def to_H2OFrame(ip, port):
# Connect to a pre-existing cluster
h2o.init(ip, port)
# TODO: negative testing
## 1. list
# a. single row
python_obj = [1, "a", 2.5, "bcd", 0]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=5)
# b. single column
python_obj = [[1], [2], [3.7], [8], [9]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = [[6, 7, 8, 9, 10], [1, 2, 3, 4, 5], [3, 2, 2, 2, 2]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
python_obj = [["a", "b"], ["c", "d"]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=2, cols=2)
# d. jagged
python_obj = [[6, 7, 8, 9, 10], [1, 2, 3, 4], [3, 2, 2]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
#h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
## 2. tuple
# a. single row
python_obj = (1, "a", 2.5, "bcd", 0)
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=5)
# b. single column
python_obj = ((1, ), (2, ), (3.7, ), (8, ), (9, ))
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = ((6, 7, 8, 9, 10), (1, 2, 3, 4, 5), (3, 2, 2, 2, 2))
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# d. jagged
python_obj = ((6, 7, 8, 9, 10), (1, 2, 3, 4), (3, 2, 2))
the_frame = h2o.H2OFrame(python_obj=python_obj)
#h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
## 3. list-tuple mixed
# a. single column
python_obj = ((1, ), [2], (3.7, ), [8], (9, ))
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# b. single column
python_obj = [(1, ), [2], (3.7, ), [8], (9, )]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = ([6, 7, 8, 9, 10], (1, 2, 3, 4, 5), [3, 2, 2, 2, 2])
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# d. multiple rows, columns
python_obj = [(6, 7, 8, 9, 10), [1, 2, 3, 4, 5], (3, 2, 2, 2, 2)]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# e. jagged
python_obj = [(6, 7, 8, 9, 10), [1, 2, 3, 4], (3, 2, 2)]
the_frame = h2o.H2OFrame(python_obj=python_obj)
# h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
# f. jagged
python_obj = ((6, 7, 8, 9, 10), [1, 2, 3, 4], (3, 2, 2))
the_frame = h2o.H2OFrame(python_obj=python_obj)
def to_H2OFrame(ip,port):
# Connect to a pre-existing cluster
h2o.init(ip,port)
# TODO: negative testing
## 1. list
# a. single row
python_obj = [1, "a", 2.5, "bcd", 0]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=5)
# b. single column
python_obj = [[1], [2], [3.7], [8], [9]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = [[6,7,8,9,10], [1,2,3,4,5], [3,2,2,2,2]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
python_obj = [["a", "b"], ["c", "d"]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=2, cols=2)
# d. jagged
python_obj = [[6,7,8,9,10], [1,2,3,4], [3,2,2]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
#h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
## 2. tuple
# a. single row
python_obj = (1, "a", 2.5, "bcd", 0)
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=5)
# b. single column
python_obj = ((1,), (2,), (3.7,), (8,), (9,))
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = ((6,7,8,9,10), (1,2,3,4,5), (3,2,2,2,2))
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# d. jagged
python_obj = ((6,7,8,9,10), (1,2,3,4), (3,2,2))
the_frame = h2o.H2OFrame(python_obj=python_obj)
#h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
## 3. list-tuple mixed
# a. single column
python_obj = ((1,), [2], (3.7,), [8], (9,))
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# b. single column
python_obj = [(1,), [2], (3.7,), [8], (9,)]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = ([6,7,8,9,10], (1,2,3,4,5), [3,2,2,2,2])
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# d. multiple rows, columns
python_obj = [(6,7,8,9,10), [1,2,3,4,5], (3,2,2,2,2)]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# e. jagged
python_obj = [(6,7,8,9,10), [1,2,3,4], (3,2,2)]
the_frame = h2o.H2OFrame(python_obj=python_obj)
# h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
# f. jagged
python_obj = ((6,7,8,9,10), [1,2,3,4], (3,2,2))
the_frame = h2o.H2OFrame(python_obj=python_obj)
def to_H2OFrame(ip,port):
# Connect to a pre-existing cluster
h2o.init(ip,port)
# TODO: negative testing
## 1. list
# a. single row
python_obj = [1, "a", 2.5, "bcd", 0]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=5)
# b. single column
python_obj = [[1], [2], [3.7], [8], [9]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = [[6,7,8,9,10], [1,2,3,4,5], [3,2,2,2,2]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# d. jagged
python_obj = [[6,7,8,9,10], [1,2,3,4], [3,2,2]]
the_frame = h2o.H2OFrame(python_obj=python_obj)
#h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
## 2. tuple
# a. single row
python_obj = (1, "a", 2.5, "bcd", 0)
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=5)
# b. single column
python_obj = ((1,), (2,), (3.7,), (8,), (9,))
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = ((6,7,8,9,10), (1,2,3,4,5), (3,2,2,2,2))
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# d. jagged
python_obj = ((6,7,8,9,10), (1,2,3,4), (3,2,2))
the_frame = h2o.H2OFrame(python_obj=python_obj)
#h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
## 3. list-tuple mixed
# a. single column
python_obj = ((1,), [2], (3.7,), [8], (9,))
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# b. single column
python_obj = [(1,), [2], (3.7,), [8], (9,)]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = ([6,7,8,9,10], (1,2,3,4,5), [3,2,2,2,2])
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# d. multiple rows, columns
python_obj = [(6,7,8,9,10), [1,2,3,4,5], (3,2,2,2,2)]
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# e. jagged
python_obj = [(6,7,8,9,10), [1,2,3,4], (3,2,2)]
the_frame = h2o.H2OFrame(python_obj=python_obj)
# h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
# f. jagged
python_obj = ((6,7,8,9,10), [1,2,3,4], (3,2,2))
the_frame = h2o.H2OFrame(python_obj=python_obj)
# h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5) TODO
## 4. dictionary
# a. single row
python_obj = {"a":1, "b":"a", "c":2.5, "d":"bcd", "e":0}
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=5)
assert set(the_frame.names()) == set(python_obj.keys()), "H2OFrame header is hosed. Got {0}, but should have got " \
"{1}".format(the_frame.names(), python_obj.keys())
python_obj = {"a":[1], "b":["a"], "c":[2.5], "d":["bcd"], "e":[0]}
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=5)
assert set(the_frame.names()) == set(python_obj.keys()), "H2OFrame header is hosed. Got {0}, but should have got " \
"{1}".format(the_frame.names(), python_obj.keys())
# b. single column
python_obj = {"foo":(1,2,3.7,8,9)}
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
assert set(the_frame.names()) == set(python_obj.keys()), "H2OFrame header is hosed. Got {0}, but should have got " \
"{1}".format(the_frame.names(), python_obj.keys())
# c. multiple rows, columns
python_obj = {"foo":[6,7,8,9,10], "bar":(1,2,3,4,5), "baz":(3,2,2,2,2)}
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=3)
assert set(the_frame.names()) == set(python_obj.keys()), "H2OFrame header is hosed. Got {0}, but should have got " \
"{1}".format(the_frame.names(), python_obj.keys())
# d. jagged
python_obj = {"foo":(6,7), "bar":(1,2,3,4), "baz":(3,2,2)}
the_frame = h2o.H2OFrame(python_obj=python_obj)
# check_dims_values_jagged() TODO
assert set(the_frame.names()) == set(python_obj.keys()), "H2OFrame header is hosed. Got {0}, but should have got " \
"{1}".format(the_frame.names(), python_obj.keys())
## 5. numpy.ndarray
# a. single row
python_obj = np.array([1, "a", 2.5, "bcd", 0])
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=5)
# b. single column
python_obj = np.array([[1], [2], [3.7], [8], [9]])
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = np.array([[6,7,8,9,10], [1,2,3,4,5], [3,2,2,2,2]])
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=3, cols=5)
# d. jagged
python_obj = np.array([[6,7,8,9,10], [1,2,3,4], [3,2,2]])
the_frame = h2o.H2OFrame(python_obj=python_obj)
# check_dims_values_jagged() TODO
## 6. pandas.DataFrame
# a. single row
python_obj = pd.DataFrame({'foo' : pd.Series([1]), 'bar' : pd.Series([6]), 'baz' : pd.Series(["a"]) })
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=1, cols=3)
# b. single column
python_obj = pd.DataFrame({'foo' : pd.Series([1, 2, 3, 7.8, 9])})
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=1)
# c. multiple rows, columns
python_obj = pd.DataFrame({'foo' : pd.Series([6,7,8,9,10]), 'bar' : pd.Series([1,2,3,4,5]),
'baz' : pd.Series([3,2,2,2,2])})
the_frame = h2o.H2OFrame(python_obj=python_obj)
h2o.check_dims_values(python_obj, the_frame, rows=5, cols=3)
# d. jagged
python_obj = pd.DataFrame({'foo' : pd.Series([6,7,8]), 'bar' : pd.Series([1,2,3,4,5]), 'baz' : pd.Series([3,2,2,2])})
the_frame = h2o.H2OFrame(python_obj=python_obj)
