def make_model():
start_time = datetime(2015, 5, 14, 0)
model = Model(
time_step=3600 * 24, # one day
start_time=start_time,
duration=timedelta(days=3),
)
model.cache_enabled = False
model.uncertain = False
# N = 10 # a line of ten points
# line_pos = np.zeros((N, 3), dtype=np.float64)
# line_pos[:, 0] = np.linspace(rel_start_pos[0], rel_end_pos[0], N)
# line_pos[:, 1] = np.linspace(rel_start_pos[1], rel_end_pos[1], N)
# start_pos = (-164.01696, 72.921024, 0)
# model.spills += point_line_release_spill(1,
# start_position=start_pos,
# release_time=model.start_time,
# end_position=start_pos)
# release = SpatialRelease(start_position=line_pos,
# release_time=model.start_time)
# model.spills += Spill(release)
c_ice_mover = IceMover(curr_file, topology_file)
model.movers += c_ice_mover
model.outputters += IceImageOutput(c_ice_mover,
viewport=((-175.0, 65.0), (-145.0,
75.05)))
return model
def make_model():
start_time = datetime(2015, 5, 14, 0)
model = Model(time_step=3600*24, # one day
start_time=start_time,
duration=timedelta(days=3),)
model.cache_enabled = False
model.uncertain = False
# N = 10 # a line of ten points
# line_pos = np.zeros((N, 3), dtype=np.float64)
# line_pos[:, 0] = np.linspace(rel_start_pos[0], rel_end_pos[0], N)
# line_pos[:, 1] = np.linspace(rel_start_pos[1], rel_end_pos[1], N)
# start_pos = (-164.01696, 72.921024, 0)
# model.spills += point_line_release_spill(1,
# start_position=start_pos,
# release_time=model.start_time,
# end_position=start_pos)
# release = SpatialRelease(start_position=line_pos,
# release_time=model.start_time)
# model.spills += Spill(release)
c_ice_mover = IceMover(curr_file, topology_file)
model.movers += c_ice_mover
model.outputters += IceImageOutput(c_ice_mover,
viewport=((-175.0, 65.0),
(-145.0, 75.05))
)
return model
def test_ice_image_mid_run():
"""
Test image outputter with a model
NOTE: could it be tested with just a mover, and not a full model?
-- that gets tricky with the cache and timesteps...
"""
start_time = datetime(2015, 5, 14, 0)
model = Model(time_step=3600 * 24, start_time=start_time, duration=timedelta(days=3)) # one day
model.cache_enabled = False
model.uncertain = False
c_ice_mover = IceMover(curr_file, topology_file)
model.movers += c_ice_mover
# run the model a couple steps
step = model.step()
step = model.step()
# now add the outputter
model.outputters += IceImageOutput(c_ice_mover, viewport=((-175.0, 65.0), (-145.0, 75.05)))
# and run some more:
step = model.step()
step = model.step()
# and check the output
ice_output = step["IceImageOutput"]
for key in ("time_stamp", "thickness_image", "concentration_image", "bounding_box", "projection"):
assert key in ice_output
print "thickness img size:", len(ice_output["thickness_image"])
print "concentration img size:", len(ice_output["concentration_image"])
def test_simple_run_with_image_output_uncertainty(tmpdir):
'''
Pretty much all this tests is that the model will run and output images
'''
images_dir = tmpdir.mkdir('Test_images2').strpath
if os.path.isdir(images_dir):
shutil.rmtree(images_dir)
os.mkdir(images_dir)
start_time = datetime(2012, 9, 15, 12, 0)
# the land-water map
gmap = gnome.map.MapFromBNA(testdata['MapFromBNA']['testmap'],
refloat_halflife=6) # hours
renderer = gnome.outputters.Renderer(testdata['MapFromBNA']['testmap'],
images_dir, size=(400, 300))
model = Model(start_time=start_time,
time_step=timedelta(minutes=15), duration=timedelta(hours=1),
map=gmap,
uncertain=True, cache_enabled=False,
)
model.outputters += renderer
a_mover = SimpleMover(velocity=(1., -1., 0.))
model.movers += a_mover
N = 10 # a line of ten points
start_points = np.zeros((N, 3), dtype=np.float64)
start_points[:, 0] = np.linspace(-127.1, -126.5, N)
start_points[:, 1] = np.linspace(47.93, 48.1, N)
# print start_points
release = SpatialRelease(start_position=start_points,
release_time=start_time)
model.spills += Spill(release)
# model.add_spill(spill)
model.start_time = release.release_time
# image_info = model.next_image()
model.uncertain = True
num_steps_output = 0
while True:
try:
image_info = model.step()
num_steps_output += 1
print image_info
except StopIteration:
print 'Done with the model run'
break
# there is the zeroth step, too.
calculated_steps = (model.duration.total_seconds() / model.time_step) + 1
assert num_steps_output == calculated_steps
def test_simple_run_with_image_output_uncertainty(tmpdir):
'''
Pretty much all this tests is that the model will run and output images
'''
images_dir = tmpdir.mkdir('Test_images2').strpath
if os.path.isdir(images_dir):
shutil.rmtree(images_dir)
os.mkdir(images_dir)
start_time = datetime(2012, 9, 15, 12, 0)
# the land-water map
gmap = gnome.map.MapFromBNA(testdata['MapFromBNA']['testmap'],
refloat_halflife=6) # hours
renderer = gnome.outputters.Renderer(testdata['MapFromBNA']['testmap'],
images_dir, size=(400, 300))
model = Model(start_time=start_time,
time_step=timedelta(minutes=15), duration=timedelta(hours=1),
map=gmap,
uncertain=True, cache_enabled=False,
)
model.outputters += renderer
a_mover = SimpleMover(velocity=(1., -1., 0.))
model.movers += a_mover
N = 10 # a line of ten points
start_points = np.zeros((N, 3), dtype=np.float64)
start_points[:, 0] = np.linspace(-127.1, -126.5, N)
start_points[:, 1] = np.linspace(47.93, 48.1, N)
# print start_points
release = SpatialRelease(start_position=start_points,
release_time=start_time)
model.spills += Spill(release)
# model.add_spill(spill)
model.start_time = release.release_time
# image_info = model.next_image()
model.uncertain = True
num_steps_output = 0
while True:
try:
image_info = model.step()
num_steps_output += 1
print image_info
except StopIteration:
print 'Done with the model run'
break
# there is the zeroth step, too.
calculated_steps = (model.duration.total_seconds() / model.time_step) + 1
assert num_steps_output == calculated_steps
def sample_model():
"""
sample model with no outputter and no spills. Use this as a template for
fixtures to add spills
Uses:
sample_data/MapBounds_Island.bna
Contains: gnome.movers.SimpleMover(velocity=(1.0, -1.0, 0.0))
duration is 1 hour with 15min intervals so 5 timesteps total,
including initial condition,
model is uncertain and cache is not enabled
No spills or outputters defined
To use:
add a spill and run
:returns: It returns a dict -
{'model':model,
'release_start_pos':start_points,
'release_end_pos':end_points}
The release_start_pos and release_end_pos can be used by test to define
the spill's 'start_position' and 'end_position'
"""
release_time = datetime(2012, 9, 15, 12, 0)
# the image output map
mapfile = os.path.join(os.path.dirname(__file__), 'sample_data',
'MapBounds_Island.bna')
# the land-water map
map_ = MapFromBNA(mapfile, refloat_halflife=06) # seconds
model = Model(
time_step=timedelta(minutes=15),
start_time=release_time,
duration=timedelta(hours=1),
map=map_,
uncertain=True,
cache_enabled=False,
)
model.movers += SimpleMover(velocity=(1., -1., 0.0))
model.uncertain = True
start_points = np.zeros((3, ), dtype=np.float64)
end_points = np.zeros((3, ), dtype=np.float64)
start_points[:] = (-127.1, 47.93, 0)
end_points[:] = (-126.5, 48.1, 0)
return {
'model': model,
'release_start_pos': start_points,
'release_end_pos': end_points,
}
def sample_model_fixture_base():
"""
sample model with no outputter and no spills. Use this as a template for
fixtures to add spills
Uses:
sample_data/MapBounds_Island.bna
Contains: gnome.movers.SimpleMover(velocity=(1.0, -1.0, 0.0))
duration is 1 hour with 15min intervals so 5 timesteps total,
including initial condition,
model is uncertain and cache is not enabled
No spills or outputters defined
To use:
add a spill and run
:returns: It returns a dict -
{'model':model,
'release_start_pos':start_points,
'release_end_pos':end_points}
The release_start_pos and release_end_pos can be used by test to define
the spill's 'start_position' and 'end_position'
"""
release_time = datetime(2012, 9, 15, 12, 0)
# the image output map
mapfile = os.path.join(os.path.dirname(__file__),
'sample_data',
'MapBounds_Island.bna')
# the land-water map
map_ = MapFromBNA(mapfile, refloat_halflife=06) # seconds
model = Model(time_step=timedelta(minutes=15),
start_time=release_time,
duration=timedelta(hours=1),
map=map_,
uncertain=True,
cache_enabled=False,
)
model.movers += SimpleMover(velocity=(1., -1., 0.0))
model.uncertain = True
start_points = np.zeros((3, ), dtype=np.float64)
end_points = np.zeros((3, ), dtype=np.float64)
start_points[:] = (-127.1, 47.93, 0)
end_points[:] = (-126.5, 48.1, 0)
return {'model': model,
'release_start_pos': start_points,
'release_end_pos': end_points,
}
def test_ice_image_mid_run():
'''
Test image outputter with a model
NOTE: could it be tested with just a mover, and not a full model?
-- that gets tricky with the cache and timesteps...
'''
start_time = datetime(2015, 5, 14, 0)
model = Model(
time_step=3600 * 24, # one day
start_time=start_time,
duration=timedelta(days=3),
)
model.cache_enabled = False
model.uncertain = False
c_ice_mover = IceMover(curr_file, topology_file)
model.movers += c_ice_mover
# run the model a couple steps
step = model.step()
step = model.step()
# now add the outputter
model.outputters += IceImageOutput(c_ice_mover,
viewport=((-175.0, 65.0), (-145.0,
75.05)))
# and run some more:
step = model.step()
step = model.step()
# and check the output
ice_output = step['IceImageOutput']
for key in ('time_stamp', 'thickness_image', 'concentration_image',
'bounding_box', 'projection'):
assert key in ice_output
print 'thickness img size:', len(ice_output['thickness_image'])
print 'concentration img size:', len(ice_output['concentration_image'])
def test_ice_image_mid_run():
'''
Test image outputter with a model
NOTE: could it be tested with just a mover, and not a full model?
-- that gets tricky with the cache and timesteps...
'''
start_time = datetime(2015, 5, 14, 0)
model = Model(time_step=3600*24, # one day
start_time=start_time,
duration=timedelta(days=3),)
model.cache_enabled = False
model.uncertain = False
c_ice_mover = IceMover(curr_file, topology_file)
model.movers += c_ice_mover
## run the model a couple steps
step = model.step()
step = model.step()
## now add the outputter
iio = IceImageOutput(c_ice_mover)
model.outputters += iio
## and run some more:
step = model.step()
step = model.step()
## and check the output
ice_output = step['IceImageOutput']
# print ice_output['time_stamp']
# print ice_output['concentration_image'][:50] # could be really big!
# print ice_output['bounding_box']
# print ice_output['projection']
for key in ('time_stamp',
'thickness_image',
'concentration_image',
'bounding_box',
'projection'):
assert key in ice_output
def test_simple_run_with_image_output_uncertainty():
"""
pretty much all this tests is that the model will run and output images
"""
# create a place for test images (cleaning out any old ones)
images_dir = os.path.join(basedir, 'Test_images2')
if os.path.isdir(images_dir):
shutil.rmtree(images_dir)
os.mkdir(images_dir)
start_time = datetime(2012, 9, 15, 12, 0)
# the land-water map
gmap = gnome.map.MapFromBNA(testmap, refloat_halflife=6) # hours
renderer = gnome.renderer.Renderer(testmap, images_dir, size=(400,
300))
model = Model(
time_step=timedelta(minutes=15),
start_time=start_time,
duration=timedelta(hours=1),
map=gmap,
uncertain=True,
cache_enabled=False,
)
model.outputters += renderer
a_mover = SimpleMover(velocity=(1., -1., 0.))
model.movers += a_mover
N = 10 # a line of ten points
start_points = np.zeros((N, 3), dtype=np.float64)
start_points[:, 0] = np.linspace(-127.1, -126.5, N)
start_points[:, 1] = np.linspace(47.93, 48.1, N)
# print start_points
spill = SpatialRelease(start_positions=start_points,
release_time=start_time)
model.spills += spill
# model.add_spill(spill)
model.start_time = spill.release_time
# image_info = model.next_image()
model.uncertain = True
num_steps_output = 0
while True:
try:
image_info = model.step()
num_steps_output += 1
print image_info
except StopIteration:
print 'Done with the model run'
break
# there is the zeroth step, too.
assert num_steps_output == model.duration.total_seconds() \
/ model.time_step + 1
