def frame_math_ops():
sin_cos_tan_atan_sinh_cosh_tanh_asinh_data = [[random.uniform(-10,10) for r in range(10)] for c in range(10)]
asin_acos_atanh_data = [[random.uniform(-1,1) for r in range(10)] for c in range(10)]
acosh_data = [[random.uniform(1,10) for r in range(10)] for c in range(10)]
abs_data = [[random.uniform(-100000,0) for r in range(10)] for c in range(10)]
signif_data = [[0.0000123456, 1], [2, 3]]
h2o_data1 = h2o.H2OFrame(zip(*sin_cos_tan_atan_sinh_cosh_tanh_asinh_data))
h2o_data2 = h2o.H2OFrame(asin_acos_atanh_data)
h2o_data3 = h2o.H2OFrame(acosh_data)
h2o_data4 = h2o.H2OFrame(abs_data)
h2o_data5 = h2o.H2OFrame(signif_data)
np_data1 = np.array(sin_cos_tan_atan_sinh_cosh_tanh_asinh_data)
np_data2 = np.array(asin_acos_atanh_data)
np_data3 = np.array(acosh_data)
np_data4 = np.array(abs_data)
for d in range(1,6):
h2o_signif = h2o_data5.signif(digits=d)
h2o_round = h2o_data5.round(digits=d+4)
s = h2o_signif[0,0]
r = h2o_round[0,0]
assert s == r, "Expected these to be equal, but signif: {0}, round: {1}".format(s, r)
h2o_transposed = h2o_data1[0:5].transpose()
r, c = h2o_transposed.dim
assert r == 5 and c == 10, "Expected 5 rows and 10 columns, but got {0} rows and {1} columns".format(r,c)
pyunit_utils.np_comparison_check(h2o_transposed, np.transpose(np_data1[:,0:5]), 10)
pyunit_utils.np_comparison_check(h2o_data1.cos(), np.cos(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.sin(), np.sin(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.tan(), np.tan(np_data1), 10)
def expr_reducers():
data = [[random.uniform(-10000, 10000) for r in range(10)] for c in range(10)]
h2o_data_1 = h2o.H2OFrame(data)
np_data = np.array(data)
row, col = h2o_data_1.dim
h2o_data = h2o_data_1 + 2
np_data = np_data + 2
def check_values(h2o_data, numpy_data):
success = True
for i in range(10):
r = random.randint(0, row - 1)
c = random.randint(0, col - 1)
h2o_val = h2o_data[r, c]
num_val = numpy_data[r, c]
if not abs(h2o_val - num_val) < 1e-06:
success = False
print("check unsuccessful! h2o computed {0} and numpy computed {1}".format(h2o_val, num_val))
return success
h2o_val = h2o_data.min()
num_val = np.min(np_data)
assert abs(h2o_val - num_val) < 1e-06, (
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal min values between h2o and "
"numpy".format(h2o_val, num_val)
)
h2o_val = h2o_data.max()
num_val = np.max(np_data)
assert abs(h2o_val - num_val) < 1e-06, (
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal max values between h2o and "
"numpy".format(h2o_val, num_val)
)
h2o_val = h2o_data.sum()
num_val = np.sum(np_data)
assert abs(h2o_val - num_val) < 1e-06, (
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal sum values between h2o and "
"numpy".format(h2o_val, num_val)
)
pyunit_utils.np_comparison_check(
h2o_data.var(), np.cov(np_data, rowvar=0, ddof=1), 10
), "expected equal var values between h2o and numpy"
def expr_reducers():
data = [[random.uniform(-10000, 10000) for r in range(10)]
for c in range(10)]
h2o_data_1 = h2o.H2OFrame(data)
np_data = np.array(data)
row, col = h2o_data_1.dim
h2o_data = h2o_data_1 + 2
np_data = np_data + 2
def check_values(h2o_data, numpy_data):
success = True
for i in range(10):
r = random.randint(0, row - 1)
c = random.randint(0, col - 1)
h2o_val = h2o_data[r, c]
num_val = numpy_data[r, c]
if not abs(h2o_val - num_val) < 1e-06:
success = False
print(
"check unsuccessful! h2o computed {0} and numpy computed {1}"
.format(h2o_val, num_val))
return success
h2o_val = h2o_data.min()
num_val = np.min(np_data)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal min values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o_data.max()
num_val = np.max(np_data)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal max values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o_data.sum()
num_val = np.sum(np_data)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal sum values between h2o and " \
"numpy".format(h2o_val,num_val)
pyunit_utils.np_comparison_check(h2o_data.var(), np.cov(np_data, rowvar=0, ddof=1), 10), \
"expected equal var values between h2o and numpy"
def frame_math_ops():
sin_cos_tan_atan_sinh_cosh_tanh_asinh_data = [
[random.uniform(-10, 10) for r in range(10)] for c in range(10)
]
asin_acos_atanh_data = [[random.uniform(-1, 1) for r in range(10)]
for c in range(10)]
acosh_data = [[random.uniform(1, 10) for r in range(10)]
for c in range(10)]
abs_data = [[random.uniform(-100000, 0) for r in range(10)]
for c in range(10)]
signif_data = [[0.0000123456, 1], [2, 3]]
h2o_data1 = h2o.H2OFrame(python_obj=zip(
*sin_cos_tan_atan_sinh_cosh_tanh_asinh_data))
h2o_data2 = h2o.H2OFrame(python_obj=asin_acos_atanh_data)
h2o_data3 = h2o.H2OFrame(python_obj=acosh_data)
h2o_data4 = h2o.H2OFrame(python_obj=abs_data)
h2o_data5 = h2o.H2OFrame(python_obj=signif_data)
np_data1 = np.array(sin_cos_tan_atan_sinh_cosh_tanh_asinh_data)
np_data2 = np.array(asin_acos_atanh_data)
np_data3 = np.array(acosh_data)
np_data4 = np.array(abs_data)
for d in range(1, 6):
h2o_signif = h2o_data5.signif(digits=d)
h2o_round = h2o_data5.round(digits=d + 4)
s = h2o_signif[0, 0]
r = h2o_round[0, 0]
assert s == r, "Expected these to be equal, but signif: {0}, round: {1}".format(
s, r)
h2o_transposed = h2o_data1[0:5].transpose()
r, c = h2o_transposed.dim
assert r == 5 and c == 10, "Expected 5 rows and 10 columns, but got {0} rows and {1} columns".format(
r, c)
pyunit_utils.np_comparison_check(h2o_transposed,
np.transpose(np_data1[:, 0:5]), 10)
pyunit_utils.np_comparison_check(h2o_data1.cos(), np.cos(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.sin(), np.sin(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.tan(), np.tan(np_data1), 10)
def expr_math_ops():
sin_cos_tan_atan_sinh_cosh_tanh_asinh_data = [[random.uniform(-10,10) for r in range(10)] for c in range(10)]
asin_acos_atanh_data = [[random.uniform(-1,1) for r in range(10)] for c in range(10)]
acosh_data = [[random.uniform(1,10) for r in range(10)] for c in range(10)]
abs_data = [[random.uniform(-100000,0) for r in range(10)] for c in range(10)]
h2o_data1_1 = h2o.H2OFrame(python_obj=sin_cos_tan_atan_sinh_cosh_tanh_asinh_data)
h2o_data2_1 = h2o.H2OFrame(python_obj=asin_acos_atanh_data)
h2o_data3_1 = h2o.H2OFrame(python_obj=acosh_data)
h2o_data4_1 = h2o.H2OFrame(python_obj=abs_data)
np_data1 = np.array(sin_cos_tan_atan_sinh_cosh_tanh_asinh_data)
np_data2 = np.array(asin_acos_atanh_data)
np_data3 = np.array(acosh_data)
np_data4 = np.array(abs_data)
h2o_data1 = h2o_data1_1 + 2
h2o_data2 = h2o_data2_1 / 1.01
h2o_data3 = h2o_data3_1 * 1.5
h2o_data4 = h2o_data4_1 - 1.5
np_data1 = np_data1 + 2
np_data2 = np_data2 / 1.01
np_data3 = np_data3 * 1.5
np_data4 = np_data4 - 1.5
pyunit_utils.np_comparison_check(h2o_data1.cos(), np.cos(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.sin(), np.sin(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.tan(), np.tan(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data2.acos(), np.arccos(np_data2), 10)
pyunit_utils.np_comparison_check(h2o_data2.asin(), np.arcsin(np_data2), 10)
pyunit_utils.np_comparison_check(h2o_data1.atan(), np.arctan(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.cosh(), np.cosh(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.sinh(), np.sinh(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.tanh(), np.tanh(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data3.acosh(), np.arccosh(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data1.asinh(), np.arcsinh(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data2.atanh(), np.arctanh(np_data2), 10)
pyunit_utils.np_comparison_check((h2o_data2/math.pi).cospi(), np.cos(np_data2), 10)
pyunit_utils.np_comparison_check((h2o_data2/math.pi).sinpi(), np.sin(np_data2), 10)
pyunit_utils.np_comparison_check((h2o_data2/math.pi).tanpi(), np.tan(np_data2), 10)
pyunit_utils.np_comparison_check(h2o_data4.abs(), np.fabs(np_data4), 10)
pyunit_utils.np_comparison_check(h2o_data2.sign(), np.sign(np_data2), 10)
pyunit_utils.np_comparison_check(h2o_data3.sqrt(), np.sqrt(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.trunc(), np.trunc(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.ceil(), np.ceil(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.floor(), np.floor(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.log(), np.log(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.log10(), np.log10(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.log1p(), np.log1p(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.log2(), np.log2(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.exp(), np.exp(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.expm1(), np.expm1(np_data3), 10)
h2o_val = h2o_data3.gamma()[5,5]
num_val = math.gamma(h2o_data3[5,5])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal gamma values between h2o and " \
"math".format(h2o_val,num_val)
h2o_val = h2o_data3.lgamma()[5,5]
num_val = math.lgamma(h2o_data3[5,5])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal lgamma values between h2o and " \
"math".\
format(h2o_val,num_val)
h2o_val = h2o_data3.digamma()[5,5]
num_val = scipy.special.polygamma(0,h2o_data3[5,5])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal digamma values between h2o and " \
"math"\
.format(h2o_val,num_val)
h2o_val = h2o_data3.trigamma()[5,5]
num_val = float(scipy.special.polygamma(1,h2o_data3[5,5]))
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal trigamma values between h2o and " \
"math".format(h2o_val,num_val)
def op_precedence():
# Connect to a pre-existing cluster
a = [[random.uniform(-100,100) for r in range(10)] for c in range(10)]
b = [[random.uniform(-100,100) for r in range(10)] for c in range(10)]
c = [[random.uniform(-100,100) for r in range(10)] for c in range(10)]
A = h2o.H2OFrame(python_obj=a)
B = h2o.H2OFrame(python_obj=b)
C = h2o.H2OFrame(python_obj=c)
np_A = np.array(a)
np_B = np.array(b)
np_C = np.array(c)
s1 = np_A + np_B * np_C
s2 = np_A - np_B - np_C
s3 = np_A ** 1 ** 2
s4 = np.logical_and(np_A == np_B, np_C)
s5 = np_A == np_B + np_C
s6 = np.logical_and(np.logical_or(np_A, np_B), np_C)
print "Check A + B * C"
S1 = A + B * C
pyunit_utils.np_comparison_check(S1, s1, 10)
print "Check A - B - C"
S2 = A - B - C
pyunit_utils.np_comparison_check(S2, s2, 10)
print "Check A ^ 2 ^ 3"
S3 = A ** 1 ** 2
pyunit_utils.np_comparison_check(S3, s3, 10)
print "Check A == B & C"
S4 = A == B & C
pyunit_utils.np_comparison_check(S4, s4, 10)
print "Check A == B + C"
S5 = A == B + C
pyunit_utils.np_comparison_check(S5, s5, 10)
print "Check A | B & C"
S6 = A | B & C
pyunit_utils.np_comparison_check(S6, s6, 10)
def vec_math_ops():
sin_cos_tan_atan_sinh_cosh_tanh_asinh_data = [[random.uniform(-10,10) for r in range(10)] for c in range(10)]
asin_acos_atanh_data = [[random.uniform(-1,1) for r in range(10)] for c in range(10)]
acosh_data = [[random.uniform(1,10) for r in range(10)] for c in range(10)]
abs_data = [[random.uniform(-100000,0) for r in range(10)] for c in range(10)]
zero_one_data = [random.randint(0,1) for c in range(10)]
zero_one_data = [zero_one_data, zero_one_data]
h2o_data1 = h2o.H2OFrame(python_obj=sin_cos_tan_atan_sinh_cosh_tanh_asinh_data)
h2o_data2 = h2o.H2OFrame(python_obj=asin_acos_atanh_data)
h2o_data3 = h2o.H2OFrame(python_obj=acosh_data)
h2o_data4 = h2o.H2OFrame(python_obj=abs_data)
h2o_data5 = h2o.H2OFrame(python_obj=zero_one_data)
np_data1 = np.array(sin_cos_tan_atan_sinh_cosh_tanh_asinh_data)
np_data2 = np.array(asin_acos_atanh_data)
np_data3 = np.array(acosh_data)
np_data4 = np.array(abs_data)
np_data5 = np.array(zero_one_data)
row, col = h2o_data1.dim
c = random.randint(0,col-1)
for d in range(1,6):
h2o_signif = h2o_data5[c].signif(digits=d)
h2o_round = h2o_data5[c].round(digits=d+4)
s = h2o_signif[0]
r = h2o_round[0]
assert s == r, "Expected these to be equal, but signif: {0}, round: {1}".format(s, r)
h2o_transposed = h2o_data1[c].transpose()
x, y = h2o_transposed.dim
assert x == 1 and y == 10, "Expected 1 row and 10 columns, but got {0} rows and {1} columns".format(x,y)
pyunit_utils.np_comparison_check(h2o_data1[:,c].cos(), np.cos(np_data1[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[:,c].sin(), np.sin(np_data1[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[:,c].tan(), np.tan(np_data1[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data2[:,c].acos(), np.arccos(np_data2[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data2[:,c].asin(), np.arcsin(np_data2[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[:,c].atan(), np.arctan(np_data1[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[:,c].cosh(), np.cosh(np_data1[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[c].sinh(), np.sinh(np_data1[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[c].tanh(), np.tanh(np_data1[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data3[c].acosh(), np.arccosh(np_data3[:,c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[c].asinh(), np.arcsinh(np_data1[:,c]), 10)
h2o_val = h2o_data3[c].gamma()[5,:]._scalar()
num_val = math.gamma(h2o_data3[5,c])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal gamma values between h2o and" \
"math".format(h2o_val,num_val)
h2o_val = h2o_data3[c].lgamma()[5,:]._scalar()
num_val = math.lgamma(h2o_data3[5,c])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal lgamma values between h2o and " \
"math".format(h2o_val,num_val)
h2o_val = h2o_data3[c].digamma()[5,:]._scalar()
num_val = scipy.special.polygamma(0,h2o_data3[5,c])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal digamma values between h2o and " \
"math".format(h2o_val,num_val)
h2o_val = h2o_data3[c].trigamma()[5,:]._scalar()
num_val = scipy.special.polygamma(1,h2o_data3[5,c])
assert abs(h2o_val - float(num_val)) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal trigamma values between h2o and " \
"math".format(h2o_val,num_val)
def op_precedence():
# Connect to a pre-existing cluster
a = [[random.uniform(-100,100) for r in range(10)] for c in range(10)]
b = [[random.uniform(-100,100) for r in range(10)] for c in range(10)]
c = [[random.uniform(-100,100) for r in range(10)] for c in range(10)]
A = h2o.H2OFrame(zip(*a))
B = h2o.H2OFrame(zip(*b))
C = h2o.H2OFrame(zip(*c))
np_A = np.array(a)
np_B = np.array(b)
np_C = np.array(c)
s1 = np_A + np_B * np_C
s2 = np_A - np_B - np_C
s3 = np_A ** 1 ** 2
s4 = np.logical_and(np_A == np_B, np_C)
s5 = np_A == np_B + np_C
s6 = np.logical_and(np.logical_or(np_A, np_B), np_C)
print "Check A + B * C"
S1 = A + B * C
pyunit_utils.np_comparison_check(S1, s1, 10)
print "Check A - B - C"
S2 = A - B - C
pyunit_utils.np_comparison_check(S2, s2, 10)
print "Check A ^ 2 ^ 3"
S3 = A ** 1 ** 2
pyunit_utils.np_comparison_check(S3, s3, 10)
print "Check A == B & C"
S4 = A == B & C
pyunit_utils.np_comparison_check(S4, s4, 10)
print "Check A == B + C"
S5 = A == B + C
pyunit_utils.np_comparison_check(S5, s5, 10)
print "Check A | B & C"
S6 = A | B & C
pyunit_utils.np_comparison_check(S6, s6, 10)
def vec_math_ops():
sin_cos_tan_atan_sinh_cosh_tanh_asinh_data = [
[random.uniform(-10, 10) for r in range(10)] for c in range(10)
]
asin_acos_atanh_data = [[random.uniform(-1, 1) for r in range(10)]
for c in range(10)]
acosh_data = [[random.uniform(1, 10) for r in range(10)]
for c in range(10)]
abs_data = [[random.uniform(-100000, 0) for r in range(10)]
for c in range(10)]
zero_one_data = [random.randint(0, 1) for c in range(10)]
zero_one_data = [zero_one_data, zero_one_data]
h2o_data1 = h2o.H2OFrame(python_obj=zip(
*sin_cos_tan_atan_sinh_cosh_tanh_asinh_data))
h2o_data2 = h2o.H2OFrame(python_obj=zip(*asin_acos_atanh_data))
h2o_data3 = h2o.H2OFrame(python_obj=zip(*acosh_data))
h2o_data4 = h2o.H2OFrame(python_obj=zip(*abs_data))
h2o_data5 = h2o.H2OFrame(python_obj=zip(*zero_one_data))
np_data1 = np.array(sin_cos_tan_atan_sinh_cosh_tanh_asinh_data)
np_data2 = np.array(asin_acos_atanh_data)
np_data3 = np.array(acosh_data)
np_data4 = np.array(abs_data)
np_data5 = np.array(zero_one_data)
row, col = h2o_data1.dim
c = random.randint(0, col - 1)
for d in range(1, 6):
h2o_signif = h2o_data5[c].signif(digits=d)
h2o_round = h2o_data5[c].round(digits=d + 4)
s = h2o_signif[0]
r = h2o_round[0]
assert s == r, "Expected these to be equal, but signif: {0}, round: {1}".format(
s, r)
h2o_transposed = h2o_data1[c].transpose()
x, y = h2o_transposed.dim
assert x == 1 and y == 10, "Expected 1 row and 10 columns, but got {0} rows and {1} columns".format(
x, y)
pyunit_utils.np_comparison_check(h2o_data1[:, c].cos(),
np.cos(np_data1[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[:, c].sin(),
np.sin(np_data1[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[:, c].tan(),
np.tan(np_data1[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data2[:, c].acos(),
np.arccos(np_data2[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data2[:, c].asin(),
np.arcsin(np_data2[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[:, c].atan(),
np.arctan(np_data1[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[:, c].cosh(),
np.cosh(np_data1[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[c].sinh(),
np.sinh(np_data1[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[c].tanh(),
np.tanh(np_data1[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data3[c].acosh(),
np.arccosh(np_data3[:, c]), 10)
pyunit_utils.np_comparison_check(h2o_data1[c].asinh(),
np.arcsinh(np_data1[:, c]), 10)
h2o_val = h2o_data3[c].gamma()[5, :]._scalar()
num_val = math.gamma(h2o_data3[5, c])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal gamma values between h2o and" \
"math".format(h2o_val,num_val)
h2o_val = h2o_data3[c].lgamma()[5, :]._scalar()
num_val = math.lgamma(h2o_data3[5, c])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal lgamma values between h2o and " \
"math".format(h2o_val,num_val)
h2o_val = h2o_data3[c].digamma()[5, :]._scalar()
num_val = scipy.special.polygamma(0, h2o_data3[5, c])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal digamma values between h2o and " \
"math".format(h2o_val,num_val)
h2o_val = h2o_data3[c].trigamma()[5, :]._scalar()
num_val = scipy.special.polygamma(1, h2o_data3[5, c])
assert abs(h2o_val - float(num_val)) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal trigamma values between h2o and " \
"math".format(h2o_val,num_val)
def expr_math_ops():
sin_cos_tan_atan_sinh_cosh_tanh_asinh_data = [
[random.uniform(-10, 10) for r in range(10)] for c in range(10)
]
asin_acos_atanh_data = [[random.uniform(-1, 1) for r in range(10)]
for c in range(10)]
acosh_data = [[random.uniform(1, 10) for r in range(10)]
for c in range(10)]
abs_data = [[random.uniform(-100000, 0) for r in range(10)]
for c in range(10)]
h2o_data1_1 = h2o.H2OFrame(sin_cos_tan_atan_sinh_cosh_tanh_asinh_data)
h2o_data2_1 = h2o.H2OFrame(asin_acos_atanh_data)
h2o_data3_1 = h2o.H2OFrame(acosh_data)
h2o_data4_1 = h2o.H2OFrame(abs_data)
np_data1 = np.array(sin_cos_tan_atan_sinh_cosh_tanh_asinh_data)
np_data2 = np.array(asin_acos_atanh_data)
np_data3 = np.array(acosh_data)
np_data4 = np.array(abs_data)
h2o_data1 = h2o_data1_1 + 2
h2o_data2 = old_div(h2o_data2_1, 1.01)
h2o_data3 = h2o_data3_1 * 1.5
h2o_data4 = h2o_data4_1 - 1.5
np_data1 = np_data1 + 2
np_data2 = old_div(np_data2, 1.01)
np_data3 = np_data3 * 1.5
np_data4 = np_data4 - 1.5
pyunit_utils.np_comparison_check(h2o_data1.cos(), np.cos(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.sin(), np.sin(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.tan(), np.tan(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data2.acos(), np.arccos(np_data2), 10)
pyunit_utils.np_comparison_check(h2o_data2.asin(), np.arcsin(np_data2), 10)
pyunit_utils.np_comparison_check(h2o_data1.atan(), np.arctan(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.cosh(), np.cosh(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.sinh(), np.sinh(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data1.tanh(), np.tanh(np_data1), 10)
pyunit_utils.np_comparison_check(h2o_data3.acosh(), np.arccosh(np_data3),
10)
pyunit_utils.np_comparison_check(h2o_data1.asinh(), np.arcsinh(np_data1),
10)
pyunit_utils.np_comparison_check(h2o_data2.atanh(), np.arctanh(np_data2),
10)
pyunit_utils.np_comparison_check((old_div(h2o_data2, math.pi)).cospi(),
np.cos(np_data2), 10)
pyunit_utils.np_comparison_check((old_div(h2o_data2, math.pi)).sinpi(),
np.sin(np_data2), 10)
pyunit_utils.np_comparison_check((old_div(h2o_data2, math.pi)).tanpi(),
np.tan(np_data2), 10)
pyunit_utils.np_comparison_check(h2o_data4.abs(), np.fabs(np_data4), 10)
pyunit_utils.np_comparison_check(h2o_data2.sign(), np.sign(np_data2), 10)
pyunit_utils.np_comparison_check(h2o_data3.sqrt(), np.sqrt(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.trunc(), np.trunc(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.ceil(), np.ceil(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.floor(), np.floor(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.log(), np.log(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.log10(), np.log10(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.log1p(), np.log1p(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.log2(), np.log2(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.exp(), np.exp(np_data3), 10)
pyunit_utils.np_comparison_check(h2o_data3.expm1(), np.expm1(np_data3), 10)
h2o_val = h2o_data3.gamma()[5, 5]
num_val = math.gamma(h2o_data3[5, 5])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal gamma values between h2o and " \
"math".format(h2o_val,num_val)
h2o_val = h2o_data3.lgamma()[5, 5]
num_val = math.lgamma(h2o_data3[5, 5])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal lgamma values between h2o and " \
"math".\
format(h2o_val,num_val)
h2o_val = h2o_data3.digamma()[5, 5]
num_val = scipy.special.polygamma(0, h2o_data3[5, 5])
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal digamma values between h2o and " \
"math"\
.format(h2o_val,num_val)
h2o_val = h2o_data3.trigamma()[5, 5]
num_val = float(scipy.special.polygamma(1, h2o_data3[5, 5]))
assert abs(h2o_val - num_val) < max(abs(h2o_val), abs(num_val)) * 1e-6, \
"check unsuccessful! h2o computed {0} and math computed {1}. expected equal trigamma values between h2o and " \
"math".format(h2o_val,num_val)
