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Silviu Marian Udrescu 2020-06-20 19:30:25 -04:00 • committed by GitHub
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commit a96e7f321a
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10 changed files with 119 additions and 133 deletions
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9
Code/RPN_to_pytorch.py
View file

@ -22,8 +22,7 @@ from S_get_number_DL_snapped import get_number_DL_snapped
from S_get_symbolic_expr_error import get_symbolic_expr_error
# parameters: path to data, RPN expression (obtained from bf)
def RPN_to_pytorch(pathdir,filename, math_expr, lr = 1e-2, N_epochs = 500):
data_file = pathdir + filename
def RPN_to_pytorch(data, math_expr, lr = 1e-2, N_epochs = 500):
param_dict = {}
unsnapped_param_dict = {'p':1}
@ -59,10 +58,6 @@ def RPN_to_pytorch(pathdir,filename, math_expr, lr = 1e-2, N_epochs = 500):
new_key = "{}{}{}{}{}".format(key, underscore, midfix, i, suffix)
return new_key
# Load the actual data
data = np.loadtxt(data_file)
# Turn BF expression to pytorch expression
eq = parse_expr(math_expr)
eq = unsnap_recur(eq,param_dict,unsnapped_param_dict)
@ -135,7 +130,7 @@ def RPN_to_pytorch(pathdir,filename, math_expr, lr = 1e-2, N_epochs = 500):
if n_operations!=0 or n_variables!=0:
complexity = complexity + (n_variables+n_operations)*np.log2((n_variables+n_operations))
error = get_symbolic_expr_error(pathdir,filename,str(eq))
error = get_symbolic_expr_error(data,str(eq))
return error, complexity, eq

5
Code/S_add_bf_on_numbers_on_pareto.py
View file

@ -29,7 +29,8 @@ from RPN_to_eq import RPN_to_eq
from S_get_number_DL_snapped import get_number_DL_snapped
# parameters: path to data, math (not RPN) expression
def add_bf_on_numbers_on_pareto(pathdir, filename, PA, math_expr):
def add_bf_on_numbers_on_pareto(pathdir, filename, PA, math_expr):
input_data = np.loadtxt(pathdir+filename)
def unsnap_recur(expr, param_dict, unsnapped_param_dict):
"""Recursively transform each numerical value into a learnable parameter."""
import sympy
@ -100,7 +101,7 @@ def add_bf_on_numbers_on_pareto(pathdir, filename, PA, math_expr):
for i in range(len(bf_on_numbers_expr)):
try:
# Calculate the error of the new, snapped expression
snapped_error = get_symbolic_expr_error(pathdir,filename,str(bf_on_numbers_expr[i]))
snapped_error = get_symbolic_expr_error(input_data,str(bf_on_numbers_expr[i]))
# Calculate the complexity of the new, snapped expression
expr = simplify(powsimp(bf_on_numbers_expr[i]))
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number

95
Code/S_add_snap_expr_on_pareto.py
View file

@ -33,6 +33,7 @@ def intify(expr):
# parameters: path to data, math (not RPN) expression
def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
input_data = np.loadtxt(pathdir+filename)
def unsnap_recur(expr, param_dict, unsnapped_param_dict):
"""Recursively transform each numerical value into a learnable parameter."""
import sympy
@ -68,29 +69,6 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
eq = parse_expr(str(math_expr))
expr = eq
# Get the numbers appearing in the expression
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
eq_numbers = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
# Do integer snap one parameter at a time
integer_snapped_expr = []
for w in range(len(eq_numbers)):
try:
param_dict = {}
unsnapped_param_dict = {'p':1}
eq = unsnap_recur(expr,param_dict,unsnapped_param_dict)
new_numbers = integerSnap(eq_numbers,w+1)
for kk in range(len(new_numbers)):
eq_numbers[new_numbers[kk][0]] = new_numbers[kk][1]
jj = 0
for parm in unsnapped_param_dict:
if parm!="p":
eq = eq.subs(parm, eq_numbers[jj])
jj = jj + 1
integer_snapped_expr = integer_snapped_expr + [eq]
except:
continue
# # Get the numbers appearing in the expression
# is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
# eq_numbers = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
@ -114,31 +92,52 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
# except:
# continue
# Get the numbers appearing in the expression
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
is_atomic_number = lambda expr:expr.is_Atom and expr.is_number
eq_numbers = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
# Do rational snap one parameter at a time
rational_snapped_expr = []
# Do integer snap one parameter at a time
integer_snapped_expr = []
for w in range(len(eq_numbers)):
try:
eq_numbers_snap = copy.deepcopy(eq_numbers)
param_dict = {}
unsnapped_param_dict = {'p':1}
eq = unsnap_recur(expr,param_dict,unsnapped_param_dict)
del unsnapped_param_dict["p"]
temp_unsnapped_param_dict = copy.deepcopy(unsnapped_param_dict)
new_numbers = integerSnap(eq_numbers,w+1)
new_numbers = {"p"+str(k): v for k, v in new_numbers.items()}
temp_unsnapped_param_dict.update(new_numbers)
#for kk in range(len(new_numbers)):
# eq_numbers[new_numbers[kk][0]] = new_numbers[kk][1]
new_eq = re.sub(r"(p\d*)",r"{\1}",str(eq))
new_eq = new_eq.format_map(temp_unsnapped_param_dict)
integer_snapped_expr = integer_snapped_expr + [parse_expr(new_eq)]
except:
continue
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
eq_numbers = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
# Do rational snap one parameter at a time
rational_snapped_expr = []
for w in range(len(eq_numbers)):
try:
param_dict = {}
unsnapped_param_dict = {'p':1}
eq = unsnap_recur(expr,param_dict,unsnapped_param_dict)
del unsnapped_param_dict["p"]
temp_unsnapped_param_dict = copy.deepcopy(unsnapped_param_dict)
new_numbers = rationalSnap(eq_numbers,w+1)
for kk in range(len(new_numbers)):
eq_numbers_snap[new_numbers[kk][0]] = new_numbers[kk][1][1:3]
jj = 0
for parm in unsnapped_param_dict:
if parm!="p":
try:
eq = eq.subs(parm, Rational(eq_numbers_snap[jj][0],eq_numbers_snap[jj][1]))
except:
eq = eq.subs(parm, eq_numbers_snap[jj])
jj = jj + 1
rational_snapped_expr = rational_snapped_expr + [eq]
new_numbers = {"p"+str(k): v for k, v in new_numbers.items()}
temp_unsnapped_param_dict.update(new_numbers)
#for kk in range(len(new_numbers)):
# eq_numbers_snap[new_numbers[kk][0]] = new_numbers[kk][1][1:3]
new_eq = re.sub(r"(p\d*)",r"{\1}",str(eq))
new_eq = new_eq.format_map(temp_unsnapped_param_dict)
rational_snapped_expr = rational_snapped_expr + [parse_expr(new_eq)]
except:
continue
@ -148,13 +147,13 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
for i in range(len(snapped_expr)):
try:
# Calculate the error of the new, snapped expression
snapped_error = get_symbolic_expr_error(pathdir,filename,str(snapped_expr[i]))
snapped_error = get_symbolic_expr_error(input_data,str(snapped_expr[i]))
# Calculate the complexity of the new, snapped expression
expr = simplify(powsimp(snapped_expr[i]))
#expr = simplify(powsimp(snapped_expr[i]))
expr = snapped_expr[i]
for s in (expr.free_symbols):
s = symbols(str(s), real = True)
expr = simplify(parse_expr(str(snapped_expr[i]),locals()))
#print("expr 0", expr)
expr = parse_expr(str(snapped_expr[i]),locals())
expr = intify(expr)
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
numbers_expr = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
@ -169,7 +168,7 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
if n_operations!=0 or n_variables!=0:
snapped_complexity = snapped_complexity + (n_variables+n_operations)*np.log2((n_variables+n_operations))
# If a bf file is provided, replace the variables with the actual ones before calculating the complexity
# If a da file is provided, replace the variables with the actual ones before calculating the complexity
else:
dr_data = np.loadtxt(DR_file,dtype="str",delimiter=",")
@ -182,10 +181,8 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
expr = parse_expr(expr)
for s in (expr.free_symbols):
s = symbols(str(s), real = True)
expr = simplify(parse_expr(str(expr),locals()))
#print("expr 1", expr)
#expr = intify(expr)
#print("expr 2", expr)
#expr = simplify(parse_expr(str(expr),locals()))
expr = parse_expr(str(expr),locals())
snapped_complexity = 0
for j in numbers_expr:
snapped_complexity = snapped_complexity + get_number_DL_snapped(float(j))

86
Code/S_add_snap_expr_on_pareto_polyfit.py
View file

@ -23,6 +23,8 @@ from sympy import preorder_traversal, count_ops
from sympy.abc import x,y
from sympy.parsing.sympy_parser import parse_expr
from sympy import Symbol, lambdify, N, simplify, powsimp, Rational, symbols, S, Float
import time
import re
from S_get_number_DL_snapped import get_number_DL_snapped
@ -33,6 +35,7 @@ def intify(expr):
# parameters: path to data, math (not RPN) expression
def add_snap_expr_on_pareto_polyfit(pathdir, filename, math_expr, PA):
input_data = np.loadtxt(pathdir+filename)
def unsnap_recur(expr, param_dict, unsnapped_param_dict):
"""Recursively transform each numerical value into a learnable parameter."""
import sympy
@ -95,85 +98,80 @@ def add_snap_expr_on_pareto_polyfit(pathdir, filename, math_expr, PA):
is_atomic_number = lambda expr:expr.is_Atom and expr.is_number
eq_numbers = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
# Do integer snap one parameter at a time
# Do integer snap one parameter at a time
integer_snapped_expr = []
for w in range(len(eq_numbers)):
try:
param_dict = {}
unsnapped_param_dict = {'p':1}
eq = unsnap_recur(expr,param_dict,unsnapped_param_dict)
del unsnapped_param_dict["p"]
temp_unsnapped_param_dict = copy.deepcopy(unsnapped_param_dict)
new_numbers = integerSnap(eq_numbers,w+1)
for kk in range(len(new_numbers)):
eq_numbers[new_numbers[kk][0]] = new_numbers[kk][1]
jj = 0
for parm in unsnapped_param_dict:
if parm!="p":
eq = eq.subs(parm, eq_numbers[jj])
jj = jj + 1
integer_snapped_expr = integer_snapped_expr + [eq]
new_numbers = {"p"+str(k): v for k, v in new_numbers.items()}
temp_unsnapped_param_dict.update(new_numbers)
#for kk in range(len(new_numbers)):
# eq_numbers[new_numbers[kk][0]] = new_numbers[kk][1]
new_eq = re.sub(r"(p\d*)",r"{\1}",str(eq))
new_eq = new_eq.format_map(temp_unsnapped_param_dict)
integer_snapped_expr = integer_snapped_expr + [parse_expr(new_eq)]
except:
continue
# Get the numbers appearing in the expression
# is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
# eq_numbers = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
eq_numbers = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
# # Do rational snap one parameter at a time
# rational_snapped_expr = []
# for w in range(len(eq_numbers)):
# try:
# eq_numbers_snap = copy.deepcopy(eq_numbers)
# param_dict = {}
# unsnapped_param_dict = {'p':1}
# eq = unsnap_recur(expr,param_dict,unsnapped_param_dict)
# new_numbers = rationalSnap(eq_numbers,w+1)
# for kk in range(len(new_numbers)):
# eq_numbers_snap[new_numbers[kk][0]] = new_numbers[kk][1][1:3]
# jj = 0
# for parm in unsnapped_param_dict:
# if parm!="p":
#
# try:
# eq = eq.subs(parm, Rational(eq_numbers_snap[jj][0],eq_numbers_snap[jj][1]))
# except:
# eq = eq.subs(parm, eq_numbers_snap[jj])
# jj = jj + 1
# rational_snapped_expr = rational_snapped_expr + [eq]
# except:
# continue
# Do rational snap one parameter at a time
rational_snapped_expr = []
for w in range(len(eq_numbers)):
try:
param_dict = {}
unsnapped_param_dict = {'p':1}
eq = unsnap_recur(expr,param_dict,unsnapped_param_dict)
del unsnapped_param_dict["p"]
temp_unsnapped_param_dict = copy.deepcopy(unsnapped_param_dict)
new_numbers = rationalSnap(eq_numbers,w+1)
new_numbers = {"p"+str(k): v for k, v in new_numbers.items()}
temp_unsnapped_param_dict.update(new_numbers)
#for kk in range(len(new_numbers)):
# eq_numbers_snap[new_numbers[kk][0]] = new_numbers[kk][1][1:3]
new_eq = re.sub(r"(p\d*)",r"{\1}",str(eq))
new_eq = new_eq.format_map(temp_unsnapped_param_dict)
rational_snapped_expr = rational_snapped_expr + [parse_expr(new_eq)]
except:
continue
# snapped_expr = np.append(integer_snapped_expr,zero_snapped_expr)
snapped_expr = np.append(integer_snapped_expr,rational_snapped_expr)
# snapped_expr = np.append(snapped_expr,rational_snapped_expr)
for i in range(len(integer_snapped_expr)):
integer_snapped_expr = snapped_expr
for i in range(len(snapped_expr)):
try:
# Calculate the error of the new, snapped expression
snapped_error = get_symbolic_expr_error(pathdir,filename,str(integer_snapped_expr[i]))
snapped_error = get_symbolic_expr_error(input_data,str(snapped_expr[i]))
# Calculate the complexity of the new, snapped expression
expr = simplify(powsimp(integer_snapped_expr[i]))
expr = snapped_expr[i]
for s in (expr.free_symbols):
s = symbols(str(s), real = True)
expr = simplify(parse_expr(str(integer_snapped_expr[i]),locals()))
expr = parse_expr(str(snapped_expr[i]),locals())
expr = intify(expr)
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
numbers_expr = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
snapped_complexity = 0
for j in numbers_expr:
snapped_complexity = snapped_complexity + get_number_DL_snapped(float(j))
# Add the complexity due to symbols
n_variables = len(expr.free_symbols)
n_operations = len(count_ops(expr,visual=True).free_symbols)
if n_operations!=0 or n_variables!=0:
snapped_complexity = snapped_complexity + (n_variables+n_operations)*np.log2((n_variables+n_operations))
PA.add(Point(x=snapped_complexity, y=snapped_error, data=str(expr)))
except:
continue
return(PA)

3
Code/S_add_sym_on_pareto.py
View file

@ -1,9 +1,6 @@
# Combines 2 pareto fromtier obtained from the separability test into a new one.
from get_pareto import Point, ParetoSet
from RPN_to_pytorch import RPN_to_pytorch
from RPN_to_eq import RPN_to_eq
from S_get_symbolic_expr_error import get_symbolic_expr_error
from sympy.parsing.sympy_parser import parse_expr
import numpy as np
import matplotlib.pyplot as plt

6
Code/S_combine_pareto.py
View file

@ -1,8 +1,6 @@
# Combines 2 pareto fromtier obtained from the separability test into a new one.
from get_pareto import Point, ParetoSet
from RPN_to_pytorch import RPN_to_pytorch
from RPN_to_eq import RPN_to_eq
from S_get_symbolic_expr_error import get_symbolic_expr_error
from sympy.parsing.sympy_parser import parse_expr
import numpy as np
@ -12,7 +10,7 @@ from os import path
from sympy import Symbol, lambdify, N
from get_pareto import Point, ParetoSet
def combine_pareto(pathdir,filename,PA1,PA2,idx_list_1,idx_list_2,PA,sep_type = "+"):
def combine_pareto(input_data,PA1,PA2,idx_list_1,idx_list_2,PA,sep_type = "+"):
possible_vars = ["x%s" %i for i in np.arange(0,30,1)]
PA1 = np.array(PA1.get_pareto_points()).astype('str')
PA2 = np.array(PA2.get_pareto_points()).astype('str')
@ -28,7 +26,7 @@ def combine_pareto(pathdir,filename,PA1,PA2,idx_list_1,idx_list_2,PA,sep_type =
for k in range(len(idx_list_2)-1,-1,-1):
exp2 = exp2.replace(possible_vars[k],possible_vars[idx_list_2[k]])
new_eq = "(" + exp1 + ")" + sep_type + "(" + exp2 + ")"
PA.add(Point(x=complexity,y=get_symbolic_expr_error(pathdir,filename,new_eq),data=new_eq))
PA.add(Point(x=complexity,y=get_symbolic_expr_error(input_data,new_eq),data=new_eq))
except:
continue
return PA

9
Code/S_final_gd.py
View file

@ -22,8 +22,7 @@ from S_get_number_DL_snapped import get_number_DL_snapped
from S_get_symbolic_expr_error import get_symbolic_expr_error
# parameters: path to data, RPN expression (obtained from bf)
def final_gd(pathdir,filename, math_expr, lr = 1e-2, N_epochs = 5000):
data_file = pathdir + filename
def final_gd(data, math_expr, lr = 1e-2, N_epochs = 5000):
param_dict = {}
unsnapped_param_dict = {'p':1}
@ -59,10 +58,6 @@ def final_gd(pathdir,filename, math_expr, lr = 1e-2, N_epochs = 5000):
new_key = "{}{}{}{}{}".format(key, underscore, midfix, i, suffix)
return new_key
# Load the actual data
data = np.loadtxt(data_file)
# Turn BF expression to pytorch expression
eq = parse_expr(math_expr)
eq = unsnap_recur(eq,param_dict,unsnapped_param_dict)
@ -146,7 +141,7 @@ def final_gd(pathdir,filename, math_expr, lr = 1e-2, N_epochs = 5000):
if n_operations!=0 or n_variables!=0:
complexity = complexity + (n_variables+n_operations)*np.log2((n_variables+n_operations))
error = get_symbolic_expr_error(pathdir,filename,str(eq))
error = get_symbolic_expr_error(data,str(eq))
return error, complexity, eq

19
Code/S_run_aifeynman.py
View file

@ -33,7 +33,8 @@ def run_AI_all(pathdir,filename,BF_try_time=60,BF_ops_file_type="14ops", polyfit
# load the data for different checks
data = np.loadtxt(pathdir+filename)
PA = get_atan(pathdir,"results/mystery_world_atan/",filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
'''
# Run bf and polyfit
PA = run_bf_polyfit(pathdir,pathdir,filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
@ -49,7 +50,7 @@ def run_AI_all(pathdir,filename,BF_try_time=60,BF_ops_file_type="14ops", polyfit
PA = get_sqrt(pathdir,"results/mystery_world_sqrt/",filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
PA = get_squared(pathdir,"results/mystery_world_squared/",filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
PA = get_tan(pathdir,"results/mystery_world_tan/",filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg)
'''
#############################################################################################################################
# check if the NN is trained. If it is not, train it on the data.
print("Checking for symmetry \n", filename)
@ -120,7 +121,8 @@ def run_AI_all(pathdir,filename,BF_try_time=60,BF_ops_file_type="14ops", polyfit
PA1 = run_AI_all(new_pathdir1,new_filename1,BF_try_time,BF_ops_file_type, polyfit_deg, NN_epochs, PA1_)
PA2_ = ParetoSet()
PA2 = run_AI_all(new_pathdir2,new_filename2,BF_try_time,BF_ops_file_type, polyfit_deg, NN_epochs, PA2_)
PA = combine_pareto(pathdir,filename,PA1,PA2,separability_plus_result[1],separability_plus_result[2],PA,"+")
combine_pareto_data = np.loadtxt(pathdir+filename)
PA = combine_pareto(combine_pareto_data,PA1,PA2,separability_plus_result[1],separability_plus_result[2],PA,"+")
return PA
elif idx_min == 5:
@ -129,7 +131,8 @@ def run_AI_all(pathdir,filename,BF_try_time=60,BF_ops_file_type="14ops", polyfit
PA1 = run_AI_all(new_pathdir1,new_filename1,BF_try_time,BF_ops_file_type, polyfit_deg, NN_epochs, PA1_)
PA2_ = ParetoSet()
PA2 = run_AI_all(new_pathdir2,new_filename2,BF_try_time,BF_ops_file_type, polyfit_deg, NN_epochs, PA2_)
PA = combine_pareto(pathdir,filename,PA1,PA2,separability_multiply_result[1],separability_multiply_result[2],PA,"*")
combine_pareto_data = np.loadtxt(pathdir+filename)
PA = combine_pareto(combine_pareto_data,PA1,PA2,separability_multiply_result[1],separability_multiply_result[2],PA,"*")
return PA
else:
return PA
@ -181,10 +184,11 @@ def run_aifeynman(pathdir,filename,BF_try_time,BF_ops_file_type, polyfit_deg=3,
PA_list = PA.get_pareto_points()
np.savetxt("results/solution_first_snap_%s.txt" %filename,PA_list,fmt="%s")
# Run gradient descent on the data one more time
# Run gradient descent on the data one more time
final_gd_data = np.loadtxt(pathdir+filename)
for i in range(len(PA_list)):
try:
gd_update = final_gd(pathdir,filename,PA_list[i][-1])
gd_update = final_gd(final_gd_data,PA_list[i][-1])
PA.add(Point(x=gd_update[1],y=gd_update[0],data=gd_update[2]))
except:
continue
@ -206,8 +210,9 @@ def run_aifeynman(pathdir,filename,BF_try_time,BF_ops_file_type, polyfit_deg=3,
# Try the found expressions on the test data
if DR_file=="" and test_data.size != 0:
test_errors = []
input_test_data = np.loadtxt(pathdir+filename+"_test")
for i in range(len(list_dt)):
test_errors = test_errors + [get_symbolic_expr_error(pathdir,filename+"_test",str(list_dt[i][-1]))]
test_errors = test_errors + [get_symbolic_expr_error(input_test_data,str(list_dt[i][-1]))]
test_errors = np.array(test_errors)
# Save all the data to file
save_data = np.column_stack((test_errors,log_err,log_err_all,list_dt))

14
Code/S_run_bf_polyfit.py
View file

@ -6,7 +6,6 @@ from RPN_to_eq import RPN_to_eq
import numpy as np
import matplotlib.pyplot as plt
from S_brute_force import brute_force
from S_combine_pareto import combine_pareto
from S_get_number_DL_snapped import get_number_DL_snapped
from sympy.parsing.sympy_parser import parse_expr
from sympy import preorder_traversal, count_ops
@ -19,7 +18,7 @@ from os import path
def run_bf_polyfit(pathdir,pathdir_transformed,filename,BF_try_time,BF_ops_file_type, PA, polyfit_deg=3, output_type=""):
input_data = np.loadtxt(pathdir_transformed+filename)
#############################################################################################################################
# run BF on the data (+)
@ -65,7 +64,7 @@ def run_bf_polyfit(pathdir,pathdir_transformed,filename,BF_try_time,BF_ops_file_
eqn = "atan(" + prefactors[i] + "+" + RPN_to_eq(express[i]) + ")"
eqns = eqns + [eqn]
errors = errors + [get_symbolic_expr_error(pathdir,filename,eqn)]
errors = errors + [get_symbolic_expr_error(input_data,eqn)]
expr = parse_expr(eqn)
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
numbers_expr = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
@ -92,7 +91,7 @@ def run_bf_polyfit(pathdir,pathdir_transformed,filename,BF_try_time,BF_ops_file_
# run gradient descent of BF output parameters and add the results to the Pareto plot
for i in range(len(express)):
try:
bf_gd_update = RPN_to_pytorch(pathdir,filename,eqns[i])
bf_gd_update = RPN_to_pytorch(input_data,eqns[i])
PA.add(Point(x=bf_gd_update[1],y=bf_gd_update[0],data=bf_gd_update[2]))
except:
continue
@ -143,7 +142,7 @@ def run_bf_polyfit(pathdir,pathdir_transformed,filename,BF_try_time,BF_ops_file_
eqn = "atan(" + prefactors[i] + "*" + RPN_to_eq(express[i]) + ")"
eqns = eqns + [eqn]
errors = errors + [get_symbolic_expr_error(pathdir,filename,eqn)]
errors = errors + [get_symbolic_expr_error(input_data,eqn)]
expr = parse_expr(eqn)
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
numbers_expr = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]
@ -171,12 +170,13 @@ def run_bf_polyfit(pathdir,pathdir_transformed,filename,BF_try_time,BF_ops_file_
# run gradient descent of BF output parameters and add the results to the Pareto plot
for i in range(len(express)):
try:
bf_gd_update = RPN_to_pytorch(pathdir,filename,eqns[i])
bf_gd_update = RPN_to_pytorch(input_data,eqns[i])
PA.add(Point(x=bf_gd_update[1],y=bf_gd_update[0],data=bf_gd_update[2]))
except:
continue
except:
pass
#############################################################################################################################
# run polyfit on the data
print("Checking polyfit \n")
@ -210,7 +210,7 @@ def run_bf_polyfit(pathdir,pathdir_transformed,filename,BF_try_time,BF_ops_file_
elif output_type=="tan":
eqn = "atan(" + eqn + ")"
polyfit_err = get_symbolic_expr_error(pathdir,filename,eqn)
polyfit_err = get_symbolic_expr_error(input_data,eqn)
expr = parse_expr(eqn)
is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
numbers_expr = [subexpression for subexpression in preorder_traversal(expr) if is_atomic_number(subexpression)]

6
Code/S_snap.py
View file

@ -60,14 +60,14 @@ def integerSnap(p, top=1):
p = np.array(p)
metric = np.abs(p - np.round(p.astype(np.double)))
chosen = np.argsort(metric)[:top]
return list(zip(chosen, np.round(p.astype(np.double))[chosen]))
return dict(list(zip(chosen, np.round(p.astype(np.double))[chosen])))
def zeroSnap(p, top=1):
p = np.array(p)
metric = np.abs(p)
chosen = np.argsort(metric)[:top]
return list(zip(chosen, np.zeros(len(chosen))))
return dict(list(zip(chosen, np.zeros(len(chosen)))))
def rationalSnap(p, top=1):
@ -75,4 +75,4 @@ def rationalSnap(p, top=1):
p = np.array(p)
snaps = np.array(list(bestApproximation(x,100) for x in p))
chosen = np.argsort(snaps[:, 3])[:top]
return list(zip(chosen, snaps[chosen, 0:3]))
return dict(list(zip(chosen, snaps[chosen, 0:3])))