def test_uni_plot_one_plot(self):
# uni plot
aplot_2 = APlot()
aplot_2.uni_plot(0, self.xx, self.yy)
aplot_2.tight_layout()
self.image_name = "image_uniplot_1"
self.check_plot()
def test_uni_plot_ax_bis(self):
# two plots same figures
aplot_1 = APlot()
aplot_1.uni_plot(0, self.xx, self.yy + 5)
aplot_1.uni_plot_ax_bis(0, self.xx, np.exp(self.xx))
self.image_name = "image_plot_bis"
self.check_plot()
def test_bi_plot(self):
aplot_4 = APlot(how=(2, 2))
aplot_4.bi_plot(0, 1, self.xx, self.yy, self.xx, self.yy)
aplot_4.uni_plot(2, self.xx, self.yy)
aplot_4.uni_plot(3, self.xx, self.yy)
aplot_4.tight_layout()
self.image_name = "image_biplot"
self.check_plot()
def test_uni_plot_for_plots_same_graph_sharey(self):
# uni plot *4
aplot_3 = APlot(how=(2, 2), sharey=True)
aplot_3.uni_plot(0, self.xx, self.yy)
aplot_3.uni_plot(1, self.xx, self.yy)
aplot_3.uni_plot(2, self.xx, self.yy)
aplot_3.uni_plot(3, self.xx, self.yy)
aplot_3.tight_layout()
self.image_name = "image_uniplot_2_sharey"
self.check_plot()
def test_show_legend_for_two_axis(self):
yy = np.abs(np.cos(self.xx)) + 1
# second, try the same as before where the second axis is also setting another characteristic.
aplot = APlot()
dict_plot1 = {'title': 'my title1'}
dict_plot2 = {'title': 'my title2'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot1)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot2)
aplot.show_legend()
self.image_name = "image_legend_two_axis"
self.check_plot()
def plot_parameters_respect_to_time_hawkes(self):
# I m printing the evolution of the parameters there.
aplot = APlot(how=(1, self.M))
tt = np.linspace(0, 1, 1000)
my_colors = plt.cm.rainbow(np.linspace(0, 1, 2 * self.M))
for i_dim in range(self.M):
xx_nu = [self.NU[i_dim](t, 1, 0) for t in tt]
aplot.uni_plot(nb_ax=i_dim,
yy=xx_nu,
xx=tt,
dict_plot_param={
"label": f"nu, {i_dim}",
"color": "blue",
"markersize": 0,
"linewidth": 2
},
tight=False)
color = iter(my_colors)
for j_dim in range(self.M):
c1 = next(color)
c2 = next(color)
xx_alpha = [self.ALPHA[i_dim][j_dim](t, 1, 0) for t in tt]
xx_beta = [self.BETA[i_dim][j_dim](t, 1, 0) for t in tt]
aplot.uni_plot(nb_ax=i_dim,
yy=xx_alpha,
xx=tt,
dict_plot_param={
"label": f"alpha, {i_dim},{j_dim}.",
"color": c1,
"markersize": 0,
"linewidth": 2
},
tight=False)
aplot.uni_plot(nb_ax=i_dim,
yy=xx_beta,
xx=tt,
dict_plot_param={
"label": f"beta, {i_dim},{j_dim}.",
"color": c2,
"markersize": 0,
"linewidth": 2
},
tight=False)
aplot.set_dict_fig(
i_dim, {
'title':
"Evolution of the parameters, time in % of total; dimension : {}"
.format(i_dim),
'xlabel':
'',
'ylabel':
''
})
aplot.show_legend(i_dim)
def test_uni_plot_for_plots_same_graph_sharey_not_same_interval_for_y(
self):
xx = np.linspace(-1, 1, 1000)
aplot_3 = APlot(how=(2, 2), sharey=True)
aplot_3.uni_plot(0, xx, np.exp(xx))
aplot_3.uni_plot(1, xx + 1, np.exp(xx + 1))
aplot_3.uni_plot(2, xx + 1, np.exp(xx + 1))
aplot_3.uni_plot(3, xx, np.exp(xx))
aplot_3.tight_layout()
self.image_name = "image_uniplot_2_sharey_not_same_interval_for_y"
self.check_plot()
integral_of_pdf_2 = simps(values_density_of_SVI2, val_density)
price_1 = compute_integral(val_density, values_density_of_SVI1)
price_2 = compute_integral(val_density, values_density_of_SVI2)
print("ST1 = ", price_1)
print("ST2 = ", price_2)
print("Relative Error between both prices: ",
(price_2 - price_1) / min(price_2, price_1) * 100, "%")
uu = np.linspace(1, 2, NB_OF_UU)
densities_plot = APlot(how=(1, 1))
densities_plot.uni_plot(nb_ax=0,
xx=val_density[::100],
yy=values_density_of_SVI1[::100],
dict_plot_param={
"color": "red",
"label": "Density 1"
})
densities_plot.uni_plot(nb_ax=0,
xx=val_density[::100],
yy=values_density_of_SVI2[::100],
dict_plot_param={"label": "Density 2"},
dict_ax={
"title": "Densities",
"xlabel": "Log Moneyness",
"ylabel": "PDF"
})
densities_plot.show_legend()
true_vs_computed_TIV = APlot(how=(1, 1))
def test_set_dict_ax_and_bis_each_parameter_only_first_two_axis_same_graph(
self):
# first, trying every simple possibility for dict_ax
yy = np.abs(np.cos(self.xx)) + 1
with self.subTest('title'):
aplot = APlot()
dict_plot = {'title': 'my title'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1)
self.image_name = "image_set_dict_ax_title"
self.check_plot()
with self.subTest('xlabel'):
aplot = APlot()
dict_plot = {'xlabel': 'my x label'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1)
self.image_name = "image_set_dict_ax_xlabel"
self.check_plot()
with self.subTest('ylabel'):
aplot = APlot()
dict_plot = {'ylabel': 'my y label'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1)
self.image_name = "image_set_dict_ax_ylabel"
self.check_plot()
with self.subTest('xscale'):
aplot = APlot()
dict_plot = {'xscale': 'log'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1)
self.image_name = "image_set_dict_ax_xscale_only_principal_axis"
self.check_plot()
with self.subTest('yscale left'):
aplot = APlot()
dict_plot = {'yscale': 'log'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1)
self.image_name = "image_set_dict_ax_yscale"
self.check_plot()
with self.subTest('xint'):
aplot = APlot()
dict_plot = {'xint': True}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 1 / 3 * np.sin(self.xx) + 1)
self.image_name = "image_set_dict_ax_xint"
self.check_plot()
with self.subTest('xint_yint'):
aplot = APlot()
dict_plot = {'xint': True, 'yint': True}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 1 / 3 * np.sin(self.xx) + 1)
self.image_name = "image_set_dict_ax_xyint"
self.check_plot()
for i in range(11):
with self.subTest('parameter', i=i):
aplot = APlot()
dict_plot = {
'parameters': ['A', 3, 5] * i,
'name_parameters': ['A', '$\sigma$', '$\\rho$'] * i
}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1)
self.image_name = f"image_set_dict_ax_parameter_{i}"
self.check_plot()
# with self.subTest('parameters not good length'):
# aplot = APlot()
#
# dict_plot = {
# 'parameters': ['A', 3, 5, 10, 42], 'name_parameters': ['A']}
#
# aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
# aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1)
with self.subTest('xlim'):
aplot = APlot()
dict_plot = {'xlim': [0, 0.5]}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1)
self.image_name = "image_set_dict_ax_xlim"
self.check_plot()
with self.subTest('ylim'):
aplot = APlot()
dict_plot = {'ylim': [1.2, 2.4]}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1)
self.image_name = "image_set_dict_ax_ylim"
self.check_plot()
def test_set_dict_ax_and_bis_each_parameter_both_two_axis_same_graph(self):
yy = np.abs(np.cos(self.xx)) + 1
# second, try the same as before where the second axis is also setting another characteristic.
with self.subTest('two different titles'):
aplot = APlot()
dict_plot1 = {'title': 'my title1'}
dict_plot2 = {'title': 'my title2'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot1)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot2)
self.image_name = "image_set_dict_ax_title_2"
self.check_plot()
with self.subTest('two xlabels'):
aplot = APlot()
dict_plot1 = {'xlabel': 'my x label1'}
dict_plot2 = {'xlabel': 'my x label2'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot1)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot2)
self.image_name = "image_set_dict_ax_xlabel_2"
self.check_plot()
with self.subTest('two ylabels'):
aplot = APlot()
dict_plot1 = {'ylabel': 'my y label1'}
dict_plot2 = {'ylabel': 'my y label2'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot1)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot2)
self.image_name = "image_set_dict_ax_ylabel_2"
self.check_plot()
with self.subTest('xscale same both axis'):
aplot = APlot()
dict_plot = {'xscale': 'log'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot)
self.image_name = "image_set_dict_ax_xscale_both_same_scale"
self.check_plot()
with self.subTest('yscale same both axis'):
aplot = APlot()
dict_plot = {'yscale': 'log'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot)
self.image_name = "image_set_dict_ax_yscale_2_same"
self.check_plot()
with self.subTest('xscale different'):
aplot = APlot()
dict_plot2 = {'xscale': 'log'}
dict_plot = {'xscale': 'linear'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot2)
self.image_name = "image_set_dict_ax_xscale_2_different_scales"
self.check_plot()
with self.subTest('yscale different'):
aplot = APlot()
dict_plot = {'yscale': 'log'}
dict_plot2 = {'yscale': 'linear'}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot2)
self.image_name = "image_set_dict_ax_yscale_2_different"
self.check_plot()
# with self.subTest('xint same'):
# aplot = APlot()
#
# dict_plot = {'xint': True}
#
# aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
# aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1, dict_ax=dict_plot)
#
# plt.savefig("image_reference_test_plot/test_image_set_dict_ax_xint_2_same.png")
#
# with self.subTest('xint_yint same'):
# aplot = APlot()
#
# dict_plot = {'xint': True, 'yint': True}
#
# aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
# aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1, dict_ax=dict_plot)
#
# plt.savefig("image_reference_test_plot/test_image_set_dict_ax_xyint_same_2.png")
# with self.subTest('xint different'):
# aplot = APlot()
#
# dict_plot = {'xint': True}
# dict_plot2 = {'xint': False}
#
# aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
# aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1, dict_ax=dict_plot2)
#
# plt.savefig("image_reference_test_plot/test_image_set_dict_ax_xint_2_different_2.png")
#
# with self.subTest('xint_yint different'):
# aplot = APlot()
#
# dict_plot = {'xint': True, 'yint': True}
# dict_plot2 = {'xint': True, 'yint': False}
#
# aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot)
# aplot.uni_plot_ax_bis(0, self.xx, 3 * np.sin(self.xx) + 1, dict_ax=dict_plot2)
#
# plt.savefig("image_reference_test_plot/test_image_set_dict_ax_xyint_different_2.png")
with self.subTest('xlim'):
aplot = APlot()
dict_plot1 = {'xlim': [0, 0.5]}
dict_plot2 = {'xlim': [0, 1.5]}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot1)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot2)
self.image_name = "image_set_dict_ax_xlim_2"
self.check_plot()
with self.subTest('ylim'):
aplot = APlot()
dict_plot1 = {'ylim': [1, 5]}
dict_plot2 = {'ylim': [1, 15]}
aplot.uni_plot(0, self.xx, yy, dict_ax=dict_plot1)
aplot.uni_plot_ax_bis(0,
self.xx,
3 * np.sin(self.xx) + 1,
dict_ax=dict_plot2)
self.image_name = "image_set_dict_ax_ylim_2"
self.check_plot()
