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add string support to if statement #33

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merged 2 commits into from
Nov 10, 2023
Merged

add string support to if statement #33

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1d83b13
add string support to if statement
TimurUncountable Nov 7, 2023
fd4396e
bump version
TimurUncountable Nov 7, 2023
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48 changes: 25 additions & 23 deletions hotxlfp/formulas/logic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,69 +7,70 @@
from . import error
from . import utils
import torch
import numpy as np


@dispatcher.register_for('AND')
@dispatcher.register_for("AND")
def AND(*args):
args = utils.iflatten(args)
return all(args)


@dispatcher.register_for('IF')
@dispatcher.register_for("IF")
def IF(test, then, otherwise):
if isinstance(test, error.XLError):
return error.XLError
test_condition = torch.tensor(test, dtype=torch.bool)
if test_condition.all():
if isinstance(then, error.XLError):
return then
return torch.tensor(then, dtype=torch.double)
elif (~test_condition).all():
if isinstance(otherwise, error.XLError):
return otherwise
return torch.tensor(otherwise, dtype=torch.double)

if isinstance(then, error.XLError):
return then
if isinstance(otherwise, error.XLError):
return otherwise


if (
isinstance(then, str)
or isinstance(otherwise, str)
or (isinstance(then, np.ndarray) and then.dtype.kind == "U")
or (isinstance(otherwise, np.ndarray) and otherwise.dtype.kind == "U")
):
then_str = np.array(then, dtype="U")
otherwise_str = np.array(otherwise, dtype="U")
return np.where(np.array(test, dtype="b"), then_str, otherwise_str)
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This seems like a good strategy. I'll test to see if this np.array strategy works on our platform, but it also looks like it shouldn't cause any regressions because of the type checks you are doing.


return torch.where(
test_condition,
torch.tensor(test, dtype=torch.bool),
torch.tensor(then, dtype=torch.double),
torch.tensor(otherwise, dtype=torch.double),
)


@dispatcher.register_for('IFERROR')
@dispatcher.register_for("IFERROR")
def IFERROR(value, value_if_error):
return value if not isinstance(value, error.XLError) else value_if_error


@dispatcher.register_for('IFNA')
@dispatcher.register_for("IFNA")
def IFNA(value, value_if_na):
return value if value != error.NOT_AVAILABLE else value_if_na


@dispatcher.register_for('NOT')
@dispatcher.register_for("NOT")
def NOT(boolean):
return not boolean


@dispatcher.register_for('XOR')
@dispatcher.register_for("XOR")
def XOR(*args):
args = utils.iflatten(args)
result = sum(bool(a) for a in args)
return bool(result & 1)


@dispatcher.register_for('OR')
@dispatcher.register_for("OR")
def OR(*args):
args = utils.iflatten(args)
return any(args)


@dispatcher.register_for('SWITCH')
@dispatcher.register_for("SWITCH")
def SWITCH(target_value, *args):
if len(args) <= 1:
return error.NOT_AVAILABLE
Expand All @@ -83,7 +84,7 @@ def SWITCH(target_value, *args):
return error.NOT_AVAILABLE


@dispatcher.register_for('IFS')
@dispatcher.register_for("IFS")
def IFS(*args):
for pair in zip(args[::2], args[1::2]):
if pair[0]:
Expand All @@ -93,11 +94,12 @@ def IFS(*args):

# Compatibility functions

@dispatcher.register_for('TRUE')

@dispatcher.register_for("TRUE")
def TRUE():
return True


@dispatcher.register_for('FALSE')
@dispatcher.register_for("FALSE")
def FALSE():
return False
2 changes: 1 addition & 1 deletion setup.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@

setup(
name="hotxlfp",
version="0.0.11+unc.29",
version="0.0.11+unc.30",
packages=[
"hotxlfp",
"hotxlfp._compat",
Expand Down
155 changes: 110 additions & 45 deletions tests/test_formula_parser.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
import torch
from hotxlfp import Parser
from math import pi
import numpy as np


def _test_equation(
Expand All @@ -20,10 +21,13 @@ def _test_equation(
except (error.XLError, TypeError):
assert should_fail
return
assert isinstance(result, torch.Tensor)
assert (
torch.abs(result - torch.tensor(answer)) < 0.000001
).all(), f"{result} != {answer}"
if isinstance(result, np.ndarray):
assert (result == answer).all(), f"{result} != {answer}"
else:
assert isinstance(result, torch.Tensor)
assert (
torch.abs(result - torch.tensor(answer)) < 0.000001
).all(), f"{result} != {answer}"


class TestFormulaParser(unittest.TestCase):
Expand Down Expand Up @@ -347,7 +351,7 @@ def test_decimal(self):
)

def test_order_of_operations(self):
_test_equation(equation="2^-2-1", variables={"a1": [1]}, answer=[-.75])
_test_equation(equation="2^-2-1", variables={"a1": [1]}, answer=[-0.75])
_test_equation(equation="(2^(-1))", variables={"a1": [1]}, answer=[0.5])
_test_equation(equation="((2^(-1))-1)", variables={"a1": [1]}, answer=[-0.5])
_test_equation(equation="2^2-1", variables={"a1": [1]}, answer=[3])
Expand All @@ -360,55 +364,116 @@ def test_order_of_operations(self):
_test_equation(equation="1 + 2 * 3 - 4", variables={"a1": [1]}, answer=[3])

def test_if_statement_args(self):
_test_equation(equation="IF(a1 > 10, 1, 100, 400)", variables={"a1": [4]}, should_fail=True)
_test_equation(equation="IF(a1 > 10, 400)", variables={"a1": [4]}, should_fail=True)
_test_equation(equation="IF(a1 > 10, )", variables={"a1": [4]}, should_fail=True)
_test_equation(
equation="IF(a1 > 10, 1, 100, 400)", variables={"a1": [4]}, should_fail=True
)
_test_equation(
equation="IF(a1 > 10, 400)", variables={"a1": [4]}, should_fail=True
)
_test_equation(
equation="IF(a1 > 10, )", variables={"a1": [4]}, should_fail=True
)
_test_equation(equation="IF(,, )", variables={"a1": [4]}, should_fail=True)
_test_equation(equation="IF(a1 > 100, 40, IF(a1 > 1, 4, 56))", variables={"a1": [40]}, answer=[4])
_test_equation(equation="IF(a1 > 10, 40, IF(a1 > 10, 4))", variables={"a1": [4]}, should_fail=True)
_test_equation(
equation="IF(a1 > 100, 40, IF(a1 > 1, 4, 56))",
variables={"a1": [40]},
answer=[4],
)
_test_equation(
equation="IF(a1 > 10, 40, IF(a1 > 10, 4))",
variables={"a1": [4]},
should_fail=True,
)
_test_equation(
equation="IF(a1 > 10, 'abc', 'def')", variables={"a1": [4]}, answer=["def"]
)
_test_equation(
equation="IF(a1 > 100, 'abc', IF(a1 > 1, 4, 56))",
variables={"a1": [40]},
answer=["4.0"],
)

def test_tensors(self):
_test_equation(equation="MIN(a1 * 2, 2, 23, a1)", variables={"a1": [5]}, answer=[2])
_test_equation(
equation="MIN(a1 * 2, 2, 23, a1)", variables={"a1": [5]}, answer=[2]
)
_test_equation(equation="MIN(2, a1 * 2)", variables={"a1": [5]}, answer=[2])
_test_equation(equation="MAX(a1 * 2, 2)", variables={"a1": [5]}, answer=[10])
_test_equation(equation="MAX(2, a1 * 2)", variables={"a1": [5]}, answer=[10])
_test_equation(equation="MAX(MAX(2, a1 * 2), 100)", variables={"a1": [5, 4]}, answer=[100, 100])
_test_equation(
equation="MAX(MAX(2, a1 * 2), 100)",
variables={"a1": [5, 4]},
answer=[100, 100],
)
_test_equation(equation="5", variables={"a1": [5, 4]}, answer=[5])
_test_equation(equation="SQRT(100)", variables={"a1": [5]}, answer=[10])
_test_equation(equation="CEILING(a1)", variables={"a1": [4.5, -1.2]}, answer=[5, -1])
_test_equation(equation="CEILING(a1, a2)", variables={"a1": [0.5, 0.5], "a2": [1, 2]}, answer=[1, 2])
_test_equation(equation="CEILING(a1, a2)", variables={"a1": [0.5, 0.5], "a2": [2]}, answer=[2, 2])
_test_equation(equation="CEILING(a1, a2)", variables={"a1": [0.5], "a2": [1]}, answer=[1])
_test_equation(equation="IF(a1 <> a2, 1, 0)", variables={"a1": [3, 2], "a2": [3, 3]}, answer=[0, 1])
_test_equation(equation="IF(a1 <> a2, 1, 0)", variables={"a1": 4, "a2": 2}, answer=1)
_test_equation(equation="IF(a1 < a2, 1, 0)", variables={"a1": [1, 2], "a2": [0, 0]}, answer=[0, 0])
_test_equation(equation="IF(a1 < a2, 1, 0)", variables={"a1": 2, "a2": 3}, answer=1)
_test_equation(
equation="CEILING(a1)", variables={"a1": [4.5, -1.2]}, answer=[5, -1]
)
_test_equation(
equation="CEILING(a1, a2)",
variables={"a1": [0.5, 0.5], "a2": [1, 2]},
answer=[1, 2],
)
_test_equation(
equation="CEILING(a1, a2)",
variables={"a1": [0.5, 0.5], "a2": [2]},
answer=[2, 2],
)
_test_equation(
equation="CEILING(a1, a2)", variables={"a1": [0.5], "a2": [1]}, answer=[1]
)
_test_equation(
equation="IF(a1 <> a2, 1, 0)",
variables={"a1": [3, 2], "a2": [3, 3]},
answer=[0, 1],
)
_test_equation(
equation="IF(a1 <> a2, 1, 0)", variables={"a1": 4, "a2": 2}, answer=1
)
_test_equation(
equation="IF(a1 < a2, 1, 0)",
variables={"a1": [1, 2], "a2": [0, 0]},
answer=[0, 0],
)
_test_equation(
equation="IF(a1 < a2, 1, 0)", variables={"a1": 2, "a2": 3}, answer=1
)

def test_scientific_notation(self):
_test_equation(equation="2e2", variables={"a1" : [1.1]}, answer=[200])
_test_equation(equation="5(m)", variables={"m" : [10]}, answer=[50])
_test_equation(equation="5(e)", variables={"e" : [10]}, answer=[50])
_test_equation(equation="5(evar)", variables={"evar" : [10]}, answer=[50])
_test_equation(equation="5(vare)", variables={"vare" : [10]}, answer=[50])
_test_equation(equation="1 e 2", variables={"a1" : [1.1]}, answer=[100])
_test_equation(equation="1e2", variables={"a1" : [1.1]}, answer=[100])
_test_equation(equation="2*1e2", variables={"a1" : [1.1]}, answer=[200])
_test_equation(equation="2*1e2^3", variables={"a1" : [1.1]}, answer=[2000000])
_test_equation(equation="(2*1e2)^3", variables={"a1" : [1.1]}, answer=[8000000])
_test_equation(equation="(2)e(4)", variables={"a1" : [1.1]}, answer=[8000000], should_fail=True)
_test_equation(equation="(2)e(4)", variables={"a1" : [1.1]}, should_fail=True)
_test_equation(equation="0.2e2", variables={"a1" : [1.1]}, answer=20)
_test_equation(equation="0.2e0.2", variables={"a1" : [1.1]}, answer=0.2 * (10 ** 0.2))
_test_equation(equation="2e-1", variables={"a1" : [1.1]}, answer=0.2)
_test_equation(equation="-2e1", variables={"a1" : [1.1]}, answer=-20)
_test_equation(equation="-2e-1", variables={"a1" : [1.1]}, answer=-0.2)
_test_equation(equation="-2e-.1", variables={"a1" : [1.1]}, answer=-2 * (10 ** (-.1)))


_test_equation(equation="2E2", variables={"a1" : [1.1]}, answer=[200])
_test_equation(equation="2*1E2", variables={"a1" : [1.1]}, answer=[200])
_test_equation(equation="0.2E2", variables={"a1" : [1.1]}, answer=20)
_test_equation(equation="-2E-1", variables={"a1" : [1.1]}, answer=-0.2)
_test_equation(equation="2e2", variables={"a1": [1.1]}, answer=[200])
_test_equation(equation="5(m)", variables={"m": [10]}, answer=[50])
_test_equation(equation="5(e)", variables={"e": [10]}, answer=[50])
_test_equation(equation="5(evar)", variables={"evar": [10]}, answer=[50])
_test_equation(equation="5(vare)", variables={"vare": [10]}, answer=[50])
_test_equation(equation="1 e 2", variables={"a1": [1.1]}, answer=[100])
_test_equation(equation="1e2", variables={"a1": [1.1]}, answer=[100])
_test_equation(equation="2*1e2", variables={"a1": [1.1]}, answer=[200])
_test_equation(equation="2*1e2^3", variables={"a1": [1.1]}, answer=[2000000])
_test_equation(equation="(2*1e2)^3", variables={"a1": [1.1]}, answer=[8000000])
_test_equation(
equation="(2)e(4)",
variables={"a1": [1.1]},
answer=[8000000],
should_fail=True,
)
_test_equation(equation="(2)e(4)", variables={"a1": [1.1]}, should_fail=True)
_test_equation(equation="0.2e2", variables={"a1": [1.1]}, answer=20)
_test_equation(
equation="0.2e0.2", variables={"a1": [1.1]}, answer=0.2 * (10**0.2)
)
_test_equation(equation="2e-1", variables={"a1": [1.1]}, answer=0.2)
_test_equation(equation="-2e1", variables={"a1": [1.1]}, answer=-20)
_test_equation(equation="-2e-1", variables={"a1": [1.1]}, answer=-0.2)
_test_equation(
equation="-2e-.1", variables={"a1": [1.1]}, answer=-2 * (10 ** (-0.1))
)

_test_equation(equation="2E2", variables={"a1": [1.1]}, answer=[200])
_test_equation(equation="2*1E2", variables={"a1": [1.1]}, answer=[200])
_test_equation(equation="0.2E2", variables={"a1": [1.1]}, answer=20)
_test_equation(equation="-2E-1", variables={"a1": [1.1]}, answer=-0.2)


if __name__ == "__main__":
unittest.main()
unittest.main()