本文整理汇总了Python中openquake.hmtk.seismicity.catalogue.Catalogue.hypocentres_as_mesh方法的典型用法代码示例。如果您正苦于以下问题：Python Catalogue.hypocentres_as_mesh方法的具体用法？Python Catalogue.hypocentres_as_mesh怎么用？Python Catalogue.hypocentres_as_mesh使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类openquake.hmtk.seismicity.catalogue.Catalogue的用法示例。
在下文中一共展示了Catalogue.hypocentres_as_mesh方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_hypocentres_as_mesh
# 需要导入模块: from openquake.hmtk.seismicity.catalogue import Catalogue [as 别名]
# 或者: from openquake.hmtk.seismicity.catalogue.Catalogue import hypocentres_as_mesh [as 别名]
def test_hypocentres_as_mesh(self):
# Tests the function to render the hypocentres to a
# hazardlib.geo.mesh.Mesh object.
cat = Catalogue()
cat.data['longitude'] = np.array([2., 3.])
cat.data['latitude'] = np.array([2., 3.])
cat.data['depth'] = np.array([2., 3.])
self.assertTrue(isinstance(cat.hypocentres_as_mesh(), Mesh))示例2: TestSelector
# 需要导入模块: from openquake.hmtk.seismicity.catalogue import Catalogue [as 别名]
# 或者: from openquake.hmtk.seismicity.catalogue.Catalogue import hypocentres_as_mesh [as 别名]
#.........这里部分代码省略.........
for iloc in range(0, 4)])
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
# Simple case with nodes inside, outside and on the border of polygon
selector0 = CatalogueSelector(self.catalogue)
test_cat1 = selector0.within_polygon(polygon0)
self.assertTrue(np.allclose(test_cat1.data['longitude'],
np.array([5.0, 5.5, 6.0])))
self.assertTrue(np.allclose(test_cat1.data['latitude'],
np.array([5.0, 5.5, 6.0])))
self.assertTrue(np.allclose(test_cat1.data['depth'],
np.array([1.0, 1.0, 1.0])))
# CASE 2: As case 1 with one of the inside nodes outside of the depths
self.catalogue.data['depth'] = \
np.array([1.0, 1.0, 1.0, 50.0, 1.0, 1.0, 1.0], dtype=float)
selector0 = CatalogueSelector(self.catalogue)
test_cat1 = selector0.within_polygon(polygon0, upper_depth=0.0,
lower_depth=10.0)
self.assertTrue(np.allclose(test_cat1.data['longitude'],
np.array([5.0, 6.0])))
self.assertTrue(np.allclose(test_cat1.data['latitude'],
np.array([5.0, 6.0])))
self.assertTrue(np.allclose(test_cat1.data['depth'],
np.array([1.0])))
def test_point_in_circular_distance(self):
# Tests point in circular distance
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
test_point = Point(5.5, 5.5)
test_mesh = self.catalogue.hypocentres_as_mesh()
selector0 = CatalogueSelector(self.catalogue)
# Within 10 km
test_cat_10 = selector0.circular_distance_from_point(
test_point, 10., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_10.data['longitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['latitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['depth'],
np.array([1.0]))
# Within 100 km
test_cat_100 = selector0.circular_distance_from_point(
test_point, 100., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_100.data['longitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_equal(test_cat_100.data['latitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0]))
# Within 1000 km
test_cat_1000 = selector0.circular_distance_from_point(
test_point, 1000., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_1000.data['longitude'],
self.catalogue.data['longitude'])
np.testing.assert_array_equal(test_cat_1000.data['latitude'],
self.catalogue.data['latitude'])
np.testing.assert_array_equal(test_cat_1000.data['depth'],
self.catalogue.data['depth'])
def test_cartesian_square_on_point(self):