def test_rstan_read_rdump():
a = np.array([1, 3, 5])
b = np.arange(10).reshape((-1, 2))
c = np.arange(18).reshape([2, 3, 3])
data = dict(**locals())
tempdir = tempfile.mkdtemp()
filename = os.path.join(tempdir, 'test_rdump.rdump')
misc.stan_rdump(data, filename)
d = misc.read_rdump(filename)
np.testing.assert_equal(d['a'], a)
np.testing.assert_equal(d['b'], b)
np.testing.assert_equal(d['c'], c)
def test_rstan_read_rdump(self):
a = np.array([1, 3, 5])
b = np.arange(10).reshape((-1, 2))
c = np.arange(18).reshape([2, 3, 3])
data = dict(a=a, b=b, c=c)
tempdir = tempfile.mkdtemp()
filename = os.path.join(tempdir, 'test_rdump.rdump')
misc.stan_rdump(data, filename)
d = misc.read_rdump(filename)
np.testing.assert_equal(d['a'], a)
np.testing.assert_equal(d['b'], b)
np.testing.assert_equal(d['c'], c)
def main(args, logger):
logger.info("Loading sequence depth file")
df = load_multiple_depth_file(args["depth_file_path"])
n_samples = len(args["depth_file_path"])
n_length = df["location"].max()
# Drop tuples those depth is 0 to reduce memory usage
stan_data = {}
stan_data["K"] = args["nmix"]
df = df[df["depth"] != 0]
n_iteration = len(df)
stan_data["I"] = n_iteration
stan_data["S"] = n_samples
stan_data["L"] = n_length
stan_data["SUBJECT"] = df["subject"].values
stan_data["LOCATION"] = df["location"].values
stan_data["DEPTH"] = df["depth"].values
stan_rdump(stan_data, args["output_dest"])
def test_stan_rdump():
data = OrderedDict(x=1, y=0, z=[1, 2, 3], Phi=np.array([[1, 2], [3, 4]]))
tempdir = tempfile.mkdtemp()
filename = os.path.join(tempdir, 'test_rdump.rdump')
misc.stan_rdump(data, filename)
data_recovered = misc.read_rdump(filename)
np.testing.assert_equal(data, data_recovered)
data = OrderedDict(x=True, y=np.array([True, False]))
data_expected = OrderedDict(x=1, y=np.array([1, 0]))
misc.stan_rdump(data, filename)
data_recovered = misc.read_rdump(filename)
np.testing.assert_equal(data_recovered, data_expected)
data = OrderedDict(x='foo')
np.testing.assert_raises(ValueError, misc.stan_rdump, data, filename)
data = OrderedDict(new=3)
np.testing.assert_raises(ValueError, misc.stan_rdump, data, filename)
def test_stan_rdump():
data = OrderedDict(x=1, y=0, z=[1, 2, 3], Phi=np.array([[1, 2], [3, 4]]))
tempdir = tempfile.mkdtemp()
filename = os.path.join(tempdir, 'test_rdump.rdump')
misc.stan_rdump(data, filename)
data_recovered = misc.read_rdump(filename)
np.testing.assert_equal(data, data_recovered)
data = OrderedDict(x=True, y=np.array([True, False]))
data_expected = OrderedDict(x=1, y=np.array([1, 0]))
misc.stan_rdump(data, filename)
data_recovered = misc.read_rdump(filename)
np.testing.assert_equal(data_recovered, data_expected)
data = OrderedDict(x='foo')
np.testing.assert_raises(ValueError, misc.stan_rdump, data, filename)
data = OrderedDict(new=3)
np.testing.assert_raises(ValueError, misc.stan_rdump, data, filename)