, add building parameters
        Sites.__init__(self, latitude, longitude, **attributes)
        self.vulnerability_set = vulnerability_set

        # Validate that the curves match this set
        self.validate_vulnerability_set()
Exemple #7
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 def test_closest_site(self):
     # Test data from GA website 
     # http://www.ga.gov.au/earth-monitoring/geodesy/geodetic-techniques/distance-calculation-algorithms.html
     latitude  = [-31,-31,-32,-33,-34,-35,-40,-50,-60,-70,-80]
     longitude = [150,151,151,151,151,151,151,151,151,151,151]
     sites = Sites(latitude, longitude)
     
     # Point A from website
     point_lat = -30
     point_lon = 150
     
     closest_site = sites.closest_site(point_lat, point_lon)
     
     assert sites.latitude[closest_site] == latitude[0]
     assert sites.longitude[closest_site] == longitude[0]
Exemple #8
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def create_site():
    """
    Create dummy site.
    Uses the same technique from test_sites
    (Test_Sites.test_read_from_file
    """
    # create dummy CSV file - this is bridges data, but sites should handle anything
    lat = [-35.352085]
    lon = [149.236994]
    clsf = ['HWB17']
    cat = ['BRIDGE']
    skew = [0]
    span = [2]
    cls = ['E']
    attribute_keys = ['BID', 'STRUCTURE_CLASSIFICATION']

    dummy_csv_data = ['BID,LONGITUDE,LATITUDE,STRUCTURE_CLASSIFICATION,'
                      'STRUCTURE_CATEGORY,SKEW,SPAN,SITE_CLASS',
                      '2,%.6f,%.6f,%s,%s,%s,%s,%s'
                          % (lon[0], lat[0], clsf[0], cat[0], skew[0], span[0], cls[0])]

    (handle, filename) = tempfile.mkstemp('.csv', 'test_sites_')
    os.close(handle)

    f = open(filename, 'wb')
    f.write('\n'.join(dummy_csv_data))
    f.close()

    # now read file - pass attribute_conversion as **kwargs data
    sites = Sites.from_csv(filename, BID=int, STRUCTURE_CLASSIFICATION=str)
    
    return sites, filename
Exemple #9
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def create_site():
    """
    Create dummy site.
    Uses the same technique from test_sites
    (Test_Sites.test_read_from_file
    """
    # create dummy CSV file - this is bridges data, but sites should handle anything
    lat = [-35.352085]
    lon = [149.236994]
    clsf = ['HWB17']
    cat = ['BRIDGE']
    skew = [0]
    span = [2]
    cls = ['E']
    attribute_keys = ['BID', 'STRUCTURE_CLASSIFICATION']

    dummy_csv_data = [
        'BID,LONGITUDE,LATITUDE,STRUCTURE_CLASSIFICATION,'
        'STRUCTURE_CATEGORY,SKEW,SPAN,SITE_CLASS',
        '2,%.6f,%.6f,%s,%s,%s,%s,%s' %
        (lon[0], lat[0], clsf[0], cat[0], skew[0], span[0], cls[0])
    ]

    (handle, filename) = tempfile.mkstemp('.csv', 'test_sites_')
    os.close(handle)

    f = open(filename, 'wb')
    f.write('\n'.join(dummy_csv_data))
    f.close()

    # now read file - pass attribute_conversion as **kwargs data
    sites = Sites.from_csv(filename, BID=int, STRUCTURE_CLASSIFICATION=str)

    return sites, filename
Exemple #10
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    def __init__(self,
                 latitude,
                 longitude,
                 building_parameters,
                 **attributes):
        """Create an object holding all Structures data.

        Inherits from Sites which handles lat, lon and attributes.  Structures
        adds the 'building_parameters' attribute which must be handled
        specially.  Compare this with the handling of 'extra' classification
        data in the Bridges class.

        TODO: make extra data here be handled in a similar way as in Bridges?
        """

        # inherit setup from Sites, add building parameters
        Sites.__init__(self, latitude, longitude, **attributes)
        self.building_parameters = building_parameters
Exemple #11
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    def test_read_from_file_Vs30(self):
        """Test reading Sites data from file taking into account Vs30 data.
        1. If VS30 is present and requested, it should be an attribute
        2. If VS30 is not present and requested, it should not be an attribute
        """

        raw_csv_no_vs30 = """BID,LATITUDE,LONGITUDE
2,-6.4125,110.837502
3,-6.4125,110.845833 
4,-6.4125,110.854164"""

        raw_csv_vs30 = """BID,LATITUDE,LONGITUDE,VS30
2,-6.4125,110.837502,666
3,-6.4125,110.845833,560
4,-6.4125,110.854164,560"""

        (handle, filename_vs30) = tempfile.mkstemp(".csv", "test_sites_")
        os.close(handle)
        f = open(filename_vs30, "wb")
        f.write(raw_csv_vs30)
        f.close()

        (handle, filename_no_vs30) = tempfile.mkstemp(".csv", "test_sites_")
        os.close(handle)
        f = open(filename_no_vs30, "wb")
        f.write(raw_csv_no_vs30)
        f.close()

        expected_vs30 = [666, 560, 560]

        # Test 1.
        sites = Sites.from_csv(filename_vs30, VS30=float)
        self.failUnless("Vs30" in sites.attributes)
        self.failUnless(np.all(sites.attributes["Vs30"] == expected_vs30))

        # Test 2.
        sites = Sites.from_csv(filename_no_vs30, VS30=float)
        self.failUnless("Vs30" not in sites.attributes)

        # get rid of test data files
        os.remove(filename_vs30)
        os.remove(filename_no_vs30)
Exemple #12
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    def test_read_from_file_Vs30(self):
        """Test reading Sites data from file taking into account Vs30 data.
        1. If VS30 is present and requested, it should be an attribute
        2. If VS30 is not present and requested, it should not be an attribute
        """

        raw_csv_no_vs30 = """BID,LATITUDE,LONGITUDE
2,-6.4125,110.837502
3,-6.4125,110.845833 
4,-6.4125,110.854164"""

        raw_csv_vs30 = """BID,LATITUDE,LONGITUDE,VS30
2,-6.4125,110.837502,666
3,-6.4125,110.845833,560
4,-6.4125,110.854164,560"""

        (handle, filename_vs30) = tempfile.mkstemp('.csv', 'test_sites_')
        os.close(handle)
        f = open(filename_vs30, 'wb')
        f.write(raw_csv_vs30)
        f.close()
        
        (handle, filename_no_vs30) = tempfile.mkstemp('.csv', 'test_sites_')
        os.close(handle)
        f = open(filename_no_vs30, 'wb')
        f.write(raw_csv_no_vs30)
        f.close()
        
        expected_vs30 = [666,560,560]
        
        # Test 1.
        sites = Sites.from_csv(filename_vs30, VS30=float)
        self.failUnless('Vs30' in sites.attributes)
        self.failUnless(np.all(sites.attributes['Vs30'] == expected_vs30))
        
        # Test 2.
        sites = Sites.from_csv(filename_no_vs30, VS30=float)
        self.failUnless('Vs30' not in sites.attributes)

        # get rid of test data files
        os.remove(filename_vs30)
        os.remove(filename_no_vs30)
Exemple #13
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    def testing(self):
        attributes = {'mo': array(['money', 'soup']),
                      'SITE_CLASS': array(['E', 'C'])}
        latitude = [10, 20]
        longitude = [1, 2]
        sites = Sites(latitude, longitude, **attributes)
        site_class2Vs30 = {'C': 30, 'E': 40}
        sites.set_Vs30(site_class2Vs30)

        actual = array(latitude)
        self.assert_(allclose(sites.latitude, actual, 0.001))
        actual = array(longitude)
        self.assert_(allclose(sites.longitude, actual, 0.001))
        actual = array(['money', 'soup'])
        for (att, act) in map(None, sites.attributes['mo'], actual):
            self.assert_(att == act)
        actual = array([40, 30])
        self.assert_(allclose(sites.attributes['Vs30'], actual, 0.001))

        site_class2Vs30 = {'C': 30}
        try:
            sites.set_Vs30(site_class2Vs30)
        except KeyError:
            pass
        else:
            self.failUnless(False, "KeyError not raised")
Exemple #14
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    def testing_truncate_sites_for_test(self):
        attributes = {'mo': array(['money', 'soup']),
                      'SITE_CLASS': array(['E', 'C']),
                      'id': array([1, 2])}
        latitude = [10, 20]
        longitude = [1, 2]
        sites = Sites(latitude, longitude, **attributes)
        use_site_indexes = False
        site_indexes = array([2])
        new_sites = truncate_sites_for_test(use_site_indexes, sites,
                                            site_indexes)
        self.failUnless(allclose(array([1, 2]), new_sites.attributes['id']))

        use_site_indexes = True
        site_indexes = array([2])
        new_sites = truncate_sites_for_test(use_site_indexes,sites,
                                            site_indexes)
        self.failUnlessEqual(site_indexes, new_sites.attributes['id'])
Exemple #15
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    def create_analysis_objects(self):
        # Parameters
        rupture_centroid_lat = asarray([-30])
        rupture_centroid_lon = asarray([150])
        length = asarray([1.0])
        azimuth = asarray([2.0])
        width = asarray([3.0])
        dip = asarray([4.0])
        depth = asarray([5.0])
        Mw = asarray([6.0])
        atten_models = asarray([
            'Allen', 'Toro_1997_midcontinent', 'Sadigh_97',
            'Youngs_97_interface', 'Youngs_97_intraslab'
        ])
        atten_model_weights = asarray([0.2, 0.2, 0.2, 0.2, 0.2])
        atten_periods = asarray([0, 1.0, 2.0])
        sites_lat = asarray([-31])
        sites_lon = asarray([150])

        # Event Set
        event_set = Event_Set.create(rupture_centroid_lat=rupture_centroid_lat,
                                     rupture_centroid_lon=rupture_centroid_lon,
                                     azimuth=azimuth,
                                     dip=dip,
                                     Mw=Mw,
                                     depth=depth,
                                     area=length * width,
                                     width=width,
                                     length=length)

        # Event Activity
        event_activity = Event_Activity(len(event_set))
        event_activity.set_scenario_event_activity()

        # Source Model
        source_model = Source_Model.create_scenario_source_model(
            len(event_set))
        source_model.set_attenuation(atten_models, atten_model_weights)
        source_model.set_ground_motion_calcs(atten_periods)
        event_set.scenario_setup()
        event_activity.ground_motion_model_logic_split(source_model, True)

        # Sites
        sites = Sites(sites_lat, sites_lon)

        # SA
        # Set up synthetic SA figures
        # Dimensions -  spawn, gmm, rm, sites, events, period
        motion = zeros((1, len(atten_models), 1, len(sites), len(event_set),
                        len(atten_periods)),
                       dtype=float)
        # Allen
        motion[:, 0, :, :, :, 0] = 0  # period 0
        motion[:, 0, :, :, :, 1] = 1  # period 1.0
        motion[:, 0, :, :, :, 2] = 2  # period 2.0
        # Toro_1997_midcontinent
        motion[:, 1, :, :, :, 0] = 3  # period 0
        motion[:, 1, :, :, :, 1] = 4  # period 1.0
        motion[:, 1, :, :, :, 2] = 5  # period 2.0
        # Sadigh_97
        motion[:, 2, :, :, :, 0] = 6  # period 0
        motion[:, 2, :, :, :, 1] = 7  # period 1.0
        motion[:, 2, :, :, :, 2] = 8  # period 2.0
        # Youngs_97_interface
        motion[:, 3, :, :, :, 0] = 9  # period 0
        motion[:, 3, :, :, :, 1] = 10  # period 1.0
        motion[:, 3, :, :, :, 2] = 11  # period 2.0
        # Young_97_intraslab
        motion[:, 4, :, :, :, 0] = 12  # period 0
        motion[:, 4, :, :, :, 1] = 13  # period 1.0
        motion[:, 4, :, :, :, 2] = 14  # period 2.0

        # A minimal set of eqrm_flags so create_parameter_data passes
        # We only care about atten_models -> everything else are dummy values
        eqrm_flags = {}
        eqrm_flags['run_type'] = 'hazard'
        eqrm_flags['is_scenario'] = True
        eqrm_flags['output_dir'] = self.dir
        eqrm_flags['input_dir'] = self.dir
        eqrm_flags['site_tag'] = 'different_to_function'
        eqrm_flags['return_periods'] = [0.0]
        eqrm_flags['use_amplification'] = False
        eqrm_flags['zone_source_tag'] = 'not_used'
        eqrm_flags['atten_periods'] = atten_periods
        eqrm_flags['atten_models'] = atten_models

        return (event_set, event_activity, source_model, sites, motion,
                eqrm_flags)
Exemple #16
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    def test_read_from_file(self):
        """Test reading Sites data from a file."""

        # create dummy CSV file - this is bridges data, but sites should handle anything
        lat = [-35.352085, -35.348677, -35.336884, -35.345209,
               -35.340859, -35.301472, -35.293012, -35.320122]
        lon = [149.236994, 149.239383, 149.241625, 149.205986,
               149.163037, 149.141364, 149.126767, 149.063810]
        clsf = ['HWB17', 'HWB17', 'HWB17', 'HWB22',
                 'HWB3', 'HWB17', 'HWB10', 'HWB28']
        cat = ['BRIDGE', 'BRIDGE', 'BRIDGE', 'BRIDGE',
               'BRIDGE', 'BRIDGE', 'BRIDGE', 'BRIDGE']
        skew = [0, 32, 20, 4, 0, 0, 12, 0]
        span = [2, 3, 6, 2, 1, 1, 3, 3]
        cls = ['E', 'F', 'G', 'D', 'E', 'F', 'G', 'C']
        attribute_keys = ['BID', 'STRUCTURE_CLASSIFICATION']

        dummy_csv_data = ['BID,LONGITUDE,LATITUDE,STRUCTURE_CLASSIFICATION,'
                          'STRUCTURE_CATEGORY,SKEW,SPAN,SITE_CLASS',
                          '2,%.6f,%.6f,%s,%s,%s,%s,%s'
                              % (lon[0], lat[0], clsf[0], cat[0], skew[0], span[0], cls[0]),
                          '3,%.6f,%.6f,%s,%s,%s,%s,%s'
                              % (lon[1], lat[1], clsf[1], cat[1], skew[1], span[1], cls[1]),
                          '4,%.6f,%.6f,%s,%s,%s,%s,%s'
                              % (lon[2], lat[2], clsf[2], cat[2], skew[2], span[2], cls[2]),
                          '5,%.6f,%.6f,%s,%s,%s,%s,%s'
                              % (lon[3], lat[3], clsf[3], cat[3], skew[3], span[3], cls[3]),
                          '6,%.6f,%.6f,%s,%s,%s,%s,%s'
                              % (lon[4], lat[4], clsf[4], cat[4], skew[4], span[4], cls[4]),
                          '7,%.6f,%.6f,%s,%s,%s,%s,%s'
                              % (lon[5], lat[5], clsf[5], cat[5], skew[5], span[5], cls[5]),
                          '8,%.6f,%.6f,%s,%s,%s,%s,%s'
                              % (lon[6], lat[6], clsf[6], cat[6], skew[6], span[6], cls[6]),
                          '9,%.6f,%.6f,%s,%s,%s,%s,%s'
                              % (lon[7], lat[7], clsf[7], cat[7], skew[7], span[7], cls[7])]

        (handle, filename) = tempfile.mkstemp('.csv', 'test_sites_')
        os.close(handle)

        f = open(filename, 'wb')
        f.write('\n'.join(dummy_csv_data))
        f.close()

        # now read file - pass attribute_conversion as **kwargs data
        sites = Sites.from_csv(filename, BID=int, STRUCTURE_CLASSIFICATION=str)

        # make sure we have required attributes, and only those attributes
        self.failUnless(hasattr(sites, 'longitude'))
        self.failUnless(np.all(sites.longitude == lon))
        self.failUnless(hasattr(sites, 'latitude'))
        self.failUnless(np.all(sites.latitude == lat))

        self.failUnless(len(sites.attributes) == len(attribute_keys))
        for key in sites.attributes:
            if key not in attribute_keys:
                self.fail("Found unexpected .attribute key '%s'" % key)

        # repeat above test, pass attributes a dict
        attr_dict = {'BID': int, 'STRUCTURE_CATEGORY': str, 'SKEW': float,
                     'SPAN': int, 'SITE_CLASS': str}
        attribute_keys = ['BID', 'STRUCTURE_CATEGORY', 'SKEW', 'SPAN', 'SITE_CLASS']
        sites = Sites.from_csv(filename, **attr_dict)

        # make sure we have required attributes, and only those attributes
        self.failUnless(hasattr(sites, 'longitude'))
        self.failUnless(np.all(sites.longitude == lon))
        self.failUnless(hasattr(sites, 'latitude'))
        self.failUnless(np.all(sites.latitude == lat))

        self.failUnless(len(sites.attributes) == len(attribute_keys))
        for key in sites.attributes:
            if key not in attribute_keys:
                self.fail("Found unexpected .attribute key '%s'" % key)

        # get rid of test data file 
        os.remove(filename)
Exemple #17
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    def test_read_from_file(self):
        """Test reading Sites data from a file."""

        # create dummy CSV file - this is bridges data, but sites should handle anything
        lat = [-35.352085, -35.348677, -35.336884, -35.345209, -35.340859, -35.301472, -35.293012, -35.320122]
        lon = [149.236994, 149.239383, 149.241625, 149.205986, 149.163037, 149.141364, 149.126767, 149.063810]
        clsf = ["HWB17", "HWB17", "HWB17", "HWB22", "HWB3", "HWB17", "HWB10", "HWB28"]
        cat = ["BRIDGE", "BRIDGE", "BRIDGE", "BRIDGE", "BRIDGE", "BRIDGE", "BRIDGE", "BRIDGE"]
        skew = [0, 32, 20, 4, 0, 0, 12, 0]
        span = [2, 3, 6, 2, 1, 1, 3, 3]
        cls = ["E", "F", "G", "D", "E", "F", "G", "C"]
        attribute_keys = ["BID", "STRUCTURE_CLASSIFICATION"]

        dummy_csv_data = [
            "BID,LONGITUDE,LATITUDE,STRUCTURE_CLASSIFICATION," "STRUCTURE_CATEGORY,SKEW,SPAN,SITE_CLASS",
            "2,%.6f,%.6f,%s,%s,%s,%s,%s" % (lon[0], lat[0], clsf[0], cat[0], skew[0], span[0], cls[0]),
            "3,%.6f,%.6f,%s,%s,%s,%s,%s" % (lon[1], lat[1], clsf[1], cat[1], skew[1], span[1], cls[1]),
            "4,%.6f,%.6f,%s,%s,%s,%s,%s" % (lon[2], lat[2], clsf[2], cat[2], skew[2], span[2], cls[2]),
            "5,%.6f,%.6f,%s,%s,%s,%s,%s" % (lon[3], lat[3], clsf[3], cat[3], skew[3], span[3], cls[3]),
            "6,%.6f,%.6f,%s,%s,%s,%s,%s" % (lon[4], lat[4], clsf[4], cat[4], skew[4], span[4], cls[4]),
            "7,%.6f,%.6f,%s,%s,%s,%s,%s" % (lon[5], lat[5], clsf[5], cat[5], skew[5], span[5], cls[5]),
            "8,%.6f,%.6f,%s,%s,%s,%s,%s" % (lon[6], lat[6], clsf[6], cat[6], skew[6], span[6], cls[6]),
            "9,%.6f,%.6f,%s,%s,%s,%s,%s" % (lon[7], lat[7], clsf[7], cat[7], skew[7], span[7], cls[7]),
        ]

        (handle, filename) = tempfile.mkstemp(".csv", "test_sites_")
        os.close(handle)

        f = open(filename, "wb")
        f.write("\n".join(dummy_csv_data))
        f.close()

        # now read file - pass attribute_conversion as **kwargs data
        sites = Sites.from_csv(filename, BID=int, STRUCTURE_CLASSIFICATION=str)

        # make sure we have required attributes, and only those attributes
        self.failUnless(hasattr(sites, "longitude"))
        self.failUnless(np.all(sites.longitude == lon))
        self.failUnless(hasattr(sites, "latitude"))
        self.failUnless(np.all(sites.latitude == lat))

        self.failUnless(len(sites.attributes) == len(attribute_keys))
        for key in sites.attributes:
            if key not in attribute_keys:
                self.fail("Found unexpected .attribute key '%s'" % key)

        # repeat above test, pass attributes a dict
        attr_dict = {"BID": int, "STRUCTURE_CATEGORY": str, "SKEW": float, "SPAN": int, "SITE_CLASS": str}
        attribute_keys = ["BID", "STRUCTURE_CATEGORY", "SKEW", "SPAN", "SITE_CLASS"]
        sites = Sites.from_csv(filename, **attr_dict)

        # make sure we have required attributes, and only those attributes
        self.failUnless(hasattr(sites, "longitude"))
        self.failUnless(np.all(sites.longitude == lon))
        self.failUnless(hasattr(sites, "latitude"))
        self.failUnless(np.all(sites.latitude == lat))

        self.failUnless(len(sites.attributes) == len(attribute_keys))
        for key in sites.attributes:
            if key not in attribute_keys:
                self.fail("Found unexpected .attribute key '%s'" % key)

        # get rid of test data file
        os.remove(filename)