def generate_fptaylor(x):
x_low = sollya.inf(x)
x_high = sollya.sup(x)
query = "\n".join([
"Variables", " real x in [{},{}];".format(x_low, x_high),
"Definitions", " r rnd64= x;",
" retval rnd64= {};".format(poly_expr), "Expressions",
" retval;"
])
rnd_rel_err = None
rnd_abs_err = None
try:
res = fptaylor.Result(query, {
**config, "--rel-error": "true",
"--abs-error": "true"
})
rnd_rel_err = float(
res.result["relative_errors"]["final_total"]["value"])
rnd_abs_err = float(
res.result["absolute_errors"]["final_total"]["value"])
except AssertionError:
pass
except KeyError:
try:
rnd_abs_err = float(
res.result["absolute_errors"]["final_total"]["value"])
except KeyError:
pass
if rnd_abs_err is None:
try:
res = fptaylor.Result(query, {
**config, "--rel-error": "false",
"--abs-error": "true"
})
rnd_abs_err = float(
res.result["absolute_errors"]["final_total"]["value"])
except AssertionError:
pass
err_int = sollya.supnorm(self.poly_object.get_sollya_object(),
sollya.exp(sollya.x), x, sollya.relative,
2**-100)
algo_rel_err = sollya.sup(err_int)
err_int = sollya.supnorm(self.poly_object.get_sollya_object(),
sollya.exp(sollya.x), x, sollya.absolute,
2**-100)
algo_abs_err = sollya.sup(err_int)
if rnd_rel_err is None or str(algo_rel_err) == "error":
rel_err = float("inf")
else:
rel_err = rnd_rel_err + algo_rel_err
abs_err = rnd_abs_err + algo_abs_err
return rel_err, abs_err
def generate_reduction_fptaylor(x):
# get sign and abs_x, must be the same at endpoints
if sollya.sup(x) <= 0:
sign_x_expr = "-1.0"
abs_x_expr = "-x"
abs_x = -x
elif sollya.inf(x) >= 0:
sign_x_expr = "1.0"
abs_x_expr = "x"
abs_x = x
else:
assert False, "Interval must not straddle 0"
# get k, must be the same at endpoints
unround_k = abs_x * n_invpi
k_low = sollya.floor(sollya.inf(unround_k))
k_high = sollya.floor(sollya.sup(unround_k))
if k_low != k_high:
assert False, "Interval must not straddle multples of pi"
k = int(k_low)
part = k % 2
r_expr = "abs_x - whole"
r = abs_x - k * n_pi
z_expr = "r"
z = r
if part == 1:
flipped_poly_expr = "-poly"
else:
flipped_poly_expr = "poly"
x_low = sollya.inf(x)
x_high = sollya.sup(x)
query = "\n".join([
"Variables", " real x in [{},{}];".format(x_low, x_high),
"Definitions", " abs_x rnd64= {};".format(abs_x_expr),
" whole rnd64= {} * {};".format(k, n_pi),
" r rnd64= abs_x - whole;", " z rnd64= {};".format(z_expr),
" poly rnd64= {};".format(poly_expr),
" flipped_poly rnd64= {};".format(flipped_poly_expr),
" retval rnd64= flipped_poly*{};".format(sign_x_expr),
"Expressions", " retval;"
])
rnd_rel_err = None
rnd_abs_err = None
try:
res = fptaylor.Result(query, {
**config, "--rel-error": "true",
"--abs-error": "true"
})
rnd_rel_err = float(
res.result["relative_errors"]["final_total"]["value"])
rnd_abs_err = float(
res.result["absolute_errors"]["final_total"]["value"])
except AssertionError:
pass
except KeyError:
try:
rnd_abs_err = float(
res.result["absolute_errors"]["final_total"]["value"])
except KeyError:
pass
if rnd_abs_err is None:
try:
res = fptaylor.Result(query, {
**config, "--rel-error": "false",
"--abs-error": "true"
})
rnd_abs_err = float(
res.result["absolute_errors"]["final_total"]["value"])
except AssertionError:
pass
err_int = sollya.supnorm(self.poly_object.get_sollya_object(),
sollya.sin(sollya.x), z, sollya.relative,
2**-100)
algo_rel_err = sollya.sup(err_int)
err_int = sollya.supnorm(self.poly_object.get_sollya_object(),
sollya.sin(sollya.x), z, sollya.absolute,
2**-100)
algo_abs_err = sollya.sup(err_int)
if rnd_rel_err is None or str(algo_rel_err) == "error":
rel_err = float("inf")
else:
rel_err = rnd_rel_err + algo_rel_err
abs_err = rnd_abs_err + algo_abs_err
return rel_err, abs_err
def piecewise_approximation(function,
variable,
precision,
bound_low=-1.0,
bound_high=1.0,
num_intervals=16,
max_degree=2,
error_threshold=S2**-24,
odd=False,
even=False):
""" Generate a piecewise approximation
:param function: function to be approximated
:type function: SollyaObject
:param variable: input variable
:type variable: Variable
:param precision: variable's format
:type precision: ML_Format
:param bound_low: lower bound for the approximation interval
:param bound_high: upper bound for the approximation interval
:param num_intervals: number of sub-interval / sub-division of the main interval
:param max_degree: maximum degree for an approximation on any sub-interval
:param error_threshold: error bound for an approximation on any sub-interval
:return: pair (scheme, error) where scheme is a graph node for an
approximation scheme of function evaluated at variable, and error
is the maximum approximation error encountered
:rtype tuple(ML_Operation, SollyaObject): """
degree_generator = piecewise_approximation_degree_generator(
function,
bound_low,
bound_high,
num_intervals=num_intervals,
error_threshold=error_threshold,
)
degree_list = list(degree_generator)
# if max_degree is None then we determine it locally
if max_degree is None:
max_degree = max(degree_list)
# table to store coefficients of the approximation on each segment
coeff_table = ML_NewTable(
dimensions=[num_intervals, max_degree + 1],
storage_precision=precision,
tag="coeff_table",
const=True # by default all approximation coeff table are const
)
error_function = lambda p, f, ai, mod, t: sollya.dirtyinfnorm(p - f, ai)
max_approx_error = 0.0
interval_size = (bound_high - bound_low) / num_intervals
for i in range(num_intervals):
subint_low = bound_low + i * interval_size
subint_high = bound_low + (i + 1) * interval_size
local_function = function(sollya.x + subint_low)
local_interval = Interval(-interval_size, interval_size)
local_degree = degree_list[i]
if local_degree > max_degree:
Log.report(
Log.Warning,
"local_degree {} exceeds max_degree bound ({}) in piecewise_approximation",
local_degree, max_degree)
# as max_degree defines the size of the table we can use
# it as the degree for each sub-interval polynomial
# as there is nothing to gain (yet) by using a smaller polynomial
degree = max_degree # min(max_degree, local_degree)
if function(subint_low) == 0.0:
# if the lower bound is a zero to the function, we
# need to force value=0 for the constant coefficient
# and extend the approximation interval
local_poly_degree_list = list(
range(1 if even else 0, degree + 1, 2 if odd or even else 1))
poly_object, approx_error = Polynomial.build_from_approximation_with_error(
function(sollya.x) / sollya.x,
local_poly_degree_list,
[precision] * len(local_poly_degree_list),
Interval(-subint_high * 0.95, subint_high),
sollya.absolute,
error_function=error_function)
# multiply by sollya.x
poly_object = poly_object.sub_poly(offset=-1)
else:
try:
poly_object, approx_error = Polynomial.build_from_approximation_with_error(
local_function,
degree, [precision] * (degree + 1),
local_interval,
sollya.absolute,
error_function=error_function)
except SollyaError as err:
# try to see if function is constant on the interval (possible
# failure cause for fpminmax)
cst_value = precision.round_sollya_object(
function(subint_low), sollya.RN)
accuracy = error_threshold
diff_with_cst_range = sollya.supnorm(cst_value, local_function,
local_interval,
sollya.absolute, accuracy)
diff_with_cst = sup(abs(diff_with_cst_range))
if diff_with_cst < error_threshold:
Log.report(Log.Info, "constant polynomial detected")
poly_object = Polynomial([function(subint_low)] +
[0] * degree)
approx_error = diff_with_cst
else:
Log.report(
Log.error,
"degree: {} for index {}, diff_with_cst={} (vs error_threshold={}) ",
degree,
i,
diff_with_cst,
error_threshold,
error=err)
for ci in range(max_degree + 1):
if ci in poly_object.coeff_map:
coeff_table[i][ci] = poly_object.coeff_map[ci]
else:
coeff_table[i][ci] = 0.0
if approx_error > error_threshold:
Log.report(
Log.Warning,
"piecewise_approximation on index {} exceeds error threshold: {} > {}",
i, approx_error, error_threshold)
max_approx_error = max(max_approx_error, abs(approx_error))
# computing offset
diff = Subtraction(variable,
Constant(bound_low, precision=precision),
tag="diff",
debug=debug_multi,
precision=precision)
int_prec = precision.get_integer_format()
# delta = bound_high - bound_low
delta_ratio = Constant(num_intervals / (bound_high - bound_low),
precision=precision)
# computing table index
# index = nearestint(diff / delta * <num_intervals>)
index = Max(0,
Min(
NearestInteger(
Multiplication(diff, delta_ratio, precision=precision),
precision=int_prec,
), num_intervals - 1),
tag="index",
debug=debug_multi,
precision=int_prec)
poly_var = Subtraction(diff,
Multiplication(
Conversion(index, precision=precision),
Constant(interval_size, precision=precision)),
precision=precision,
tag="poly_var",
debug=debug_multi)
# generating indexed polynomial
coeffs = [(ci, TableLoad(coeff_table, index, ci))
for ci in range(max_degree + 1)][::-1]
poly_scheme = PolynomialSchemeEvaluator.generate_horner_scheme2(
coeffs, poly_var, precision, {}, precision)
return poly_scheme, max_approx_error
def build_from_approximation_with_error(function, poly_degree,
coeff_formats, approx_interval,
*modifiers, **kwords):
""" construct a polynomial object from a function approximation using
sollya's fpminimax """
tightness = kwords["tightness"] if "tightness" in kwords else S2**-24
error_function = kwords[
"error_function"] if "error_function" in kwords else lambda p, f, ai, mod, t: sollya.supnorm(
p, f, ai, mod, t)
precision_list = []
for c in coeff_formats:
if isinstance(c, ML_FP_Format):
precision_list.append(c.get_sollya_object())
else:
precision_list.append(c)
sollya_poly = sollya.fpminimax(function, poly_degree, precision_list,
approx_interval, *modifiers)
if sollya_poly.is_error():
print(
"function: {}, poly_degree: {}, precision_list: {}, approx_interval: {}, modifiers: {}"
.format(function, poly_degree, precision_list, approx_interval,
modifiers))
raise SollyaError()
fpnorm_modifiers = sollya.absolute if sollya.absolute in modifiers else sollya.relative
#approx_error = sollya.supnorm(sollya_poly, function, approx_interval, fpnorm_modifiers, tightness)
approx_error = error_function(sollya_poly, function, approx_interval,
fpnorm_modifiers, tightness)
return Polynomial(sollya_poly), approx_error
def generate_reduction_fptaylor(x):
# get k, must be the same at endpoints
unround_k = x * n_invlog2
k_low = sollya.floor(sollya.inf(unround_k))
k_high = sollya.floor(sollya.sup(unround_k))
if not (k_low == k_high or (k_low == -1 and sollya.sup(x) == 0)):
assert False, "Interval must not straddle multples of log(2)"
k = int(k_low)
r = x - k * n_log2
twok = 2**k
x_low = sollya.inf(x)
x_high = sollya.sup(x)
query = "\n".join([
"Variables", " real x in [{},{}];".format(x_low, x_high),
"Definitions", " whole rnd64= {} * {};".format(k, n_log2),
" r rnd64= x - whole;", " poly rnd64= {};".format(poly_expr),
" retval rnd64= poly*{};".format(twok), "Expressions",
" retval;"
])
rnd_rel_err = None
rnd_abs_err = None
try:
res = fptaylor.Result(query, {
**config, "--rel-error": "true",
"--abs-error": "true"
})
rnd_rel_err = float(
res.result["relative_errors"]["final_total"]["value"])
rnd_abs_err = float(
res.result["absolute_errors"]["final_total"]["value"])
except AssertionError:
pass
except KeyError:
try:
rnd_abs_err = float(
res.result["absolute_errors"]["final_total"]["value"])
except KeyError:
pass
if rnd_abs_err is None:
try:
res = fptaylor.Result(query, {
**config, "--rel-error": "false",
"--abs-error": "true"
})
rnd_abs_err = float(
res.result["absolute_errors"]["final_total"]["value"])
except AssertionError:
pass
err_int = sollya.supnorm(self.poly_object.get_sollya_object(),
sollya.exp(sollya.x), r, sollya.relative,
2**-100)
algo_rel_err = sollya.sup(err_int)
err_int = sollya.supnorm(self.poly_object.get_sollya_object(),
sollya.exp(sollya.x), r, sollya.absolute,
2**-100)
algo_abs_err = sollya.sup(err_int)
if rnd_rel_err is None or str(algo_rel_err) == "error":
rel_err = float("inf")
else:
rel_err = rnd_rel_err + algo_rel_err
abs_err = rnd_abs_err + algo_abs_err
return rel_err, abs_err
def generate_reduction_fptaylor(x):
unround_e = sollya.log2(I)
e_low = sollya.floor(sollya.inf(unround_e))
e_high = sollya.floor(sollya.sup(unround_e))
if e_low != e_high:
assert False, "Interval must not stradle a binade"
e = int(e_low) + 1
z = x / (2**e) * 0.5
query = "\n".join(
["Variables",
" real z in [{},{}];".format(sollya.inf(z), sollya.sup(z)),
"Definitions",
" poly rnd64= {};".format(poly_expr),
" retval rnd64= {}*{} + poly;".format(e, n_log2),
"Expressions",
" retval;"])
rnd_rel_err = None
rnd_abs_err = None
try:
res = fptaylor.Result(query, {**config,
"--rel-error": "true",
"--abs-error": "true"})
rnd_rel_err = float(res.result["relative_errors"]["final_total"]["value"])
rnd_abs_err = float(res.result["absolute_errors"]["final_total"]["value"])
except AssertionError:
pass
except KeyError:
try:
rnd_abs_err = float(res.result["absolute_errors"]["final_total"]["value"])
except KeyError:
pass
if rnd_abs_err is None:
try:
res = fptaylor.Result(query, {**config,
"--rel-error": "false",
"--abs-error": "true"})
rnd_abs_err = float(res.result["absolute_errors"]["final_total"]["value"])
except AssertionError:
pass
err_int = sollya.supnorm(self.poly_object.get_sollya_object(),
sollya.log(sollya.x),
z,
sollya.relative,
2**-100)
algo_rel_err = sollya.sup(err_int)
err_int = sollya.supnorm(self.poly_object.get_sollya_object(),
sollya.log(sollya.x),
z,
sollya.absolute,
2**-100)
algo_abs_err = sollya.sup(err_int)
if rnd_rel_err is None or str(algo_rel_err) == "error":
rel_err = float("inf")
else:
rel_err = rnd_rel_err + algo_rel_err
abs_err = rnd_abs_err + algo_abs_err
return rel_err, abs_err
top_approx_error.value))
error_count += 1
if args.exit_on_error:
sys.exit(1)
if args.check_level in ["strong"]:
sub_function = sub_approx.function
sub_approx_poly = sub_approx.poly.get_sollya_object()
# TODO/FIXME errorType should be derived from approx
# error target type
# TODO/FIXME: manage accuracy properly
error_type = sub_approx.approx_error.sollya_error_type
eval_approx_error = sup(
abs(
sollya.supnorm(sub_approx_poly, sub_function,
sub_approx.interval, error_type,
2**-24)))
eval_approx_error_inf = sup(
abs(
sollya.infnorm(sub_approx_poly - sub_function,
sub_approx.interval)))
if sub_approx.approx_error.value > eval_approx_error and sub_approx.approx_error.value > eval_approx_error_inf:
print(
"[ERROR] approx-error for sub approximation (#{}) infnorm={}, supnorm={} exceeds registered value {}"
.format(
sub_id,
eval_approx_error,
eval_approx_error_inf,
sub_approx.approx_error.value,
))
error_count += 1