# MODEL 3
par_na = np.ones((r,r)) * 2
par_nb = np.ones((r,m)) * 2
# in data > roll rows 1 up and duplicate last row
U = np.roll(U,-1,axis=0)
U[:][-1] = U[:][-2]
mdl3 = lspv(U,Y,par_na,par_nb)
Ym3 = lspv_apl(U,Y,mdl3,par_na,par_nb)
# MODEL 4
# replaces all negative values with 0
Ym4 = Ym3.clip(min=0)
n = int(max( (par_na.max(),par_nb.max())))
vaf_model_1 = vaf( Y[n:][:], Ym1)
vaf_model_2 = vaf( Y[(n):][:], Ym2)
vaf_model_3 = vaf( Y[(n):][:], Ym3)
vaf_model_4 = vaf( Y[(n):][:], Ym4)
# moje da se oformi tablica s matplotlib
print ('VAF MODEL 1')
for item in vaf_model_1:
print ("--",item.round(3),"--",end='\n')
print ('\nVAF MODEL 2')
for item in vaf_model_2:
print ("--",item.round(3),"--",end='\n')
print ('\nVAF MODEL 3')
for item in vaf_model_3:
# MODEL 2
opt_maxiter = 50
opt_taux = 10**(-6)
opt_tauf = 10**(-6)
opt_dsp = 0
# the list contains the matrix E and a vector Pm
elspm_list = elspm(U, Y, par_na, par_nb, par_nc)
E = elspm_list[0]
Pm = mdl2 = elspm_list[1]
Ym2 = elspm_apl(U, Y, Pm, par_na, par_nb, par_nc, E)
n = int(max((par_na, par_nb, par_nc)))
vaf_model_1 = vaf(Y[n:][:], Ym1)
print('VAF MODEL 1')
for item in vaf_model_1:
print("--", item.round(3), "--", end='\n')
vaf_model_2 = vaf(Y[n:][:], Ym2)
print('VAF MODEL 2')
for item in vaf_model_2:
print("--", item.round(3), "--", end='\n')
# plot Y vs Y from Models
for col in range(0, Y.shape[1]):
title = str('Product ' + str(col + 1))
plt.figure(col)
def roblspm(
U,Y,par_na,par_nb,
opt_dvaf = 10**(-2),
opt_max_iter = 100,
opt_hst = 0):
import numpy as np
from dmpm import dmpm
from vaf import vaf
from pm2v import pm2v
r = (Y.shape)[1]
m = (U.shape)[1]
na = par_na
nb = par_nb
n = max(na,nb)
# DATA MATRIX CREATION
F = dmpm(U,Y,na,nb)
# CODE IN MATLAB
# Y = Y(n + 1:end, :);
Y = Y[n:,:]
# CODE IN MATLAB
# Pm = (F'*F)^-1*F'*Y;
# FIRST
# (F'*F)
F_transposed = F.transpose()
first = np.dot(F_transposed,F)
# SECOND
# (F'*F)^-1
second = np.linalg.inv(first)
# THIRD
# F'*Y
third = np.dot(F_transposed,Y)
# FOURTH
# (F'*F)^-1*F'*Y;
fourth = np.dot(second,third)
Pm = fourth
# CODE IN MATLAB
# Ym = F*Pm;
Ym = np.dot(F,Pm)
vafw = vaf(Y,Ym)
vaf0 = vafw
# NEW VARIABLES
if opt_hst:
VAFw = vafw
VAFw = VAFw.reshape(-1,1)
VAF = vaf0
VAF = VAF.reshape(-1,1)
PM = pm2v(Pm,par_na,par_nb)
PM = PM.reshape(-1,1)
YM = Ym.flatten()
YM = YM.reshape(-1,1)
# -------------------------------------------------------------------
# START OF ITERATION LOOP
iter = 0
iterate = True
while iterate:
iter += 1
# ----------------------------------------------------------------
# CODE IN MATLAB
# ww = min(1, max(1e-8, abs(Y - Ym).^-1));
# abs(y - ym).^-1
first = np.absolute(np.subtract(Y,Ym))
first = np.power(first,(-1))
# max(1e-8, first)
second = np.clip(first, a_min = 10**(-8), a_max = np.max(first))
# min(1,second)
third = np.clip(second, a_min = np.min(first), a_max = 1)
ww = third
# ----------------------------------------------------------------
for i in range(0,r):
# Wi = repmat(ww(:, i), 1, r*na + m*nb);
vctr = ww[:,i]
Wi = np.tile(vctr,((r*na + m*nb),1)).transpose()
# Pm(:, i) = (F'*(Wi.*F))^-1*F'*(ww(:, i).*Y(:, i));
# first = (F'*(Wi.*F))^-1
first_1 = F.transpose()
first_2 = np.multiply(Wi,F)
first_3 = np.dot(first_1,first_2)
first_4 = np.linalg.inv(first_3)
first = first_4
# second = F'
second = F.transpose()
# third = (ww(:, i).*Y(:, i))
third_1 = ww[:,i]
third_2 = Y[:,i]
third = np.multiply(third_1,third_2)
# forming Pm
Pm_1 = np.dot(first,second)
Pm_2 = np.dot(Pm_1,third)
Pm_final = Pm_2
Pm[:,i] = Pm_final
Ym = np.dot(F,Pm)
vafw_1 = vafw
vafw = vaf(Y,Ym,ww)
vaf0 = vaf(Y,Ym)
if opt_hst :
# appending values to arrays
to_append = pm2v(Pm,par_na,par_nb).reshape(-1,1)
PM = np.append(PM,to_append,axis = 1)
vafw = vafw.reshape(-1,1)
VAFw = np.append(VAFw,vafw,axis = 1)
vaf0 = vaf0.reshape(-1,1)
VAF = np.append(VAF,vaf0,axis = 1)
to_append = Ym.transpose().flatten('F').reshape(-1,1)
YM = np.append(YM,to_append,axis = 1)
# CHECK FOR END CONDITION
# CODE IN MATLAB
# if any(abs(vafw - vafw_1)) <= dvaf || iter >= maxIter,
if iter >= opt_max_iter:
iterate = False
else:
# creating abs(vafw - vafw_1)
vafw_differences = abs(np.subtract(vafw,vafw_1))
for row in vafw_differences:
for item in row:
if item <= opt_dvaf:
iterate = False
print("The function [roblspm.py] took",iter,"iterations to reach the end condition.")
# CREATE RETURN LIST
return_list = [PM,VAFw,VAF,YM,Pm]
return return_list
mdl = lspv(U, Y, par_na, par_nb)
Ym1 = lspv_apl(U, Y, mdl, par_na, par_nb)
# MODEL 1 ROB LS
# roblspv returns a list of NumPy arrays which are later unpacked
model_list = roblspv(U, Y, par_na, par_nb, opt_dvaf, opt_max_iter, opt_hst)
# return_list = [PM,VAFw,VAF,YM,pm]
mdl_PM = model_list[0]
mdl_VAFW = model_list[1]
mdl_VAF = model_list[2]
mdl_YM = model_list[3]
mdl_pm = model_list[4]
Ym2 = lspv_apl(U, Y, mdl_pm, par_na, par_nb)
vaf_model_1 = vaf(Y[a + n:][:], Ym1[a:][:])
print('VAF MODEL 1')
for item in vaf_model_1:
print("--", item.round(3), "--", end='\n')
test_1 = Y[a + n:][:]
test_2 = Ym2[a:][:]
vaf_model_2 = vaf(Y[a + n:][:], Ym2[a:][:])
print('VAF MODEL 2')
for item in vaf_model_2:
print("--", item.round(3), "--", end='\n')
# ADDITIONAL PLOT
#plt.figure()
def roblspv(U,
Y,
par_na,
par_nb,
opt_dvaf=10**(-2),
opt_max_iter=100,
opt_hst=0):
import numpy as np
from numpy import linalg
from dmpv import dmpv
from vaf import vaf
from dv2dm import dv2dm
r = (Y.shape)[1]
na = par_na
nb = par_nb
n = max(int(np.max(par_na)), int(np.max(par_nb)))
# DATA MATRIX CREATION
F = dmpv(U, Y, par_na, par_nb)
# CODE IN MATLAB
# pm = (F'*F)^-1 * F' * vec( Y(n + 1:end, :)');
# first (F'*F)^-1
first = np.dot(F.transpose(), F)
first = np.linalg.inv(first)
# second F'
second = F.transpose()
# third vec( Y(n + 1:end, :)')
y = Y[(n):][:]
y = y.transpose()
y = y.flatten('F')
y = y.reshape(-1, 1)
pm = np.dot(first, second)
pm = np.dot(pm, y)
ym = np.dot(F, pm)
first = dv2dm(y, r)
second = dv2dm(ym, r)
vafw = vaf(first, second)
vaf0 = vafw
# NEW VARIABLES
if opt_hst:
VAFw = vafw
VAFw = VAFw.reshape(-1, 1)
VAF = vaf0
VAF = VAF.reshape(-1, 1)
PM = pm
PM = PM.reshape(-1, 1)
YM = ym
YM = YM.reshape(-1, 1)
# -------------------------------------------------------------------
# START OF ITERATION LOOP
iter = 0
iterate = True
while iterate:
print("THIS IS ITERATION", iter + 1)
iter += 1
# ----------------------------------------------------------------
# CODE IN MATLAB
# w = min(1, max(1e-8, abs(y - ym).^-1));
# abs(y - ym).^-1
first = np.absolute(np.subtract(y, ym))
first = np.power(first, (-1))
# max(1e-8, first)
second = np.clip(first, a_min=10**(-8), a_max=np.max(first))
# min(1,second)
third = np.clip(second, a_min=np.min(first), a_max=1)
w = third
# ----------------------------------------------------------------
# CODE IN MATLAB
# ww = repmatc(w, size(F, 2));
ww = np.broadcast_to(w, shape=(2176, F.shape[1]))
# ----------------------------------------------------------------
# CODE IN MATLAB
# pm = (F'*(ww.*F))^-1*(ww.*F)'*y;
# (F'*(ww.*F))^-1
first = F.transpose()
second = np.multiply(ww, F)
third = np.dot(first, second)
fourth = np.linalg.inv(third)
# (ww.*F)'*y
first = np.multiply(ww, F).transpose()
second = np.dot(first, y)
pm = np.dot(fourth, second)
pm = pm.reshape(-1, 1)
# ----------------------------------------------------------------
# CODE IN MATLAB
# ym = F*pm;
ym = np.dot(F, pm)
ym = ym.reshape(-1, 1)
vafw_1 = vafw
# CODE IN MATLAB
# vafw = vaf(dv2dm(y, r), dv2dm(ym, r), dv2dm(w, r));
# vafw = vaf(Y , Ym , w );
vaf_arg_1 = dv2dm(y, r)
vaf_arg_2 = dv2dm(ym, r)
vaf_arg_3 = dv2dm(w, r)
# vaf_weights FUNCTION NEEDED
vafw = vaf(vaf_arg_1, vaf_arg_2, vaf_arg_3)
vafw = vafw.reshape(-1, 1)
# CODE IN MATLAB
# vaf0 = vaf(dv2dm(y, r), dv2dm(ym, r));
vaf0 = vaf(vaf_arg_1, vaf_arg_2)
vaf0 = vaf0.reshape(-1, 1)
if opt_hst:
# appending values to arrays
PM = np.append(PM, pm, axis=1)
VAFw = np.append(VAFw, vafw, axis=1)
VAF = np.append(VAF, vaf0, axis=1)
YM = np.append(YM, ym, axis=1)
# CHECK FOR END CONDITION
# CODE IN MATLAB
# if any(abs(vafw - vafw_1)) <= dvaf || iter >= maxIter,
if iter >= opt_max_iter:
iterate = False
else:
# creating abs(vafw - vafw_1)
vafw_differences = abs(np.subtract(vafw, vafw_1))
for row in vafw_differences:
for item in row:
if item <= opt_dvaf:
iterate = False
# CREATE RETURN LIST
return_list = [PM, VAFw, VAF, YM, pm]
return return_list