#% matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from fuzzython.fsets.triangular import Triangular
from fuzzython.variable import Variable
from fuzzython.adjective import Adjective
from fuzzython.ruleblock import RuleBlock
from fuzzython.norms import norms

n_p_tanio=Triangular((0.99,1),(1,0),(10,1))
p_tanio=n_p_tanio.complement(cnorm=norms.zadeh_complement)
p_srednio1=Triangular((5,0),(8.25,1),(12.5,0))
p_srednio2=Triangular((7.5,0),(12.25,1),(15,0))
p_srednio=p_moderate1.union(p_srednio2,snorm=norms.algebraic_sum)
p_drogo=Triangular((10,0),(20,1),(20.1,0))

a_p_tanio = Adjective('p_tanio', p_tanio)
a_p_srednio = Adjective('p_srednio', p_srednio)
a_p_drogo = Adjective('p_drogo', p_drogo)

a_p_tanio2 = Adjective('p_tanio', p_tanio)
a_p_srednio2 = Adjective('p_srednio', p_srednio2)
a_p_drogo2 = Adjective('p_drogo', p_drogo)


cena_dzis = Variable('cena_dzis', 'zł', a_p_tanio, a_p_srednio, a_p_drogo)
cena_wczoraj = Variable('cena_wczoraj', 'zł', a_p_tanio2, a_p_srednio2, a_p_drogo2)

cena_dzis2 = Variable('cena_dzis2', 'zł', a_p_tanio, a_p_srednio, a_p_drogo, defuzzification='COA')
cena_wczoraj2 = Variable('cena_wczoraj2', 'zł', a_p_tanio2, a_p_srednio2, a_p_drogo2, defuzzification='MM',default=0)

scope = locals()

rule4a = 'if cena_wczoraj is a_p_tanio2 and cena_dzis is a_p_tanio then z=cena_dzis*0.5+cena_wczoraj*0.5+1'
rule4b = 'if cena_wczoraj is a_p_tanio2 and cena_dzis is a_p_srednio then z=cena_dzis*0.6+cena_wczoraj*0.4+1'
rule4c = 'if cena_wczoraj is a_p_tanio2 and cena_dzis is a_p_drogo then z=cena_dzis*0.8+cena_wczoraj*0.2+1'

rule5a = 'if cena_wczoraj is a_p_srednio2 and cena_dzis is a_p_tanio then z=0.6*cena_dzis+0.4*cena_wczoraj+1'
rule5b = 'if cena_wczoraj is a_p_srednio2 and cena_dzis is a_p_srednio then z=cena_dzis*0.5+cena_wczoraj*0.5+1'
rule5c = 'if cena_wczoraj is a_p_srednio2 and cena_dzis is a_p_drogo then z=0.6*cena_dzis+0.4*cena_wczoraj+1'

rule6a = 'if cena_wczoraj is a_p_drogo2 and cena_dzis is a_p_tanio then z=0.8*cena_dzis+0.2*cena_wczoraj+1'
rule6b = 'if cena_wczoraj is a_p_drogo2 and cena_dzis is a_p_srednio then z=0.6*cena_dzis+0.4*cena_wczoraj+1'
rule6c = 'if cena_wczoraj is a_p_drogo2 and cena_dzis is a_p_drogo then z=cena_dzis*0.5+cena_wczoraj*0.5+1'

block1 = RuleBlock('rb_takagi1', operators=('MIN', 'MAX', 'ZADEH'), activation='MIN', accumulation='MAX')
block1.add_rules(rule4a,rule4b,rule4c,rule5a,rule5b,rule5c,rule6a,rule6b,rule6c, scope=scope)

block2 = RuleBlock('rb_takagi2', operators=('PROD', 'ASUM', 'SUGENO'), activation='PROD', accumulation='ASUM')
block2.add_rules(rule4a,rule4b,rule4c,rule5a,rule5b,rule5c,rule6a,rule6b,rule6c, scope=scope)

block3 = RuleBlock('rb_takagi3', operators=('BDIF', 'MAX', 'SUGENO'), activation='BDIF', accumulation='MAX')
block3.add_rules(rule4a,rule4b,rule4c,rule5a,rule5b,rule5c,rule6a,rule6b,rule6c, scope=scope)

rule1a = 'if cena_wczoraj2 is a_p_tanio2 and cena_dzis2 is a_p_tanio then z=cena_dzis2*0.5+cena_wczoraj2*0.5+1'
rule1b = 'if cena_wczoraj2 is a_p_tanio2 and cena_dzis2 is a_p_srednio then z=cena_dzis2*0.6+cena_wczoraj2*0.4+1'
rule1c = 'if cena_wczoraj2 is a_p_tanio2 and cena_dzis2 is a_p_drogo then z=cena_dzis2*0.8+cena_wczoraj2*0.2+1'

rule2a = 'if cena_wczoraj2 is a_p_srednio2 and cena_dzis2 is a_p_tanio then z=0.6*cena_dzis2+0.4*cena_wczoraj2+1'
rule2b = 'if cena_wczoraj2 is a_p_srednio2 and cena_dzis2 is a_p_srednio then z=cena_dzis2*0.5+cena_wczoraj2*0.5+1'
rule2c = 'if cena_wczoraj2 is a_p_srednio2 and cena_dzis2 is a_p_drogo then z=0.6*cena_dzis2+0.4*cena_wczoraj2+1'

rule3a = 'if cena_wczoraj2 is a_p_drogo2 and cena_dzis2 is a_p_tanio then z=0.8*cena_dzis2+0.2*cena_wczoraj2+1'
rule3b = 'if cena_wczoraj2 is a_p_drogo2 and cena_dzis2 is a_p_srednio then z=0.6*cena_dzis2+0.4*cena_wczoraj2+1'
rule3c = 'if cena_wczoraj2 is a_p_drogo2 and cena_dzis2 is a_p_drogo then z=cena_dzis2*0.5+cena_wczoraj2*0.5+1'

block4 = RuleBlock('rb_takagi4', operators=('EPROD', 'ESUM', 'ZADEH'), activation='EPROD', accumulation='ESUM')
block4.add_rules(rule1a,rule1b,rule1c,rule2a,rule2b,rule2c,rule3a,rule3b,rule3c, scope=scope)

from fuzzython.systems.sugeno import SugenoSystem

sugeno1 = SugenoSystem('model_takagi1', block1)
sugeno2 = SugenoSystem('model_takagi2', block2)
sugeno3 = SugenoSystem('model_takagi3', block3)
sugeno4 = SugenoSystem('model_takagi4', block4)

# dane wejściowe
inputs = {'cena_dzis': 6, 'cena_wczoraj': 14}
# obliczenie odpowiedzi
res1 = sugeno1.compute(inputs)
res2 = sugeno2.compute(inputs)
res3 = sugeno3.compute(inputs)

inputs2 = {'cena_dzis2': 6, 'cena_wczoraj2': 14}
res4 = sugeno4.compute(inputs2)
# zwraca słownik, trochę inaczej niż w mamdani
print(res1,res2,res3,res4)

# przygotowanie siatki
sampled = np.linspace(1, 20, 50)
x, y = np.meshgrid(sampled, sampled)
z1 = np.zeros((len(sampled),len(sampled)))
z2 = np.zeros((len(sampled),len(sampled)))
z3 = np.zeros((len(sampled),len(sampled)))
z4 = np.zeros((len(sampled),len(sampled)))

for i in range(len(sampled)):
    for j in range(len(sampled)):
        inputs = {'cena_dzis': x[i, j], 'cena_wczoraj': y[i, j]}
        inputs2 = {'cena_dzis2': x[i, j], 'cena_wczoraj2': y[i, j]}
        res1 = sugeno1.compute(inputs)
        res2 = sugeno2.compute(inputs)
        res3 = sugeno3.compute(inputs)
        res4 = sugeno4.compute(inputs2)
        z1[i, j] = res1['rb_takagi1']
        z2[i, j] = res2['rb_takagi2']
        z3[i, j] = res3['rb_takagi3']
        z4[i, j] = res4['rb_takagi4']

fig1 = plt.figure()
ax1 = fig1.add_subplot(111, projection='3d')
surf = ax1.plot_surface(x, y, z1, rstride=1, cstride=1, cmap='viridis', linewidth=0.4, antialiased=True)
cset = ax1.contourf(x, y, z1, zdir='z', offset= -1, cmap='viridis', alpha=0.5)
cset = ax1.contourf(x, y, z1, zdir='x', offset= 11, cmap='viridis', alpha=0.5)
cset = ax1.contourf(x, y, z1, zdir='y', offset= 11, cmap='viridis', alpha=0.5)
ax1.set_xlabel('cena_dzis')
ax1.set_ylabel('cena_wczoraj')
ax1.set_zlabel('cena_jutro')
ax1.view_init(30, 200)

fig2 = plt.figure()
ax2 = fig2.add_subplot(111, projection='3d')
surf = ax2.plot_surface(x, y, z2, rstride=1, cstride=1, cmap='viridis', linewidth=0.4, antialiased=True)
cset = ax2.contourf(x, y, z2, zdir='z', offset= -1, cmap='viridis', alpha=0.5)
cset = ax2.contourf(x, y, z2, zdir='x', offset= 11, cmap='viridis', alpha=0.5)
cset = ax2.contourf(x, y, z2, zdir='y', offset= 11, cmap='viridis', alpha=0.5)
ax2.set_xlabel('cena_dzis')
ax2.set_ylabel('cena_wczoraj')
ax2.set_zlabel('cena_jutro')
ax2.view_init(30, 200)

fig3 = plt.figure()
ax3 = fig3.add_subplot(111, projection='3d')
surf = ax3.plot_surface(x, y, z3, rstride=1, cstride=1, cmap='viridis', linewidth=0.4, antialiased=True)
cset = ax3.contourf(x, y, z3, zdir='z', offset= -1, cmap='viridis', alpha=0.5)
cset = ax3.contourf(x, y, z3, zdir='x', offset= 11, cmap='viridis', alpha=0.5)
cset = ax3.contourf(x, y, z3, zdir='y', offset= 11, cmap='viridis', alpha=0.5)
ax3.set_xlabel('cena_dzis')
ax3.set_ylabel('cena_wczoraj')
ax3.set_zlabel('cena_jutro')
ax3.view_init(30, 200)

fig4 = plt.figure()
ax4 = fig4.add_subplot(111, projection='3d')
surf = ax4.plot_surface(x, y, z4, rstride=1, cstride=1, cmap='viridis', linewidth=0.4, antialiased=True)
cset = ax4.contourf(x, y, z4, zdir='z', offset= -1, cmap='viridis', alpha=0.5)
cset = ax4.contourf(x, y, z4, zdir='x', offset= 11, cmap='viridis', alpha=0.5)
cset = ax4.contourf(x, y, z4, zdir='y', offset= 11, cmap='viridis', alpha=0.5)
ax4.set_xlabel('cena_dzis')
ax4.set_ylabel('cena_wczoraj')
ax4.set_zlabel('cena_jutro')
ax4.view_init(30, 200)