def _plot(self,
x,
y,
labels=None,
x_label='Return [%]',
y_label='-',
title='Backtesting results',
plot_title='',
xlim=None,
ylim=None,
pres_name=None):
if pres_name is None:
pres_name = self.presname
pres = Presenter(pres_name)
fig = plt.figure()
plt.scatter(x, y)
if xlim is not None:
plt.xlim(xlim)
if ylim is not None:
plt.ylim(ylim)
plt.xlabel(x_label)
plt.ylabel(y_label)
plt.title(plot_title)
plt.grid()
img_path = 'temp.png'
plt.savefig(img_path)
plt.close(fig)
pres.add_picture_slide(img_path, title=title)
pres.save_presentation(pres_name)
def _bcbcg_blbcg_least_square_exp_b(self):
""" """
self._BB_6 = np.random.random( ( self._mat.shape[0],6) )
self._BX_6 = np.ones ( (self._mat.shape[1],6) )
#line 1
blbcg_solver_obj = BLBCG()
self._final_x_blbcg_m6s6, self._final_r_blbcg_m6s6, self._residual_hist_blbcg_m6s6 = \
blbcg_solver_obj.blbcg_solver_least_square(self._mat, self._BB_6, self._BX_6, 6, self._tol, self._maxiter, 0)
#line 2
blbcg_solver_obj = BLBCG()
self._final_x_blbcg_m6s12, self._final_r_blbcg_m6s12, self._residual_hist_blbcg_m6s12 = \
blbcg_solver_obj.blbcg_solver_least_square(self._mat, self._BB_6, self._BX_6, 12, self._tol, self._maxiter, 0)
#line 3
bcbcg_solver_obj = BCBCG()
self._final_x_bcbcg_m6s6, self._final_r_bcbcg_m6s6, self._residual_hist_bcbcg_m6s6 = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_6, self._BX_6, 6, self._tol, self._maxiter, 0)
#line 4
bcbcg_solver_obj = BCBCG()
self._final_x_bcbcg_m6s12, self._final_r_bcbcg_m6s12, self._residual_hist_bcbcg_m6s12 = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_6, self._BX_6, 12, self._tol, self._maxiter, 0)
plot_worker = Presenter()
residual_list = [self._residual_hist_blbcg_m6s6, self._residual_hist_blbcg_m6s12, \
self._residual_hist_bcbcg_m6s6, self._residual_hist_bcbcg_m6s12 ]
legend_list = ["blbcg_m6s6", "blbcg_m6s12", "bcbcg_m6s6", "bcbcg_m6s12"]
color_list = ["r","k","b","y"]
#plot_worker.instant_plot_y_log10(residual_list, "Chem97ZtZ", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
plot_worker.instant_plot_y_log10(residual_list, "test", "#iteration", "$\\mathbf{log_{10}\\frac{||x_1||}{||b_1||}}$", legend_list, color_list)
def _cg_bcg_exp(self, block_size):
""" """
print("_cg_bcg_bcbcg_least_square_exp starting, ... ")
self._BB_1 = np.random.random((self._mat.shape[0], 1))
self._BX_1 = np.ones((self._mat.shape[1], 1))
self._BB_X = np.random.random((self._mat.shape[0], block_size))
self._BX_X = np.ones((self._mat.shape[1], block_size))
#line 1
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_1,
self._BB_1, self._tol,
self._maxiter)
self._final_X_cg, self._final_R_cg, self._residual_hist_cg = bcg_solver_obj.bcg_variant_lstsq_run(
0)
##line 2
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_X,
self._BB_X, self._tol,
self._maxiter)
self._final_X_bcg_mX, self._final_R_bcg_mX, self._residual_hist_bcg_mX = bcg_solver_obj.bcg_variant_lstsq_run(
0)
plot_worker = Presenter()
residual_list = [self._residual_hist_cg, self._residual_hist_bcg_mX]
legend_list = ["cg", "bcg_m" + str(block_size)]
color_list = ["r", "k"]
plot_worker.instant_plot_y_log10(
residual_list, "MG", "#iteration",
"$\\mathbf{log_{10}\\frac{||r_1||}{||b_1||}}$", legend_list,
color_list)
def main():
"""MVP architecture to separate logic from interface"""
_view = View()
_presenter = Presenter(_view)
_view.set_presenter(_presenter)
_presenter.run()
def legendre_poly_exp_a(self, order_lo, order_hi):
""" """
x = np.linspace(-1.1, 1.1, 41)
order_controller = np.zeros(order_hi + 1)
y_list = []
plot_worker = Presenter()
legend_list = []
color_list = []
for order_idx in range(order_lo, order_hi + 1):
order_controller[order_idx] = 1
legp = np.polynomial.legendre.Legendre(order_controller)
legcoef = np.polynomial.legendre.leg2poly(legp.coef)
poly = np.polynomial.Polynomial(legcoef)
y_list.append(poly(x))
print(order_idx, " ", poly(x))
legend_list.append("order_" + str(order_idx))
color_list.append("k")
order_controller[order_idx] = 0
plot_worker.instant_plot_unified_x_axis(x, y_list, "Legendre Poly",
"x", "y", legend_list,
color_list)
def _lbcg_least_square_exp(self):
""" """
lbcg_solver_obj = LBCG()
self._final_x_a, self._final_r_a, self._residual_hist_a = \
lbcg_solver_obj.lbcg_solver_least_square(self._mat, self._SB, self._SX, 8, self._tol, self._maxiter)
self._final_x_b, self._final_r_b, self._residual_hist_b = \
lbcg_solver_obj.lbcg_solver_least_square(self._mat, self._SB, self._SX, 18, self._tol, self._maxiter)
cbcg_solver_obj = CBCG()
self._final_x_c, self._final_r_c, self._residual_hist_c = \
cbcg_solver_obj.cbcg_solver_least_square(self._mat, self._SB, self._SX, 8, self._tol, self._maxiter)
self._final_x_d, self._final_r_d, self._residual_hist_d = \
cbcg_solver_obj.cbcg_solver_least_square(self._mat, self._SB, self._SX, 18, self._tol, self._maxiter)
plot_worker = Presenter()
residual_list = [
self._residual_hist_a, self._residual_hist_b,
self._residual_hist_c, self._residual_hist_d
]
legend_list = [
"lbcg_lstsq_s8", "lbcg_lstsq_s18", "cbcg_lstsq_s8",
"cbcg_lstsq_s18"
]
color_list = ["r", "k", "b", "y"]
#plot_worker.instant_plot_y_log10(residual_list, "crystm01", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
#plot_worker.instant_plot_y_log10(residual_list, "wathen100", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
plot_worker.instant_plot_y_log10(residual_list, "bodyy06",
"#iteration",
"$\\frac{||x_1||}{||b_1||}$",
legend_list, color_list)
def _cm_plot(self,
x,
y,
labels=None,
x_label='Transaction Value [monetary unit]',
y_label='Transaction Costs [monetary unit]',
title='Transaction costs',
plot_title=''):
pres = Presenter(self.presname)
fig = plt.figure()
if isinstance(y[0], np.ndarray) | isinstance(y[0], list):
for i in range(0, len(y)):
plt.plot(x, y[i], label=labels[i])
plt.legend(loc='upper left')
else:
plt.plot(x, y, 'b', label=labels)
if labels is not None:
plt.legend(loc='upper left')
plt.xlabel(x_label)
plt.ylabel(y_label)
plt.title(plot_title)
img_path = 'temp.png'
plt.savefig(img_path)
plt.close(fig)
pres.add_picture_slide(img_path, title=title)
pres.save_presentation(self.presname)
os.remove(img_path)
def chebyshev_poly_exp_a(self, order_lo, order_hi):
""" """
x = np.linspace(-1.1, 1.1, 41)
order_controller = np.zeros(order_hi + 1)
y_list = []
plot_worker = Presenter()
legend_list = []
color_list = []
for order_idx in range(order_lo, order_hi + 1):
order_controller[order_idx] = 1
cheb = np.polynomial.chebyshev.Chebyshev(order_controller)
choef = np.polynomial.chebyshev.cheb2poly(cheb.coef)
poly = np.polynomial.Polynomial(choef)
y_list.append(poly(x))
print(order_idx, " ", poly(x))
legend_list.append("order_" + str(order_idx))
color_list.append("k")
order_controller[order_idx] = 0
plot_worker.instant_plot_unified_x_axis(x, y_list, "chebyshev Poly",
"x", "y", legend_list,
color_list)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.presenter = Presenter()
self.setGeometry(200, 200, 300, 300)
self.setWindowTitle("Qt Window example")
self.initUI()
self.show()
def main():
# view = View()
# dim_view = DimensionalView(view.drawing_area_dimensional.get_allocation().width,view.drawing_area_dimensional.get_allocation().height)
# comp_view = ComplexView(view.drawing_area_complex.get_allocation().width,view.drawing_area_complex.get_allocation().height)
app = QApplication(sys.argv)
p = Presenter()
p.show()
app.exec_()
def __init__(self):
super(Multiply, self).__init__()
self.resize(400, 300)
self.view = MainWindow(self)
self.presenter = Presenter(self.view, MultiplyModel, ResetModel)
self.view.inputChanged.connect(self.presenter.onInputChanged)
self.view.resetClicked.connect(self.presenter.resetToZero)
def _db_presenter_a(self):
plot_worker = Presenter()
residual_list = [self._residual_hist_a]
residual_list.append(self._residual_hist_b)
legend_list = ["bcbcg_s3", "bcbcg_s5"]
color_list = ["r", "k"]
# latex style notation
#plot_worker.instant_plot_y_log10(residual_list, "crystm01 $x_1$")
#plot_worker.instant_plot_y_log10(residual_list, "crystm01", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
plot_worker.instant_plot_y(residual_list, "crystm01", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
def _pc_lbcg_vs_cbcg(self):
""" """
#print(self._mat)
self._pc_jacobi = diags(self._mat.diagonal())
#print ("")
#print ("dia")
#print(self._pc_jacobi)
self._pc_jacobi = np.sqrt(self._pc_jacobi)
#print ("")
#print(self._pc_jacobi)
self._pc_jacobi = inv(self._pc_jacobi)
#print ("")
#print ("inverse")
#print(self._pc_jacobi)
#print(type(self._pc_jacobi))
self._left_pcd_mat = aslinearoperator(self._pc_jacobi)(
self._mat.toarray())
#print ("")
#print ("left pcd")
self._pcd_mat = np.matmul(self._left_pcd_mat,
self._pc_jacobi.toarray())
#print ("")
#print (csr_matrix(self._pcd_mat).diagonal())
#print ("mat cond:", np.linalg.cond(self._mat.toarray()))
#print ("pcd_mat cond:", np.linalg.cond(self._pcd_mat))
self._pcd_mat = csr_matrix(self._pcd_mat)
lbcg_solver_obj = LBCG()
self._final_x_a, self._final_r_a, self._residual_hist_a = \
lbcg_solver_obj.lbcg_solver_least_square(self._pcd_mat, self._SB, self._SX, 8, self._tol, self._maxiter)
self._final_x_b, self._final_r_b, self._residual_hist_b = \
lbcg_solver_obj.lbcg_solver_least_square(self._pcd_mat, self._SB, self._SX, 18, self._tol, self._maxiter)
cbcg_solver_obj = CBCG()
self._final_x_c, self._final_r_c, self._residual_hist_c = \
cbcg_solver_obj.cbcg_solver_least_square(self._pcd_mat, self._SB, self._SX, 8, self._tol, self._maxiter)
self._final_x_d, self._final_r_d, self._residual_hist_d = \
cbcg_solver_obj.cbcg_solver_least_square(self._pcd_mat, self._SB, self._SX, 18, self._tol, self._maxiter)
plot_worker = Presenter()
residual_list = [
self._residual_hist_a, self._residual_hist_b,
self._residual_hist_c, self._residual_hist_d
]
legend_list = [
"pcd_lbcg_lstsq_s8", "pcd_lbcg_lstsq_s18", "pcd_cbcg_lstsq_s8",
"pcd_cbcg_lstsq_s18"
]
color_list = ["r", "k", "b", "y"]
#plot_worker.instant_plot_y_log10(residual_list, "crystm01", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
#plot_worker.instant_plot_y_log10(residual_list, "wathen100", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
plot_worker.instant_plot_y_log10(residual_list, "bodyy06",
"#iteration",
"$\\frac{||x_1||}{||b_1||}$",
legend_list, color_list)
def _bcbcg_blbcg_least_square_exp_b(self):
""" figure 2"""
print("_bcbcg_blbcg_least_square_exp_b starting ... ")
m = 3
self._BB = np.random.random((self._mat.shape[0], m))
self._BX = np.ones((self._mat.shape[1], m))
#line 1
blbcg_solver_obj = BLBCG()
self._final_x_blbcg_a, self._final_r_blbcg_a, self._residual_hist_blbcg_a = \
blbcg_solver_obj.blbcg_solver_least_square(self._mat, self._BB, self._BX, 16, self._tol, self._maxiter, 0)
#line 2
blbcg_solver_obj = BLBCG()
self._final_x_blbcg_b, self._final_r_blbcg_b, self._residual_hist_blbcg_b = \
blbcg_solver_obj.blbcg_solver_least_square(self._mat, self._BB, self._BX, 32, self._tol, self._maxiter, 0)
#line addition
#blbcg_solver_obj = BLBCG()
#self._final_x_blbcg_c, self._final_r_blbcg_c, self._residual_hist_blbcg_c = \
# blbcg_solver_obj.blbcg_solver_least_square(self._mat, self._BB_4, self._BX_4, 32, self._tol, self._maxiter, 0)
#line 3
bcbcg_solver_obj = BCBCG()
self._final_x_bcbcg_a, self._final_r_bcbcg_a, self._residual_hist_bcbcg_a = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB, self._BX, 16, self._tol, self._maxiter, 0)
#line 4
bcbcg_solver_obj = BCBCG()
self._final_x_bcbcg_b, self._final_r_bcbcg_b, self._residual_hist_bcbcg_b = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB, self._BX, 32, self._tol, self._maxiter, 0)
#line addition
#bcbcg_solver_obj = BCBCG()
#self._final_x_bcbcg_c, self._final_r_bcbcg_c, self._residual_hist_bcbcg_c = \
# bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_4, self._BX_4, 32, self._tol, self._maxiter, 0)
plot_worker = Presenter()
#residual_list = [self._residual_hist_blbcg_a, self._residual_hist_blbcg_b, self._residual_hist_blbcg_c, \
# self._residual_hist_bcbcg_a, self._residual_hist_bcbcg_b, self._residual_hist_bcbcg_c ]
residual_list = [self._residual_hist_blbcg_a, self._residual_hist_blbcg_b, \
self._residual_hist_bcbcg_a, self._residual_hist_bcbcg_b ]
#legend_list = ["blbcg_m4s4", "blbcg_m4s8", "blbcg_m4s12", "bcbcg_m4s4", "bcbcg_m4s8", "bcbcg_m4s12"]
legend_list = [
"blbcg_m3s16", "blbcg_m3s32", "bcbcg_m3s16", "bcbcg_m3s32"
]
#color_list = ["r","k","b","y","g","m"]
color_list = ["r", "k", "b", "g"]
#plot_worker.instant_plot_y_log10(residual_list, "test", "#iteration", "$\\mathbf{log_{10}\\frac{||x_1||}{||b_1||}}$", legend_list, color_list)
plot_worker.instant_plot_y_log10(
residual_list, "bodyy6", "#iteration",
"$\\mathbf{log_{10}\\frac{||x_1||}{||b_1||}}$", legend_list,
color_list)
def __init__(self, context, plot=False, plot_title='Backtesting.pptx'):
self.context = context
self.plot = plot
if self.plot:
pres = Presenter()
pres.start_presentation(title='Backtesting')
self.presname = plot_title
pres.save_presentation(self.presname)
if self.context['strategy_type'] == 'index':
self.index_strategy()
def __init__(self,
broker_id=None,
sec_type=None,
exchange_id=None,
country=None,
sec_price=None,
no_sec=None,
plot=False,
location=None):
# #### MAIN INPUT ####
self.name = 'Transaction Cost Model'
self.dbTCM = DatabaseManipulationTCM()
self.broker_id = broker_id
self.sec_type = sec_type
self.exchange_id = exchange_id
self.country = country
# Ensure that sec_price is a numpy array, and create one if not provided
if not isinstance(sec_price, list) and sec_price is not None:
sec_price = [sec_price]
self.sec_price = np.arange(
10, 500, 10) if sec_price is None else np.array(sec_price)
# Ensure that no_sec is a numpy array, and create one if not provided
if not isinstance(no_sec, list) and no_sec is not None:
no_sec = [no_sec]
self.no_sec = np.arange(10, 500,
10) if no_sec is None else np.array(no_sec)
# Assign location, if not provided, it will be main file of project
if location is None:
self.location = ''
else:
self.location = ''.join([location, '/'])
# #### PRESENTATION ####
self.plot = plot
self.presname = ''
if self.plot:
pres = Presenter()
pres.start_presentation(title='Transaction Costs')
text = ''.join([
'broker id: ',
str(self.broker_id), '\n security type: ', self.sec_type,
'\n exchange id: ', self.exchange_id, '\n country: ',
self.country
])
pres.add_text_slide(text, title='Input')
self.presname = ''.join([
self.location, 'Transaction_Costs_',
str(broker_id), '_', self.sec_type, '_', self.exchange_id, '_',
self.country, '.pptx'
])
pres.save_presentation(self.presname)
def _cg_bcg_bcbcg_least_square_exp(self):
""" """
print("_cg_bcg_bcbcg_least_square_exp starting, ... ")
self._BB_1 = np.random.random( ( self._mat.shape[0],1) )
self._BX_1 = np.ones ( (self._mat.shape[1],1) )
self._BB_4 = np.random.random( ( self._mat.shape[0],4) )
self._BX_4 = np.ones ( (self._mat.shape[1],4) )
self._BB_12 = np.random.random( ( self._mat.shape[0],12) )
self._BX_12 = np.ones ( (self._mat.shape[1],12) )
#line 1
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_1, self._BB_1, self._tol, self._maxiter)
self._final_X_cg, self._final_R_cg, self._residual_hist_cg = bcg_solver_obj.bcg_variant_lstsq_run(0)
##line 2
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_12, self._BB_12, self._tol, self._maxiter)
self._final_X_bcg_m12, self._final_R_bcg_m12, self._residual_hist_bcg_m12 = bcg_solver_obj.bcg_variant_lstsq_run(0)
##line 3
#bcbcg_solver_obj = BCBCG()
#self._final_x_bcbcg_m1s2, self._final_r_bcbcg_m1s2, self._residual_hist_bcbcg_m1s2 = \
# bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_1, self._BX_1, 2, self._tol, self._maxiter, 0)
##line 4
#bcbcg_solver_obj = BCBCG()
#self._final_x_bcbcg_m1s8, self._final_r_bcbcg_m1s8, self._residual_hist_bcbcg_m1s8 = \
# bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_1, self._BX_1, 8, self._tol, self._maxiter, 0)
##line 5
#bcbcg_solver_obj = BCBCG()
#self._final_x_bcbcg_m4s2, self._final_r_bcbcg_m4s2, self._residual_hist_bcbcg_m4s2 = \
# bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_4, self._BX_4, 2, self._tol, self._maxiter, 0)
##line 6
#bcbcg_solver_obj = BCBCG()
#self._final_x_bcbcg_m4s8, self._final_r_bcbcg_m4s8, self._residual_hist_bcbcg_m4s8 = \
# bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_4, self._BX_4, 8, self._tol, self._maxiter, 0)
plot_worker = Presenter()
#residual_list = [self._residual_hist_cg, self._residual_hist_bcg_m12, \
# self._residual_hist_bcbcg_m1s2, self._residual_hist_bcbcg_m1s8, \
# self._residual_hist_bcbcg_m4s2, self._residual_hist_bcbcg_m4s8 ]
residual_list = [self._residual_hist_cg, self._residual_hist_bcg_m12]
#legend_list = ["cg","bcg_m12", "bcbcg_m1s2", "bcbcg_m1s8", "bcbcg_m4s2", "bcbcg_m4s8"]
legend_list = ["cg","bcg_m12"]
#color_list = ["r","k","b","y","m","g"]
color_list = ["r","k"]
#plot_worker.instant_plot_y_log10(residual_list, "test", "#iteration", "$\\mathbf{log_{10}\\frac{||x_1||}{||b_1||}}$", legend_list, color_list)
#plot_worker.instant_plot_y_log10(residual_list, "wathen100(dim=30,401, nnz=471,601, cond=5816.01 )", "#iteration", "$\\mathbf{log_{10}\\frac{||x_1||}{||b_1||}}$", legend_list, color_list)
plot_worker.instant_plot_y_log10(residual_list, "MG", "#iteration", "$\\mathbf{log_{10}\\frac{||x_1||}{||b_1||}}$", legend_list, color_list)
def _db_bcbcg_lstsq (self):
""" """
bcbcg_solver_obj = BCBCG()
self._final_X_a, self._final_R_a, self._residual_hist_a = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB, self._BX, self._step_val, self._tol, self._maxiter,0)
self._final_X_b, self._final_R_b, self._residual_hist_b = \
bcbcg_solver_obj.bcbcg_solver(self._mat, self._BB, self._BX, self._step_val, self._tol, self._maxiter,0)
plot_worker = Presenter()
residual_list = [self._residual_hist_a, self._residual_hist_b]
legend_list = ["bcbcg_s20b4_lstsq","bcbcg_s20b4"]
color_list = ["r","k"]
plot_worker.instant_plot_y_log10(residual_list, "crystm02", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
def _db_cbcg_lstsq (self):
cbcg_solver_obj = CBCG()
self._final_x_a, self._final_r_a, self._residual_hist_a = \
cbcg_solver_obj.cbcg_solver_least_square(self._mat, self._SB, self._SX, self._step_val, self._tol, self._maxiter)
self._final_x_b, self._final_r_b, self._residual_hist_b = \
cbcg_solver_obj.cbcg_solver_least_square(self._mat, self._SB, self._SX, self._step_val, self._tol, self._maxiter)
plot_worker = Presenter()
residual_list = [self._residual_hist_a, self._residual_hist_b]
legend_list = ["cbcg_s2_lstsq","blbcg_s2"]
color_list = ["r","k"]
plot_worker.instant_plot_y_log10(residual_list, "bodyy6", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
def _cg_bcg_bcbcg_least_square_exp(self):
""" """
self._BB_1 = np.random.random( ( self._mat.shape[0],1) )
self._BX_1 = np.ones ( (self._mat.shape[1],1) )
self._BB_6 = np.random.random( ( self._mat.shape[0],6) )
self._BX_6 = np.ones ( (self._mat.shape[1],6) )
self._BB_12 = np.random.random( ( self._mat.shape[0],12) )
self._BX_12 = np.ones ( (self._mat.shape[1],12) )
#line 1
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_1, self._BB_1, self._tol, self._maxiter)
self._final_X_cg, self._final_R_cg, self._residual_hist_cg = bcg_solver_obj.bcg_variant_lstsq_run(0)
#line 2
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_12, self._BB_12, self._tol, self._maxiter)
self._final_X_bcg_m12, self._final_R_bcg_m12, self._residual_hist_bcg_m12 = bcg_solver_obj.bcg_variant_lstsq_run(0)
#line 3
bcbcg_solver_obj = BCBCG()
self._final_x_bcbcg_m1s2, self._final_r_bcbcg_m1s2, self._residual_hist_bcbcg_m1s2 = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_1, self._BX_1, 2, self._tol, self._maxiter, 0)
#line 4
#bcbcg_solver_obj = BCBCG()
#self._final_x_bcbcg_m1s6, self._final_r_bcbcg_m1s6, self._residual_hist_bcbcg_m1s6 = \
# bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_1, self._BX_1, 6, self._tol, self._maxiter, 0)
bcbcg_solver_obj = BCBCG()
self._final_x_bcbcg_m1s6, self._final_r_bcbcg_m1s6, self._residual_hist_bcbcg_m1s6 = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_1, self._BX_1, 8, self._tol, self._maxiter, 0)
#line 5
bcbcg_solver_obj = BCBCG()
self._final_x_bcbcg_m6s2, self._final_r_bcbcg_m6s2, self._residual_hist_bcbcg_m6s2 = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_6, self._BX_6, 2, self._tol, self._maxiter, 0)
#line 6
#bcbcg_solver_obj = BCBCG()
#self._final_x_bcbcg_m6s6, self._final_r_bcbcg_m6s6, self._residual_hist_bcbcg_m6s6 = \
# bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_6, self._BX_6, 6, self._tol, self._maxiter, 0)
bcbcg_solver_obj = BCBCG()
self._final_x_bcbcg_m6s6, self._final_r_bcbcg_m6s6, self._residual_hist_bcbcg_m6s6 = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB_6, self._BX_6, 8, self._tol, self._maxiter, 0)
plot_worker = Presenter()
residual_list = [self._residual_hist_cg, self._residual_hist_bcg_m12, \
self._residual_hist_bcbcg_m1s2, self._residual_hist_bcbcg_m1s6, \
self._residual_hist_bcbcg_m6s2, self._residual_hist_bcbcg_m6s6 ]
legend_list = ["cg","bcg_m12", "bcbcg_m1s2", "bcbcg_m1s6", "bcbcg_m6s2", "bcbcg_m6s6"]
color_list = ["r","k","b","y","m","g"]
plot_worker.instant_plot_y_log10(residual_list, "test", "#iteration", "$\\mathbf{log_{10}\\frac{||x_1||}{||b_1||}}$", legend_list, color_list)
def find_poster_raw(user_id):
"""
Return User's Profile in JSON.
"""
presenter = Presenter(user_id)
response = {
'user_id': user_id,
'top_favorites': presenter.get_posters('TF', 8),
'nearest_neighbours': presenter.get_posters('NN', 8),
'latent_factors': presenter.get_posters('LF', 8)
}
return jsonify(response)
def find_data(user_id):
"""
Return user's data in JSON.
"""
presenter = Presenter(user_id)
response = {
'user_id': user_id,
'top_favorites': presenter.get_data('TF'),
'nearest_neighbours': presenter.get_data('NN'),
'latent_factors': presenter.get_data('LF')
}
return jsonify(response)
def _db_power_iteration(self):
pi_worker = PowerIteration();
tol = 1e-4
maxiters = 1000
self._v_eigen, self._lambda_eigen, self._lambda_eigen_list = pi_worker.naive_power_iteration (self._mat, self._X, maxiters, tol)
self._v_shift_eigen, self._lambda_shift_eigen, self._lambda_shift_eigen_list = pi_worker.power_iteration_with_shifting (self._mat, self._X, self._lambda_eigen, maxiters, tol)
print ("lambda ", self._lambda_shift_eigen)
plot_worker = Presenter()
ratio_list = [ [x+self._lambda_eigen for x in self._lambda_shift_eigen_list] ]
legend_list = ["naive power iteration"]
color_list = ["k"]
plot_worker.instant_plot_y_log10(ratio_list, "crystm01" , "#iteration", "$\\frac{\\lambda_{old} - \\lambda_{new}}{\\lambda_i{old} }$", legend_list, color_list)
def find_poster(user_id):
"""
User's Profile Page.
"""
presenter = Presenter(user_id)
response = {
'header': 'OpenREC',
'user_id': user_id,
'top_favorites': presenter.get_posters('TF', 8),
'nearest_neighbours': presenter.get_posters('NN', 8),
'latent_factors': presenter.get_posters('LF', 8)
}
return render_template('user.html', data=response)
def _db_lbcg_least_square_exp (self):
""" """
lbcg_solver_obj = LBCG()
self._final_x_a, self._final_r_a, self._residual_hist_a = \
lbcg_solver_obj.lbcg_solver_least_square(self._mat, self._SB, self._SX, self._step_val, self._tol, self._maxiter)
cbcg_solver_obj = CBCG()
self._final_x_b, self._final_r_b, self._residual_hist_b = \
cbcg_solver_obj.cbcg_solver(self._mat, self._SB, self._SX, self._step_val, self._tol, self._maxiter)
plot_worker = Presenter()
residual_list = [self._residual_hist_a, self._residual_hist_b]
legend_list = ["lbcg_lstsq_s2", "cbcg_s2"]
color_list = ["r","k"]
#plot_worker.instant_plot_y_log10(residual_list, "crystm01", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
plot_worker.instant_plot_y_log10(residual_list, "wathen100", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
def _blbcg_least_square_exp(self):
""" """
blbcg_solver_obj = BLBCG()
self._final_x_a, self._final_r_a, self._residual_hist_a = \
blbcg_solver_obj.blbcg_solver_least_square(self._mat, self._BB, self._BX, self._step_val, self._tol, self._maxiter, 0)
bcbcg_solver_obj = BCBCG()
self._final_x_b, self._final_r_b, self._residual_hist_b = \
bcbcg_solver_obj.bcbcg_solver_least_square(self._mat, self._BB, self._BX, self._step_val, self._tol, self._maxiter, 0)
plot_worker = Presenter()
residual_list = [self._residual_hist_a, self._residual_hist_b]
legend_list = ["blbcg_s64b4_lstsq","bcbcg_s64b4_lstsq"]
color_list = ["r","k"]
#plot_worker.instant_plot_y_log10(residual_list, "crystm01", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
plot_worker.instant_plot_y_log10(residual_list, "bodyy6", "#iteration", "$\\frac{||x_1||}{||b_1||}$", legend_list, color_list)
def main():
window_width = 80
window_height = 50
window_title = "Janus Mining Colony"
font_path = Path("fonts/libtcod/dejavu16x16_gs_tc.png")
presenter = Presenter(window_width, window_height, window_title, font_path)
while presenter.is_window_open():
presenter.put_tile(1, 1, '@', libtcodpy.white)
presenter.present()
key = libtcodpy.console_check_for_keypress()
if key.vk == libtcodpy.KEY_ESCAPE:
return True
def _db_bcg_least_square (self):
""" """
m = 32
self._BB_m = np.random.random( ( self._mat.shape[0],m) )
self._BX_m = np.ones ( (self._mat.shape[1],m) )
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_m, self._BB_m, self._tol, self._maxiter)
self._final_X_bcg, self._final_R_bcg, self._residual_hist_bcg = bcg_solver_obj.bcg_variant_one_run(0)
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_m, self._BB_m, self._tol, self._maxiter)
self._final_X_bcg_lstsq, self._final_R_bcg_lstsq, self._residual_hist_bcg_lstsq = bcg_solver_obj.bcg_variant_lstsq_run(0)
plot_worker = Presenter()
residual_list = [self._residual_hist_bcg, self._residual_hist_bcg_lstsq]
legend_list = ["bcg","bcg_lstsq"]
color_list = ["r","k"]
plot_worker.instant_plot_y_log10(residual_list, "test", "#iteration", "$\\mathbf{log_{10}\\frac{||x_1||}{||b_1||}}$", legend_list, color_list)
def __init__(self, path="../database"):
self.session_files = []
self.books = self.getBooks(path)
self.preferences = Preferences()
self.preferences.readConfig()
self.session = copy.deepcopy(self.preferences)
self.db = Database()
self.openDefaultDatabase()
self.presenter = Presenter()
self.songs = []
self.uploaded_song = {}
def __init__(self,
context,
data,
plot=False,
plot_title='Backtesting.pptx',
plot_data=None):
""" Initializes Backtesting class
:param context: dictionary filled with vital information for backtesting and running the strategy algorithm
:param data: list of the dataframes of the various securities needed for performance measurements
:param plot: boolean for whether to plot or not. Default is False
:param plot_title: string title to save plot presentation as. Default is 'Backtesting.pptx'
:param plot_data: dictionary with additional information to use for plotting
:return: N.A.
"""
self.context = context
self.plot = plot
if self.context['start_date'] is None:
self.context['start_date'] = 'default'
if self.context['end_date'] is None:
self.context['end_date'] = 'default'
# self.perf_data is one big dataframe of all dataframes in data, cut to provided start and end date
# Will be used to determine performance (returns) of strategy
# self.test_data is also one big dataframe, but cut only to provided end date
# Will be used to determine orders from strategy
self.perf_data = [None] * len(data)
self.test_data = [None] * len(data)
for i, df in enumerate(data):
self.perf_data[i] = dfm.cut_dates(df, self.context['start_date'],
self.context['end_date'])
self.test_data[i] = dfm.cut_dates(df, 'default',
self.context['end_date'])
self.perf_df = dfm.merge_dfs(self.perf_data)
self.test_df = dfm.merge_dfs(self.test_data)
if self.plot:
self.plot_data = plot_data
self.presname = plot_title
self.pres = Presenter(new_pres=self.presname, title='Backtesting')
if self.plot_data['benchmark'] is not None:
self.plot_data['benchmark'] = dfm.cut_dates(
plot_data['benchmark'], self.context['start_date'],
self.context['end_date'])
