def test_get_empty_result(base):
c = Castra(path=base, template=A)
c.extend(A)
df = c[100:200]
assert (df.columns == A.columns).all()
def test_get_empty_result(base):
c = Castra(path=base, template=A)
c.extend(A)
df = c[100:200]
assert (df.columns == A.columns).all()
def test_pickle_Castra():
path = tempfile.mkdtemp(prefix='castra-')
c = Castra(path=path, template=A)
c.extend(A)
c.extend(B)
dumped = pickle.dumps(c)
undumped = pickle.loads(dumped)
tm.assert_frame_equal(pd.concat([A, B]), undumped[:])
def test_pickle_Castra():
path = tempfile.mkdtemp(prefix='castra-')
c = Castra(path=path, template=A)
c.extend(A)
c.extend(B)
dumped = pickle.dumps(c)
undumped = pickle.loads(dumped)
tm.assert_frame_equal(pd.concat([A, B]), undumped[:])
def test_reload():
path = tempfile.mkdtemp(prefix='castra-')
try:
c = Castra(template=A, path=path)
c.extend(A)
d = Castra(path=path)
assert c.columns == d.columns
assert (c.partitions == d.partitions).all()
assert c.minimum == d.minimum
finally:
shutil.rmtree(path)
def test_Castra():
c = Castra(template=A)
c.extend(A)
c.extend(B)
assert c.columns == ['x', 'y']
tm.assert_frame_equal(c[0:100], pd.concat([A, B]))
tm.assert_frame_equal(c[:5], A)
tm.assert_frame_equal(c[5:], B)
tm.assert_frame_equal(c[2:5], A[1:])
tm.assert_frame_equal(c[2:15], pd.concat([A[1:], B[:1]]))
def test_reload():
path = tempfile.mkdtemp(prefix='castra-')
try:
c = Castra(template=A, path=path)
c.extend(A)
d = Castra(path=path)
assert c.columns == d.columns
assert (c.partitions == d.partitions).all()
assert c.minimum == d.minimum
finally:
shutil.rmtree(path)
def test_Castra():
c = Castra(template=A)
c.extend(A)
c.extend(B)
assert c.columns == ['x', 'y']
tm.assert_frame_equal(c[0:100], pd.concat([A, B]))
tm.assert_frame_equal(c[:5], A)
tm.assert_frame_equal(c[5:], B)
tm.assert_frame_equal(c[2:5], A[1:])
tm.assert_frame_equal(c[2:15], pd.concat([A[1:], B[:1]]))
def test_readonly():
path = tempfile.mkdtemp(prefix='castra-')
try:
c = Castra(path=path, template=A)
c.extend(A)
d = Castra(path=path, readonly=True)
with pytest.raises(IOError):
d.extend(B)
with pytest.raises(IOError):
d.extend_sequence([B])
with pytest.raises(IOError):
d.flush()
with pytest.raises(IOError):
d.drop()
with pytest.raises(IOError):
d.save_partitions()
with pytest.raises(IOError):
d.flush_meta()
assert c.columns == d.columns
assert (c.partitions == d.partitions).all()
assert c.minimum == d.minimum
finally:
shutil.rmtree(path)
def test_readonly():
path = tempfile.mkdtemp(prefix='castra-')
try:
c = Castra(path=path, template=A)
c.extend(A)
d = Castra(path=path, readonly=True)
with pytest.raises(IOError):
d.extend(B)
with pytest.raises(IOError):
d.extend_sequence([B])
with pytest.raises(IOError):
d.flush()
with pytest.raises(IOError):
d.drop()
with pytest.raises(IOError):
d.save_partitions()
with pytest.raises(IOError):
d.flush_meta()
assert c.columns == d.columns
assert (c.partitions == d.partitions).all()
assert c.minimum == d.minimum
finally:
shutil.rmtree(path)
def floats_to_castra(input_dir, output_fname, progress=False, **kwargs):
"""Convert MITgcm float data to pands hdf format.
Paramters
---------
input_dir : path
Where to find the MITgcm output data
output_fname : path
Filename of the hdf data store
kwargs :
Extra keyword arguments to pass to floater.input_formats.MITgcmFloatData
"""
import pandas as pd
from castra import Castra
output_fname = _maybe_add_suffix(output_fname, '.castra')
mfd = input.MITgcmFloatData(input_dir, **kwargs)
c = None
for block in mfd.generator(progress=progress, return_full_block=True):
df = pd.DataFrame.from_records(block)
if not c:
c = Castra(output_fname, template=df)
c.extend(df)
def test_get_slice(base):
c = Castra(path=base, template=A)
c.extend(A)
tm.assert_frame_equal(c[:], c[:, :])
tm.assert_frame_equal(c[:, 1:], c[:][['y']])
def test_get_slice(base):
c = Castra(path=base, template=A)
c.extend(A)
tm.assert_frame_equal(c[:], c[:, :])
tm.assert_frame_equal(c[:, 1:], c[:][['y']])
