def tester(n, m):
N = global_N
test_data = tv.sin_cos_arr(N, n, m)
from upsample import upsample
test_data = upsample(test_data, factor=4)
dd = field_trace.Derivator(test_data)
nulls = field_trace.find_null_cells_minimize(dd)
cell_locs = [null.loc for null in nulls]
null_locs = [(null.x0, null.y0) for null in nulls]
print 4*n*m, len(nulls)
if 0:
X, Y = zip(*null_locs)
import pylab as pl
pl.ion()
pl.imshow(test_data)
pl.scatter(Y, X)
X, Y = zip(*cell_locs)
pl.scatter(Y, X, c='r')
raw_input("enter to continue")
pl.close('all')
def test_level_set():
N = 64
n, m = 1, 4
test_data = tv.sin_cos_arr(N, n, m)
dd = field_trace.Derivator(test_data)
nulls = field_trace.find_null_cells(dd)
saddles = [null for null in nulls if null.is_saddle()]
peaks = [null for null in nulls if not null.is_saddle()]
saddle0s = [(s.x0, s.y0) for s in saddles]
peak0s = [(p.x0, p.y0) for p in peaks]
x0, y0 = saddle0s[0]
psi_interp = Interp2DPeriodic(N, N, test_data)
level_val = psi_interp.eval(x0, y0)
level_sets = [null.levelset for null in nulls]
mask = field_trace.marked_to_mask(test_data.shape, level_sets)
masked_data = test_data.copy()
masked_data[mask] = test_data.max()
if 0:
import pylab as pl
pl.ion()
pl.imshow(masked_data, cmap='hot', interpolation='nearest')
# # Plot the grid points
# if 0:
# X = np.linspace(0, dta.shape[0]-1, dta.shape[0])
# for i in range(dta.shape[0]):
# Y = np.zeros(dta.shape[1])
# Y.fill(i)
# pl.scatter(Y, X, c='m')
X, Y = zip(*saddle0s)
pl.scatter(Y, X, c='k')
X, Y = zip(*peak0s)
pl.scatter(Y, X, c='b')
raw_input("enter to continue")
def test_derivator():
N = global_N
n, m = 10, 3
test_data = tv.sin_cos_arr(N, n, m)
dd = field_trace.Derivator(test_data)
psi_1 = vcalc.cderivative(test_data, 'X_DIR')
psi_2 = vcalc.cderivative(test_data, 'Y_DIR')
ok_(np.allclose(dd.deriv1, psi_1))
ok_(np.allclose(dd.deriv2, psi_2))
ok_(np.allclose(dd.perp_deriv1, psi_2))
ok_(np.allclose(dd.perp_deriv2, -psi_1))
psi_11 = vcalc.cderivative(test_data, 'X_DIR', order=2)
psi_22 = vcalc.cderivative(test_data, 'Y_DIR', order=2)
psi_12 = vcalc.cderivative(test_data, 'X_DIR')
psi_12 = vcalc.cderivative(psi_12, 'Y_DIR')
Xlen = float(N)
psi_11_interp = Interp2DPeriodic(Xlen, Xlen, psi_11)
psi_22_interp = Interp2DPeriodic(Xlen, Xlen, psi_22)
psi_12_interp = Interp2DPeriodic(Xlen, Xlen, psi_12)
num_pts = 100
rand_Xs = np.random.uniform(0.0, float(N), num_pts)
rand_Ys = np.random.uniform(0.0, float(N), num_pts)
def compare_interps(dd_interp, interp, xys):
dd_interps = [dd_interp.eval(x, y) for (x, y) in zip(*xys)]
interps = [interp.eval(x, y) for (x, y) in zip(*xys)]
ok_(np.allclose(dd_interps, interps))
compare_interps(dd.deriv12_interp, psi_12_interp, [rand_Xs, rand_Ys])
compare_interps(dd.deriv11_interp, psi_11_interp, [rand_Xs, rand_Ys])
compare_interps(dd.deriv22_interp, psi_22_interp, [rand_Xs, rand_Ys])
