def plot_avg_vs_vp_id(self, prop, show=True):
data = {}
for vp in self.vps:
data[vp.vp_id] = np.mean(
[get_class_value(log, prop) for log in vp.logs])
plt.plot(range(len(data)), [d[1] for d in sorted(data.items())])
show_plot(show)
def prop_inspection(self, prop):
self.data_matrix(prop)
for v in self.ttest_multiple([prop], 2):
print(v)
# plt.figure().canvas.set_window_title(prop)
f, ax = plt.subplots(2, 2)
ax = ax.flatten()
self.boxplot_all(prop, fig=ax[0])
self.boxplot_vs_run(prop, fig=ax[1])
self.plot_avg_vs_run(prop, fig=ax[2], global_run_counter=True)
self.plot_avg_vs_run(prop, fig=ax[3])
show_plot()
def plot_gear_probability(self):
data = defaultdict(lambda: [[] for _ in range(5)])
for log in self.all_logs():
d = data[log.condition]
for i in range(len(log.t)):
d[log.gear[i]].append(log.speed[i])
f, ax = plt.subplots(5) # one plot for each gear
for cond, d in data.items(): # each condition
for gear, o in enumerate(d): # each gear
hist, bins = np.histogram(o, 30)
x = [(bins[i] + bins[i + 1]) / 2 for i in range(len(bins) - 1)]
ax[gear].plot(x, hist, c=condition2color(cond))
show_plot()
def plot_avg_vs_run(self,
prop,
global_run_counter=False,
show=None,
fig=None):
data, max_items = self.data_vs_run(
prop, global_run_counter=global_run_counter)
for key, values in data.items():
errorbar(
np.arange(max_items) + 1,
values,
ylabel=prop,
xlabel='global run counter' if global_run_counter else 'run',
colors=condition2color(key),
show=show,
fig=fig)
show_plot(show)
if 0 < stop_condition < 3:
correct = True
else:
print("Brak takiego kryterium")
except ValueError:
print("Brak takiego kryterium")
accuracy = 0
iteration = 0
if stop_condition == 1:
accuracy = abs(float(input("Podaj dokładność epsilon: ")))
iteration = -1
else:
iteration = int(input("Podaj liczbe iteracji: "))
accuracy = -1
result_bisection = bisection(left, right, accuracy, iteration, function_number) # miejsce zerowe (bisekcja)
result_newton = newton(left, right, accuracy, iteration, function_number) # miejsce zerowe (netwon)
if result_bisection is False:
print("Bisekcja: Funkcja nie spełnia założeń na danym przedziale")
else:
print("Bisekcja - " + str(result_bisection))
if result_newton is False:
print("Newton: Funkcja nie spełnia założeń na danym przedziale")
else:
print("Newton - " + str(result_newton))
show_plot(left, right, function_number, result_bisection, result_newton) # rysowanie wykresu