def test_2d_arrays_created_in_python():
"""
Check that transferring various arrays to R preserves columns, rows,
and shape.
"""
bools = [True, False, True, True]
strings = ['abc', 'def', 'ghi', 'jkl']
arrays = [
# next is same as: numpy.array([[1,2,3], [4,5,6]])
numpy.arange(6).reshape((2, 3), order='C'),
# next is same as: numpy.array([[1,3,5], [2,4,6]])
numpy.arange(6).reshape((2, 3), order='F'),
# next is same as: numpy.array([[True, False], [True, True]])
numpy.array(bools).reshape((2, 2), order='C'),
# next is same as: numpy.array([[True, True], [False, True]])
numpy.array(bools).reshape((2, 2), order='F'),
numpy.array(strings).reshape((2, 2), order='C'),
numpy.array(strings).reshape((2, 2), order='F'),
]
for arr in arrays:
res = conn.r.ident(arr)
assert res.shape == arr.shape
assert compareArrays(res, arr)
# assign array within R namespace and check some cols and rows:
conn.r.arr = arr
# check that 2nd row (last row) is equal:
assert compareArrays(arr[1], conn.r('arr[2,]'))
# check that 2nd column (middle col) is equal:
assert compareArrays(arr[:, 1], conn.r('arr[,2]'))
def test_2d_arrays_created_in_python():
"""
Check that transferring various arrays to R preserves columns, rows,
and shape.
"""
bools = [True, False, True, True]
strings = ['abc', 'def', 'ghi', 'jkl']
arrays = [
# next is same as: numpy.array([[1,2,3], [4,5,6]])
numpy.arange(6).reshape((2, 3), order='C'),
# next is same as: numpy.array([[1,3,5], [2,4,6]])
numpy.arange(6).reshape((2, 3), order='F'),
# next is same as: numpy.array([[True, False], [True, True]])
numpy.array(bools).reshape((2, 2), order='C'),
# next is same as: numpy.array([[True, True], [False, True]])
numpy.array(bools).reshape((2, 2), order='F'),
numpy.array(strings).reshape((2, 2), order='C'),
numpy.array(strings).reshape((2, 2), order='F'),
]
for arr in arrays:
res = conn.r.ident(arr)
assert res.shape == arr.shape
assert compareArrays(res, arr)
# assign array within R namespace and check some cols and rows:
conn.r.arr = arr
# check that 2nd row (last row) is equal:
assert compareArrays(arr[1], conn.r('arr[2,]'))
# check that 2nd column (middle col) is equal:
assert compareArrays(arr[:, 1], conn.r('arr[,2]'))
def test_eval_sequence():
# first string evaluate of R expression:
res = conn.r('seq(1, 5)')
assert compareArrays(res, numpy.array(range(1, 6)))
assert res.dtype == numpy.int32
# now make Python-style call to the R function:
assert compareArrays(conn.r.seq(1, 5), numpy.array(range(1, 6)))
def test_eval_sequence():
# first string evaluate of R expression:
res = conn.r('seq(1, 5)')
assert compareArrays(res, numpy.array(range(1, 6)))
assert res.dtype == numpy.int32
# now make Python-style call to the R function:
assert compareArrays(conn.r.seq(1, 5), numpy.array(range(1, 6)))
def test_eval_bool_arrays():
"""Test boolean arrays"""
res = conn.r('TRUE', atomicArray=True)
assert compareArrays(res, numpy.array([True]))
assert res.dtype == numpy.bool
assert compareArrays(conn.r('c(TRUE, FALSE)'), numpy.array([True, False]))
# test via call to ident function with single argument:
assert compareArrays(conn.r.ident(numpy.array([True, False, False])),
numpy.array([True, False, False]))
def test_eval_string_arrays():
"""Test for string arrays"""
assert compareArrays(conn.r("'abc'", atomicArray=True),
numpy.array(['abc']))
assert compareArrays(conn.r("c('abc', 'def')"), numpy.array(['abc',
'def']))
# test via call to ident function with single argument:
assert compareArrays(conn.r.ident(numpy.array(['abc', 'def'])),
numpy.array(['abc', 'def']))
def test_eval_polyroot():
# first string evaluate of R expression:
res = conn.r('polyroot(c(-39.141,151.469,401.045))')
exp_res = numpy.array(
[0.1762039 + 1.26217745e-29j, -0.5538897 - 1.26217745e-29j])
assert compareArrays(res, exp_res)
# now make Python-style call to the R function:
assert compareArrays(conn.r.polyroot(conn.r.c(-39.141, 151.469, 401.045)),
exp_res)
def test_eval_polyroot():
# first string evaluate of R expression:
res = conn.r('polyroot(c(-39.141,151.469,401.045))')
exp_res = numpy.array([0.1762039 + 1.26217745e-29j,
-0.5538897 - 1.26217745e-29j])
assert compareArrays(res, exp_res)
# now make Python-style call to the R function:
assert compareArrays(conn.r.polyroot(conn.r.c(-39.141, 151.469, 401.045)),
exp_res)
def test_eval_string_arrays():
"""Test for string arrays"""
assert compareArrays(conn.r("'abc'", atomicArray=True),
numpy.array(['abc']))
assert compareArrays(conn.r("c('abc', 'def')"),
numpy.array(['abc', 'def']))
# test via call to ident function with single argument:
assert compareArrays(conn.r.ident(numpy.array(['abc', 'def'])),
numpy.array(['abc', 'def']))
def test_eval_bool_arrays():
"""Test boolean arrays"""
res = conn.r('TRUE', atomicArray=True)
assert compareArrays(res, numpy.array([True]))
assert res.dtype == numpy.bool
assert compareArrays(conn.r('c(TRUE, FALSE)'), numpy.array([True, False]))
# test via call to ident function with single argument:
assert compareArrays(conn.r.ident(numpy.array([True, False, False])),
numpy.array([True, False, False]))
def test_eval_complex_arrays():
"""Test complex number arrays"""
res = conn.r("complex(real = 5.5, imaginary = 6.6)", atomicArray=True)
assert compareArrays(res, numpy.array([(5.5 + 6.6j)]))
assert isinstance(res, numpy.ndarray)
assert res.dtype == numpy.complex
# test via call to ident function with single argument:
arr = numpy.array([(5.5 + 6.6j), (-3.0 - 6j)])
assert compareArrays(conn.r.ident(arr), arr)
def test_eval_complex_arrays():
"""Test complex number arrays"""
res = conn.r("complex(real = 5.5, imaginary = 6.6)", atomicArray=True)
assert compareArrays(res, numpy.array([(5.5+6.6j)]))
assert isinstance(res, numpy.ndarray)
assert res.dtype == numpy.complex
# test via call to ident function with single argument:
arr = numpy.array([(5.5+6.6j), (-3.0-6j)])
assert compareArrays(conn.r.ident(arr), arr)
def test_eval_float_arrays():
"""Test float arrays"""
assert compareArrays(conn.r("266.5", atomicArray=True),
numpy.array([266.5]))
assert compareArrays(conn.r("c(55.2, -35.7)"), numpy.array([55.2, -35.7]))
res = conn.r("c(55.5, -35.5)")
assert isinstance(res, numpy.ndarray)
assert res.dtype == numpy.float
# test via call to ident function with single argument:
assert compareArrays(conn.r.ident(numpy.array([1.7, 5.6])),
numpy.array([1.7, 5.6]))
def test_eval_float_arrays():
"""Test float arrays"""
assert compareArrays(conn.r("266.5", atomicArray=True),
numpy.array([266.5]))
assert compareArrays(conn.r("c(55.2, -35.7)"), numpy.array([55.2, -35.7]))
res = conn.r("c(55.5, -35.5)")
assert isinstance(res, numpy.ndarray)
assert res.dtype == numpy.float
# test via call to ident function with single argument:
assert compareArrays(conn.r.ident(numpy.array([1.7, 5.6])),
numpy.array([1.7, 5.6]))
def test_eval_integer_arrays():
"""
Test integer arrays. The result from R is actually always a numpy
float array
"""
assert compareArrays(conn.r("266", atomicArray=True), numpy.array([266]))
assert compareArrays(conn.r("c(55, -35)"), numpy.array([55.0, -35.0]))
res = conn.r("c(55, -35)")
assert isinstance(res, numpy.ndarray)
assert res.dtype == numpy.float
#### Create real integer arrays in R:
res = conn.r('as.integer(c(1, 5))')
assert compareArrays(res, numpy.array([1, 5]))
assert res.dtype in (numpy.int, numpy.int32)
# test via call to ident function with single argument:
assert compareArrays(conn.r.ident(numpy.array([1, 5])),
numpy.array([1, 5]))
def test_eval_integer_arrays():
"""
Test integer arrays. The result from R is actually always a numpy
float array
"""
assert compareArrays(conn.r("266", atomicArray=True), numpy.array([266]))
assert compareArrays(conn.r("c(55, -35)"), numpy.array([55.0, -35.0]))
res = conn.r("c(55, -35)")
assert isinstance(res, numpy.ndarray)
assert res.dtype == numpy.float
#### Create real integer arrays in R:
res = conn.r('as.integer(c(1, 5))')
assert compareArrays(res, numpy.array([1, 5]))
assert res.dtype in (numpy.int, numpy.int32)
# test via call to ident function with single argument:
assert compareArrays(conn.r.ident(numpy.array([1, 5])), numpy.array([1,
5]))
def test_2d_numeric_array_created_in_R():
"""
Create an array in R, transfer it to python, and check that columns,
rows, and shape are preserved.
Note: Arrays in R are always in Fortran order, i.e. first index moves
fastest.
The array in R looks like:
[,1] [,2] [,3]
[1,] 1 3 5
[2,] 2 4 6
"""
arr = conn.r('arr = array(1:6, dim=c(2, 3))')
assert compareArrays(conn.r.arr, arr)
# check that 2nd row (last row) is equal:
assert len(arr[1]) == len(conn.r('arr[2,]')) == 3
assert compareArrays(arr[1], conn.r('arr[2,]'))
# check that 2nd column (middle col) is equal:
assert len(arr[:, 1]) == len(conn.r('arr[,2]')) == 2
assert compareArrays(arr[:, 1], conn.r('arr[,2]'))
def test_2d_numeric_array_created_in_R():
"""
Create an array in R, transfer it to python, and check that columns,
rows, and shape are preserved.
Note: Arrays in R are always in Fortran order, i.e. first index moves
fastest.
The array in R looks like:
[,1] [,2] [,3]
[1,] 1 3 5
[2,] 2 4 6
"""
arr = conn.r('arr = array(1:6, dim=c(2, 3))')
assert compareArrays(conn.r.arr, arr)
# check that 2nd row (last row) is equal:
assert len(arr[1]) == len(conn.r('arr[2,]')) == 3
assert compareArrays(arr[1], conn.r('arr[2,]'))
# check that 2nd column (middle col) is equal:
assert len(arr[:, 1]) == len(conn.r('arr[,2]')) == 2
assert compareArrays(arr[:, 1], conn.r('arr[,2]'))
def test_eval_very_convoluted_function_result():
"""
The result of this call is a highly nested data structure.
Have fun on evaluation it!
"""
res = conn.r('x<-1:20; y<-x*2; lm(y~x)')
assert res.__class__ == TaggedList
# check which tags the TaggedList has:
assert res.keys == ['coefficients', 'residuals', 'effects', 'rank',
'fitted.values', 'assign', 'qr', 'df.residual',
'xlevels', 'call', 'terms', 'model']
assert compareArrays(res['coefficients'],
TaggedArray.new(numpy.array([-0., 2.]),
['(Intercept)', 'x']))
def test_eval_very_convoluted_function_result():
"""
The result of this call is a highly nested data structure.
Have fun on evaluation it!
"""
res = conn.r('x<-1:20; y<-x*2; lm(y~x)')
assert res.__class__ == TaggedList
# check which tags the TaggedList has:
assert res.keys == [
'coefficients', 'residuals', 'effects', 'rank', 'fitted.values',
'assign', 'qr', 'df.residual', 'xlevels', 'call', 'terms', 'model'
]
assert compareArrays(
res['coefficients'],
TaggedArray.new(numpy.array([-0., 2.]), ['(Intercept)', 'x']))
def test_eval_unicode_arrays():
"""
Test for unicode arrays. The ident function should return the
same array, just not as unicode
"""
try:
u1 = eval("u'abc'")
u2 = eval("u'def'")
except SyntaxError:
# Python 3 below 3.3 does not accept the u'' operator,
# just skip this test!
return
# test via call to ident function with single argument:
assert conn.r.ident(numpy.array([u1])) == 'abc'
assert compareArrays(conn.r.ident(numpy.array([u1, u2])),
numpy.array(['abc', 'def']))
def test_eval_unicode_arrays():
"""
Test for unicode arrays. The ident function should return the
same array, just not as unicode
"""
try:
u1 = eval("u'abc'")
u2 = eval("u'def'")
except SyntaxError:
# Python 3 below 3.3 does not accept the u'' operator,
# just skip this test!
return
# test via call to ident function with single argument:
assert conn.r.ident(numpy.array([u1])) == 'abc'
assert compareArrays(conn.r.ident(numpy.array([u1, u2])),
numpy.array(['abc', 'def']))
def test_empty_boolean_array():
"""Check that zero-length boolean ('logical') array is returned fine"""
conn.r('empty_bool_arr = as.logical(c())')
assert compareArrays(conn.r.empty_bool_arr, numpy.array([], dtype=bool))
def test_tagged_array():
res = conn.r('c(a=1.,b=2.,c=3.)')
exp_res = TaggedArray.new(numpy.array([1., 2., 3.]), ['a', 'b', 'c'])
assert compareArrays(res, exp_res)
assert res.keys() == exp_res.keys() # compare the tags of both arrays
def test_tagged_array():
res = conn.r('c(a=1.,b=2.,c=3.)')
exp_res = TaggedArray.new(numpy.array([1., 2., 3.]), ['a', 'b', 'c'])
assert compareArrays(res, exp_res)
assert res.keys() == exp_res.keys() # compare the tags of both arrays
def test_empty_boolean_array():
"""Check that zero-length boolean ('logical') array is returned fine"""
conn.r('empty_bool_arr = as.logical(c())')
assert compareArrays(conn.r.empty_bool_arr, numpy.array([], dtype=bool))
