def test_exp():
from datatable import exp
assert exp(0) == math.exp(0)
assert exp(1) == math.exp(1)
assert exp(-2.5e12) == math.exp(-2.5e12)
assert exp(12345678) == math.inf
assert exp(None) is None
def test_exp_srcs(src):
from math import exp, inf
DT = dt.Frame(src)
DT1 = dt.exp(DT)
frame_integrity_check(DT1)
assert all([st == stype.float64 for st in DT1.stypes])
pyans = []
for x in src:
if x is None:
pyans.append(None)
else:
try:
pyans.append(exp(x))
except OverflowError:
pyans.append(inf)
assert DT1.to_list()[0] == pyans
def test_exp_srcs(src):
from math import exp, inf
dt0 = dt.Frame(src)
dt1 = dt.exp(dt0)
dt1.internal.check()
assert all([st == stype.float64 for st in dt1.stypes])
pyans = []
for x in src:
if x is None:
pyans.append(None)
else:
try:
pyans.append(exp(x))
except OverflowError:
pyans.append(inf)
assert dt1.to_list()[0] == pyans
def test_exp_all_stypes():
from datatable import exp
src = [[-127, -5, -1, 0, 2, 127], [-32767, -299, -7, 32767, 12, -543],
[-2147483647, -1000, 3, -589, 2147483647, 0],
[-2**63 + 1, 2**63 - 1, 0, -2**32, 2**32, -793]]
DT = dt.Frame(src, stypes=[dt.int8, dt.int16, dt.int32, dt.int64])
DT1 = DT[:, [exp(f[i]) for i in range(4)]]
frame_integrity_check(DT1)
pyans = []
for col in src:
l = []
for x in col:
if x is None:
l.append(None)
else:
try:
l.append(math.exp(x))
except OverflowError:
l.append(math.inf)
pyans.append(l)
assert DT1.to_list() == pyans
def test_exp_all_stypes():
from datatable import exp
import math
src = [[-127, -5, -1, 0, 2, 127], [-32767, -299, -7, 32767, 12, -543],
[-2147483647, -1000, 3, -589, 2147483647, 0],
[-2**63 + 1, 2**63 - 1, 0, -2**32, 2**32, -793]]
dt0 = dt.Frame(src, stypes=[dt.int8, dt.int16, dt.int32, dt.int64])
dt1 = dt0[:, [exp(f[i]) for i in range(4)]]
dt1.internal.check()
pyans = []
for col in src:
l = []
for x in col:
if x is None:
l.append(None)
else:
try:
l.append(math.exp(x))
except OverflowError:
l.append(math.inf)
pyans.append(l)
assert dt1.topython() == pyans
def transform(self, X: dt.Frame):
return X[:, [(dt.f[i] / dt.abs(dt.f[i])) * dt.exp(0.5 * dt.log(dt.abs(dt.f[i]))) for i in range(X.ncols)]]
def transform(self, X: dt.Frame):
X_diff = X[:, dt.f[0] - dt.f[1]]
X_diff[dt.f[0] > 20, 0] = 20 # want no more than e**20
return X_diff[:, dt.exp(dt.f[0])]
def transform(self, X: dt.Frame):
return X[:, dt.exp(dt.f[0] - dt.f[1])]
# https://datatable.readthedocs.io/en/latest/?badge=latest
# https://datatable.readthedocs.io/en/latest/using-datatable.html
try:
# noinspection PyUnresolvedReferences
import datatable
except ImportError:
pass
import data_algebra
import data_algebra.data_model
import data_algebra.expr_rep
import data_algebra.data_ops
expr_to_dt_expr_map = {
"exp": lambda expr: datatable.exp(expr_to_dt_expr(expr.args[0])),
"sum": lambda expr: datatable.sum(expr_to_dt_expr(expr.args[0])),
"+":
lambda expr: expr_to_dt_expr(expr.args[0]) + expr_to_dt_expr(expr.args[1]),
"-":
lambda expr: expr_to_dt_expr(expr.args[0]) - expr_to_dt_expr(expr.args[1]),
"*":
lambda expr: expr_to_dt_expr(expr.args[0]) * expr_to_dt_expr(expr.args[1]),
"/":
lambda expr: expr_to_dt_expr(expr.args[0]) / expr_to_dt_expr(expr.args[1]),
"neg": lambda expr: -expr_to_dt_expr(expr.args[0]),
}
def expr_to_dt_expr(expr):
if isinstance(expr, data_algebra.expr_rep.ColumnReference):
