def search_for_best(data):
"""searches for best configuration"""
min_residue = 1
data_temp = copy.copy(data)
_file = 'best_fit.txt'
f = open(_file, "w")
f.write("Подбор степеней полиномов для x1, x2, x3 при заданных условиях по критерию минимума максимального отклонения:\n")
for i_step_x1 in range(data._startdeg_x1, data._enddeg_x1+1):
for i_step_x2 in range(data._startdeg_x2, data._enddeg_x2+1):
for i_step_x3 in range(data._startdeg_x3, data._enddeg_x3+1):
data_temp._enddeg_x1 = i_step_x1
data_temp._enddeg_x2 = i_step_x2
data_temp._enddeg_x3 = i_step_x3
residue = fs.find_functions(data_temp)
res= -1
for i in range(data._dim_y):
if res < max(residue[:, i]):
res = max(residue[:, i])
if res < min_residue:
min_residue = res
f.write("Степени полиномов для x1, x2, x3: %d %d %d\n" % (i_step_x1, i_step_x2, i_step_x3))
f.write("Максимальное отклонение в этом случае: %0.6f\nСредние отклонения по координатам:\n" % min_residue)
for i in range(data._dim_y):
f.write("i = %d\t%0.6f\n" % (i+1, np.mean(residue[:, i])))
f.write("\n")
f.close()
def search_for_best(data):
"""searches for best configuration"""
min_residue = 1
data_temp = copy.copy(data)
_file = 'best_fit.txt'
f = open(_file, "w")
f.write("Searching for optimal power of poplynomials for x1, x2, x3 by data provided using using min max error criteria:\n")
for i_step_x1 in range(data._startdeg_x1, data._enddeg_x1+1):
for i_step_x2 in range(data._startdeg_x2, data._enddeg_x2+1):
for i_step_x3 in range(data._startdeg_x3, data._enddeg_x3+1):
data_temp._enddeg_x1 = i_step_x1
data_temp._enddeg_x2 = i_step_x2
data_temp._enddeg_x3 = i_step_x3
residue = fs.find_functions(data_temp)
res= -1
for i in range(data._dim_y):
if res < max(residue[:, i]):
res = max(residue[:, i])
if res < min_residue:
min_residue = res
f.write("Powers of polynomials for x1, x2, x3: %d %d %d\n" % (i_step_x1, i_step_x2, i_step_x3))
f.write("Max error in this case: %0.6f\nAverage error by coordinates:\n" % min_residue)
for i in range(data._dim_y):
f.write("i = %d\t%0.6f\n" % (i+1, np.mean(residue[:, i])))
f.write("\n")
f.close()
__author__ = 'Artemko'
import data as d
import functions_search as fs
import find_best as fb
data = d.Data()
data.normalize()
data.plot_data()
if data._findBest:
"""find polynomial degrees in specified boundaries for minimal residue"""
fb.search_for_best(data)
else:
"""calculate everything for specified configuration"""
fs.find_functions(data)
