def full_focus():
focus = pygridgen.Focus()
focus.add_focus(0.25, 'x', factor=3, extent=0.1)
focus.add_focus(0.75, 'x', factor=2, extent=0.2)
focus.add_focus(0.50, 'y', factor=2, extent=0.3)
return focus
def test_gridgen_to_from_spec(use_focus):
x = numpy.array([0.50, 2.00, 2.00, 3.50, 3.50, 2.00, 2.00, 0.50, 0.50])
y = numpy.array([0.50, 0.50, 1.75, 1.75, 2.25, 2.25, 3.50, 3.50, 0.50])
beta = numpy.array([1, 1, -1, 1, 1, -1, 1, 1, 0])
focus = None
if use_focus:
focus = pygridgen.Focus()
focus.add_focus(0.50, 'y', factor=5, extent=0.25)
focus.add_focus(0.50, 'x', factor=5, extent=0.25)
grid1 = pygridgen.Gridgen(x, y, beta, shape=(20, 10), focus=focus)
grid2 = pygridgen.grid.Gridgen.from_spec((grid1.to_spec()))
# testing - using almost equal due to rounding issues with floats
numpy.testing.assert_array_almost_equal(grid1.x, grid2.x)
numpy.testing.assert_array_almost_equal(grid1.y, grid2.y)
def test_gridgen_to_from_spec(simple_grid, use_focus):
x = numpy.array([0.50, 2.00, 2.00, 3.50, 3.50, 2.00, 2.00, 0.50, 0.50])
y = numpy.array([0.50, 0.50, 1.75, 1.75, 2.25, 2.25, 3.50, 3.50, 0.50])
beta = numpy.array([1, 1, -1, 1, 1, -1, 1, 1, 0])
if use_focus:
focus = pygridgen.Focus()
focus.add_focus(0.50, 'y', factor=5, extent=0.25)
focus.add_focus(0.50, 'x', factor=5, extent=0.25)
simple_grid.focus = focus
simple_grid.generate_grid()
grid2 = pygridgen.grid.Gridgen.from_spec((simple_grid.to_spec()))
# testing - using almost equal due to rounding issues with floats
numpy.testing.assert_array_almost_equal(simple_grid.x, grid2.x)
numpy.testing.assert_array_almost_equal(simple_grid.y, grid2.y)
def make_focus():
focus = pygridgen.Focus()
focus.add_focus(0.50, 'x', factor=2.0, extent=3.0)
focus.add_focus(0.75, 'y', factor=0.5, extent=2.0)
return focus
def setup(self):
self.x = [0.0, 1.0, 2.0, 1.0, 0.0]
self.y = [0.0, 0.0, 0.5, 1.0, 1.0]
self.beta = [1.0, 1.0, 0.0, 1.0, 1.0]
self.shape = (9, 9)
focus = pygridgen.Focus()
focus.add_focus_x(0.50, factor=2.0, Rx=3.0)
focus.add_focus_y(0.75, factor=0.5, Ry=2.0)
self.options = {'ul_idx': 0, 'focus': focus}
self.grid = self.make_grid()
self.known_x = np.array(
[[1., 1.04, 1.12, 1.27, 2., 1.27, 1.12, 1.04, 1.],
[0.95, 0.97, 1.02, 1.1, 1.15, 1.1, 1.02, 0.97, 0.95],
[0.86, 0.87, 0.89, 0.92, 0.93, 0.92, 0.89, 0.87, 0.86],
[0.73, 0.74, 0.75, 0.76, 0.76, 0.76, 0.75, 0.74, 0.73],
[0.59, 0.59, 0.6, 0.6, 0.6, 0.6, 0.6, 0.59, 0.59],
[0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45],
[0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
[0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15],
[0., 0., 0., 0., 0., 0., 0., 0., 0.]])
self.known_y = np.array(
[[0., 0.02, 0.06, 0.14, 0.5, 0.86, 0.94, 0.98, 1.],
[-0., 0.07, 0.16, 0.3, 0.5, 0.7, 0.84, 0.93, 1.],
[-0., 0.1, 0.21, 0.35, 0.5, 0.65, 0.79, 0.9, 1.],
[-0., 0.12, 0.24, 0.37, 0.5, 0.63, 0.76, 0.88, 1.],
[-0., 0.12, 0.25, 0.37, 0.5, 0.63, 0.75, 0.88, 1.],
[-0., 0.12, 0.25, 0.37, 0.5, 0.63, 0.75, 0.88, 1.],
[-0., 0.13, 0.25, 0.38, 0.5, 0.62, 0.75, 0.87, 1.],
[-0., 0.13, 0.25, 0.38, 0.5, 0.62, 0.75, 0.87, 1.],
[-0., 0.13, 0.25, 0.38, 0.5, 0.62, 0.75, 0.87, 1.]])
self.known_x_psi = np.array(
[[0.97, 1.02, 1.1, 1.15, 1.1, 1.02, 0.97],
[0.87, 0.89, 0.92, 0.93, 0.92, 0.89, 0.87],
[0.74, 0.75, 0.76, 0.76, 0.76, 0.75, 0.74],
[0.59, 0.6, 0.6, 0.6, 0.6, 0.6, 0.59],
[0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45],
[0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
[0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15]])
self.known_y_psi = np.array([[0.07, 0.16, 0.3, 0.5, 0.7, 0.84, 0.93],
[0.1, 0.21, 0.35, 0.5, 0.65, 0.79, 0.9],
[0.12, 0.24, 0.37, 0.5, 0.63, 0.76, 0.88],
[0.12, 0.25, 0.37, 0.5, 0.63, 0.75, 0.88],
[0.12, 0.25, 0.37, 0.5, 0.63, 0.75, 0.88],
[0.13, 0.25, 0.38, 0.5, 0.62, 0.75, 0.87],
[0.13, 0.25, 0.38, 0.5, 0.62, 0.75,
0.87]])
self.known_x_rho = np.array(
[[0.99, 1.04, 1.13, 1.38, 1.38, 1.13, 1.04, 0.99],
[0.91, 0.94, 0.98, 1.02, 1.02, 0.98, 0.94, 0.91],
[0.8, 0.81, 0.83, 0.84, 0.84, 0.83, 0.81, 0.8],
[0.66, 0.67, 0.68, 0.68, 0.68, 0.68, 0.67, 0.66],
[0.52, 0.52, 0.52, 0.53, 0.53, 0.52, 0.52, 0.52],
[0.37, 0.37, 0.37, 0.37, 0.37, 0.37, 0.37, 0.37],
[0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22],
[0.07, 0.07, 0.07, 0.07, 0.07, 0.07, 0.07, 0.07]])
self.known_y_rho = np.array(
[[0.02, 0.08, 0.16, 0.36, 0.64, 0.84, 0.92, 0.98],
[0.04, 0.14, 0.26, 0.41, 0.59, 0.74, 0.86, 0.96],
[0.05, 0.17, 0.29, 0.43, 0.57, 0.71, 0.83, 0.95],
[0.06, 0.18, 0.3, 0.43, 0.57, 0.7, 0.82, 0.94],
[0.06, 0.19, 0.31, 0.44, 0.56, 0.69, 0.81, 0.94],
[0.06, 0.19, 0.31, 0.44, 0.56, 0.69, 0.81, 0.94],
[0.06, 0.19, 0.31, 0.44, 0.56, 0.69, 0.81, 0.94],
[0.06, 0.19, 0.31, 0.44, 0.56, 0.69, 0.81, 0.94]])
self.known_x_u = np.array([[1., 1.07, 1.19, 1.57, 1.19, 1.07, 1.],
[0.92, 0.96, 1.01, 1.04, 1.01, 0.96, 0.92],
[0.8, 0.82, 0.84, 0.85, 0.84, 0.82, 0.8],
[0.66, 0.67, 0.68, 0.68, 0.68, 0.67, 0.66],
[0.52, 0.52, 0.53, 0.53, 0.53, 0.52, 0.52],
[0.37, 0.37, 0.37, 0.38, 0.37, 0.37, 0.37],
[0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22],
[0.07, 0.07, 0.07, 0.07, 0.07, 0.07, 0.07]])
self.known_x_v = np.array(
[[0.96, 1., 1.06, 1.12, 1.12, 1.06, 1., 0.96],
[0.86, 0.88, 0.9, 0.92, 0.92, 0.9, 0.88, 0.86],
[0.73, 0.74, 0.75, 0.76, 0.76, 0.75, 0.74, 0.73],
[0.59, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.59],
[0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45],
[0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
[0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15]])
self.known_y_u = np.array([[0.04, 0.11, 0.22, 0.5, 0.78, 0.89, 0.96],
[0.09, 0.19, 0.32, 0.5, 0.68, 0.81, 0.91],
[0.11, 0.23, 0.36, 0.5, 0.64, 0.77, 0.89],
[0.12, 0.24, 0.37, 0.5, 0.63, 0.76, 0.88],
[0.12, 0.25, 0.37, 0.5, 0.63, 0.75, 0.88],
[0.13, 0.25, 0.37, 0.5, 0.63, 0.75, 0.87],
[0.13, 0.25, 0.38, 0.5, 0.62, 0.75, 0.87],
[0.13, 0.25, 0.38, 0.5, 0.62, 0.75, 0.87]])
self.known_y_v = np.array(
[[0.04, 0.12, 0.23, 0.4, 0.6, 0.77, 0.88, 0.96],
[0.05, 0.16, 0.28, 0.42, 0.58, 0.72, 0.84, 0.95],
[0.06, 0.18, 0.3, 0.43, 0.57, 0.7, 0.82, 0.94],
[0.06, 0.18, 0.31, 0.44, 0.56, 0.69, 0.82, 0.94],
[0.06, 0.19, 0.31, 0.44, 0.56, 0.69, 0.81, 0.94],
[0.06, 0.19, 0.31, 0.44, 0.56, 0.69, 0.81, 0.94],
[0.06, 0.19, 0.31, 0.44, 0.56, 0.69, 0.81, 0.94]])
