def test_gaussian_trigger(self):
x=np.arange(100)
max_val=10.*np.exp(-(x-50.)*(x-50.)/(10.*10.))
max_x=np.random.rand(100)
max_y=np.random.rand(100)
max_z=np.random.rand(100)
left_trig=right_trig=3
locs=trigger_locations_inner(max_val,max_x,max_y,max_z,left_trig,right_trig,0.0,1.0)
self.assertAlmostEqual(locs[0]['max_trig'],10)
self.assertAlmostEqual(locs[0]['o_time'],50)
def test_gaussian_trigger(self):
x = np.arange(100)
max_val = 10. * np.exp(-(x - 50.) * (x - 50.) / (10. * 10.))
max_x = np.random.rand(100)
max_y = np.random.rand(100)
max_z = np.random.rand(100)
left_trig = right_trig = 3
locs = trigger_locations_inner(max_val, max_x, max_y, max_z, left_trig,
right_trig, 0.0, 1.0)
self.assertAlmostEqual(locs[0]['max_trig'], 10)
self.assertAlmostEqual(locs[0]['o_time'], 50)
def test_smoothing(self):
from filters import smooth
x=np.arange(100)
max_val=100.*np.exp(-(x-50.)*(x-50.)/(10.*10.))+np.random.rand(100)
max_x=np.random.rand(100)
max_y=np.random.rand(100)
max_z=np.random.rand(100)
max_val_smooth=smooth(max_val)
left_trig=right_trig=3
locs_smooth=trigger_locations_inner(max_val_smooth,max_x,max_y,max_z,left_trig,right_trig,0.0,1.0)
self.assertAlmostEqual(locs_smooth[0]['o_time'],50.,2)
def test_smoothing(self):
from filters import smooth
x = np.arange(100)
max_val = 100. * np.exp(-(x - 50.) * (x - 50.) /
(10. * 10.)) + np.random.rand(100)
max_x = np.random.rand(100)
max_y = np.random.rand(100)
max_z = np.random.rand(100)
max_val_smooth = smooth(max_val)
left_trig = right_trig = 3
locs_smooth = trigger_locations_inner(max_val_smooth, max_x, max_y,
max_z, left_trig, right_trig,
0.0, 1.0)
self.assertAlmostEqual(locs_smooth[0]['o_time'], 50., 2)
def test_simple_trigger(self):
max_val=np.random.rand(100)
max_x=np.random.rand(100)
max_y=np.random.rand(100)
max_z=np.random.rand(100)
max_val[10]=5
max_val[20]=7
max_val[45]=2
max_val[80]=10
left_trig=right_trig=3
locs=trigger_locations_inner(max_val,max_x,max_y,max_z,left_trig,right_trig,0.0,1.0)
self.assertEqual(len(locs),3)
self.assertAlmostEqual(locs[0]['max_trig'],5)
self.assertAlmostEqual(locs[1]['max_trig'],7)
self.assertAlmostEqual(locs[2]['max_trig'],10)
self.assertAlmostEqual(locs[0]['o_time'],10)
self.assertAlmostEqual(locs[1]['o_time'],20)
self.assertAlmostEqual(locs[2]['o_time'],80)
def test_simple_trigger(self):
max_val = np.random.rand(100)
max_x = np.random.rand(100)
max_y = np.random.rand(100)
max_z = np.random.rand(100)
max_val[10] = 5
max_val[20] = 7
max_val[45] = 2
max_val[80] = 10
left_trig = right_trig = 3
locs = trigger_locations_inner(max_val, max_x, max_y, max_z, left_trig,
right_trig, 0.0, 1.0)
self.assertEqual(len(locs), 3)
self.assertAlmostEqual(locs[0]['max_trig'], 5)
self.assertAlmostEqual(locs[1]['max_trig'], 7)
self.assertAlmostEqual(locs[2]['max_trig'], 10)
self.assertAlmostEqual(locs[0]['o_time'], 10)
self.assertAlmostEqual(locs[1]['o_time'], 20)
self.assertAlmostEqual(locs[2]['o_time'], 80)
def test_dirac_migration(self):
from locations_trigger import trigger_locations_inner
from filters import smooth
wo = WavelocOptions()
wo.set_test_options()
wo.opdict['outdir'] = 'TEST_Dirac'
wo.opdict['search_grid'] = 'grid.Taisne.search.hdr'
wo.opdict['loclevel'] = 10
wo.opdict[
'load_ttimes_buf'] = True # Optimized in time, but you must be usre you're reading the right grid for the test
wo.opdict['syn_addnoise'] = False
wo.opdict['syn_amplitude'] = 1.0
wo.opdict['syn_datalength'] = 20.0
wo.opdict['syn_samplefreq'] = 100.0
wo.opdict['syn_kwidth'] = 0.1
wo.opdict['syn_otime'] = 6.0
wo.opdict['syn_ix'] = 16
wo.opdict['syn_iy'] = 8
wo.opdict['syn_iz'] = 6
wo.opdict['syn_filename'] = 'test_grid4D_hires.hdf5'
wo.verify_migration_options()
wo.verify_location_options()
wo.verify_synthetic_options()
##########################
# generate the test case and retrieve necessary information
##########################
logging.info('Running synthetic test case generation...')
test_info = generateSyntheticDirac(wo.opdict)
logging.debug(test_info)
# retrieve info
grid_filename = test_info['dat_file']
stack_filename = test_info['stack_file']
nx, ny, nz, nt = test_info['grid_shape']
dx, dy, dz, dt = test_info['grid_spacing']
x_orig, y_orig, z_orig = test_info['grid_orig']
ix_true, iy_true, iz_true, it_true = test_info['true_indexes']
stack_start_time = test_info['start_time']
# plot base filename
base_path = wo.opdict['base_path']
outdir = wo.opdict['outdir']
# loclevel for triggers
loclevel = wo.opdict['loclevel']
# set up x, y, z, t arrays
x = np.arange(nx) * dx
y = np.arange(ny) * dy
z = np.arange(nz) * dz
t = np.arange(nt) * dt + stack_start_time
# extract the max stacks
f_stack = h5py.File(stack_filename, 'r')
max_val = f_stack['max_val']
max_x = f_stack['max_x']
max_y = f_stack['max_y']
max_z = f_stack['max_z']
locs = trigger_locations_inner(max_val, max_x, max_y, max_z, loclevel,
loclevel, stack_start_time, dt)
self.assertTrue(len(locs) > 0)
#print locs
# This is a dirac test, so only have one element in locs
imax = np.argmax([loc['max_trig'] for loc in locs])
trig_loc = locs[imax]
self.assertAlmostEqual(wo.opdict['syn_otime'], trig_loc['o_time'], 2)
self.assertAlmostEqual(wo.opdict['syn_ix'] * dx + x_orig,
trig_loc['x_mean'])
self.assertAlmostEqual(wo.opdict['syn_iy'] * dy + y_orig,
trig_loc['y_mean'])
self.assertAlmostEqual(wo.opdict['syn_iz'] * dz + z_orig,
trig_loc['z_mean'])
f_stack.close()
def test_dirac_migration(self):
from locations_trigger import trigger_locations_inner
from filters import smooth
wo=WavelocOptions()
wo.set_test_options()
wo.opdict['outdir'] = 'TEST_Dirac'
wo.opdict['search_grid']='grid.Taisne.search.hdr'
wo.opdict['loclevel'] = 10
wo.opdict['load_ttimes_buf'] = True # Optimized in time, but you must be usre you're reading the right grid for the test
wo.opdict['syn_addnoise']=False
wo.opdict['syn_amplitude']=1.0
wo.opdict['syn_datalength']=20.0
wo.opdict['syn_samplefreq']=100.0
wo.opdict['syn_kwidth']=0.1
wo.opdict['syn_otime']=6.0
wo.opdict['syn_ix']=16
wo.opdict['syn_iy']=8
wo.opdict['syn_iz']=6
wo.opdict['syn_filename']='test_grid4D_hires.hdf5'
wo.verify_migration_options()
wo.verify_location_options()
wo.verify_synthetic_options()
##########################
# generate the test case and retrieve necessary information
##########################
logging.info('Running synthetic test case generation...')
test_info=generateSyntheticDirac(wo.opdict)
logging.debug(test_info)
# retrieve info
grid_filename=test_info['dat_file']
stack_filename=test_info['stack_file']
nx,ny,nz,nt=test_info['grid_shape']
dx,dy,dz,dt=test_info['grid_spacing']
x_orig,y_orig,z_orig=test_info['grid_orig']
ix_true,iy_true,iz_true,it_true=test_info['true_indexes']
stack_start_time=test_info['start_time']
# plot base filename
base_path=wo.opdict['base_path']
outdir=wo.opdict['outdir']
# loclevel for triggers
loclevel=wo.opdict['loclevel']
# set up x, y, z, t arrays
x=np.arange(nx)*dx
y=np.arange(ny)*dy
z=np.arange(nz)*dz
t=np.arange(nt)*dt+stack_start_time
# extract the max stacks
f_stack=h5py.File(stack_filename,'r')
max_val=f_stack['max_val']
max_x=f_stack['max_x']
max_y=f_stack['max_y']
max_z=f_stack['max_z']
locs=trigger_locations_inner(max_val,max_x,max_y,max_z,loclevel,loclevel,stack_start_time,dt)
self.assertTrue(len(locs)>0)
#print locs
# This is a dirac test, so only have one element in locs
imax=np.argmax([loc['max_trig'] for loc in locs])
trig_loc=locs[imax]
self.assertAlmostEqual(wo.opdict['syn_otime'],trig_loc['o_time'],2)
self.assertAlmostEqual(wo.opdict['syn_ix']*dx+x_orig,trig_loc['x_mean'])
self.assertAlmostEqual(wo.opdict['syn_iy']*dy+y_orig,trig_loc['y_mean'])
self.assertAlmostEqual(wo.opdict['syn_iz']*dz+z_orig,trig_loc['z_mean'])
f_stack.close()