#!/usr/bin/env python
# -*- coding: UTF-8 -*-
#
# Copyright 2016-2026 European Commission (JRC);
# Licensed under the EUPL (the 'Licence');
# You may not use this work except in compliance with the Licence.
# You may obtain a copy of the Licence at: http://ec.europa.eu/idabc/eupl
"""
Python equivalents of logical Excel functions.
"""
import functools
import numpy as np
from . import (
wrap_ufunc, Error, flatten, get_error, wrap_func, XlError, raise_errors,
Array, replace_empty, _convert2float, return_2d_func
)
FUNCTIONS = {}
[docs]
def xif(condition, x, y=False):
if isinstance(condition, str):
return Error.errors['#VALUE!']
return x if condition else y
[docs]
def solve_cycle(*args):
return not args[0]
FUNCTIONS['IF'] = {
'function': wrap_ufunc(
xif, input_parser=lambda *a: a, check_nan=False,
check_error=lambda cond, *a: get_error(cond)
),
'solve_cycle': solve_cycle
}
[docs]
def xifs(*cond_vals):
if len(cond_vals) % 2:
cond_vals += 0,
for b, v in zip(cond_vals[::2], cond_vals[1::2]):
err = get_error(b)
if err:
return err
if isinstance(b, str):
raise ValueError
if b:
return v
return Error.errors['#N/A']
FUNCTIONS['_XLFN.IFS'] = FUNCTIONS['IFS'] = {
'function': wrap_ufunc(
xifs, input_parser=lambda *a: a, check_nan=False,
check_error=lambda *a: None
),
'solve_cycle': lambda *a: not any(a[::2])
}
[docs]
def xiferror(val, val_if_error):
from .info import iserror
return val_if_error if iserror(val) else val
FUNCTIONS['IFERROR'] = {
'function': wrap_ufunc(
xiferror, input_parser=lambda *a: a, check_error=lambda *a: False,
check_nan=False,
),
'solve_cycle': solve_cycle
}
[docs]
def xifna(val, val_if_error):
from .info import isna
return val_if_error if isna(val) else val
FUNCTIONS['_XLFN.IFNA'] = FUNCTIONS['IFNA'] = {
'function': wrap_ufunc(
xifna, input_parser=lambda *a: a, check_error=lambda *a: False,
check_nan=False,
),
'solve_cycle': solve_cycle
}
[docs]
def xswitch(val, *args):
if isinstance(val, bool):
condition = lambda x: val is x
else:
condition = lambda x: val == x
for k, v in zip(args[::2], args[1::2]):
if isinstance(k, XlError):
return k
elif condition(k):
return v
else:
return args[-1] if len(args) % 2 else Error.errors['#N/A']
FUNCTIONS["_XLFN.SWITCH"] = FUNCTIONS["SWITCH"] = {
'function': wrap_ufunc(
xswitch, input_parser=lambda *a: a,
check_error=lambda first, *a: get_error(first),
)
}
[docs]
def xand(logical, *logicals, func=np.logical_and.reduce):
args = (logical,) + logicals
raise_errors(args)
check = lambda x: not isinstance(x, str)
inp = tuple(flatten(args, check=check, drop_empty=True))
return func(inp) if inp else Error.errors['#VALUE!']
FUNCTIONS['AND'] = {'function': wrap_func(xand)}
FUNCTIONS['OR'] = {'function': wrap_func(
functools.partial(xand, func=np.logical_or.reduce)
)}
FUNCTIONS['_XLFN.XOR'] = FUNCTIONS['XOR'] = {'function': wrap_func(
functools.partial(xand, func=np.logical_xor.reduce)
)}
FUNCTIONS['NOT'] = {'function': wrap_ufunc(
np.logical_not, input_parser=lambda *a: a,
)}
def _get_first(v):
if isinstance(v, np.ndarray):
return v.ravel()[0]
return v
[docs]
def xbycol(array, func, axis=0):
array = np.atleast_2d(array)
if axis == 0:
array = array.T
res = np.asarray([[_get_first(func(v)) for v in array]], object)
if axis == 1:
res = res.T
return res.view(Array)
FUNCTIONS['_XLFN.BYCOL'] = FUNCTIONS['BYCOL'] = wrap_func(
functools.partial(xbycol, axis=0)
)
FUNCTIONS['_XLFN.BYROW'] = FUNCTIONS['BYROW'] = wrap_func(
functools.partial(xbycol, axis=1)
)
[docs]
def xmakearray(rows, cols, func):
if rows.is_integer() and cols.is_integer() and rows >= 1 and cols >= 1:
return np.asarray([[
_get_first(func(r, c)) for c in np.arange(cols) + 1
] for r in np.arange(rows) + 1], object).tolist()
return [[Error.errors['#VALUE!']]]
FUNCTIONS['_XLFN.MAKEARRAY'] = FUNCTIONS['MAKEARRAY'] = wrap_ufunc(
xmakearray, input_parser=lambda rows, columns, func: (
float(_convert2float(rows)), float(_convert2float(columns)), func
),
check_error=lambda rows, columns, func: get_error(rows, columns, func),
args_parser=lambda rows, columns, func: (
replace_empty(rows), replace_empty(columns), func
), return_func=return_2d_func, check_nan=False, excluded={2}
)
FUNCTIONS['_XLFN.REDUCE'] = FUNCTIONS['REDUCE'] = wrap_ufunc(
functools.reduce, input_parser=lambda initial_value, array, func: (
func, array, initial_value
),
check_error=lambda initial_value, array, func: get_error(func),
args_parser=lambda initial_value, array, func: (
replace_empty(initial_value), list(flatten(array, None)), func
), return_func=return_2d_func, check_nan=False, excluded={1, 2}
)
[docs]
def xscan(initial_value, array, func):
array = np.atleast_2d(array)
out = []
acc = replace_empty(initial_value)
for x in flatten(array, None):
acc = func(acc, x)
out.append(_get_first(acc))
return np.asarray(out).reshape(array.shape).view(Array)
FUNCTIONS['_XLFN.SCAN'] = FUNCTIONS['SCAN'] = wrap_func(xscan)
[docs]
def xmap(array, func, *arrays):
if arrays:
arrays = (func,) + arrays
func = arrays[-1]
arrays = arrays[:-1]
array = np.atleast_2d(array)
shape = array.shape
arrays = [array] + [np.atleast_2d(v) for v in arrays]
if not all(shape == v.shape for v in arrays):
return np.asarray([[Error.errors['#VALUE!']]]).view(Array)
out = []
for args in zip(*(flatten(v, None) for v in arrays)):
out.append(_get_first(func(*args)))
return np.asarray(out).reshape(array.shape).view(Array)
FUNCTIONS['_XLFN.MAP'] = FUNCTIONS['MAP'] = wrap_func(xmap)
def _true():
return True
def _false():
return False
FUNCTIONS['TRUE'] = wrap_func(_true)
FUNCTIONS['FALSE'] = wrap_func(_false)