def filtration(self, model_for_filtration, choice_filter):
trend_filter = Trend() # Тренд фильтра
# Фильтр низких частот
if choice_filter == 1:
trend_filter.generation_trend_filter_potter()
# Фильтр высоких частот
if choice_filter == 2:
trend_filter.generating_trend_high_potter()
# Фильтр полосовой
if choice_filter == 3:
trend_filter.generating_trend_bandpass_filter()
# Фильтр режекторный
if choice_filter == 4:
trend_filter.generating_trend_notch_filter()
# Тренд существущей модели
trend_model = Trend()
trend_model.x = model_for_filtration.x
trend_model.y = model_for_filtration.y
trend_model.n = model_for_filtration.n
trend = convolution(trend_model, trend_filter)
self.x = trend.x
self.y = trend.y
def convolution(trend_1, trend_2):
trend = Trend()
n = len(trend_1.y)
m = len(trend_2.y)
y = []
for i in range(n):
y_k = 0
for j in range(m):
coefficient_x = i - j
if coefficient_x >= 0:
y_m = trend_1.y[coefficient_x] * trend_2.y[j]
else:
# y_m = trend_2.y[j]
y_m = 0
y_k += y_m
y.append(y_k)
trend.y = np.array(y)
trend.x = trend_1.x
return trend
def sum_trend(trend_1, trend_2):
trend = Trend()
trend.y = trend_1.y + trend_2.y
trend.x = trend_1.x
return trend
def multi(trend_1, trend_2):
trend = Trend()
trend.y = trend_1.y * trend_2.y
trend.x = trend_1.x
return trend
def calculation(self):
# y(x)=kx+b
if self.option == 1:
trend = Trend()
trend.generating_trend_line()
self.y = trend.y
# y(x)=-kx+b
if self.option == 2:
trend = Trend()
trend.generating_trend_line()
trend.y = np.flip(trend.y)
self.y = trend.y
# y(x) = beta * exp^(alpha * i)
if self.option == 3:
trend = Trend()
trend.generating_exhibitor()
self.y = trend.y
# y(x) = beta * exp^(alpha * -i)
if self.option == 4:
trend = Trend()
trend.generating_exhibitor()
trend.y = np.flip(trend.y)
self.y = trend.y
# Встроенный рандом
if self.option == 5:
trend = Trend()
trend.generating_trend_random(self.s_min, self.s_max)
self.y = trend.y
# Кастомный рандом
if self.option == 6:
trend = Trend()
trend.generating_custom_random()
self.y = trend.y
# Рандом + сдвиг
if self.option == 7:
trend1 = Trend()
trend1.generating_trend_random(self.s_min, self.s_max)
trend = self.shift(trend1)
self.y = trend.y
# Указали, что не требуется нормализация
self.flag_normalisation = 0
# Значения за областью
if self.option == 8:
trend1 = Trend()
trend1.generating_random_spikes(self.s_min, self.s_max)
self.y = trend1.y
# Указали, что не требуется нормализация
self.flag_normalisation = 0
# Адитивная модель №1
if self.option == 9:
trend1 = Trend()
trend1.generating_trend_line()
trend1.y = np.flip(trend1.y)
trend2 = Trend()
trend2.generating_trend_random(self.s_min, self.s_max)
trend = sum_trend(trend1, trend2)
self.y = trend.y
# Адитивная модель №2
if self.option == 10:
trend1 = Trend()
trend1.generating_trend_line()
trend2 = Trend()
trend2.generating_trend_random(self.s_min, self.s_max)
trend = sum_trend(trend1, trend2)
self.y = trend.y
# Мультипликативная модель №1
if self.option == 11:
trend1 = Trend()
trend1.generating_trend_line()
trend1.y = np.flip(trend1.y)
trend2 = Trend()
trend2.generating_trend_random(self.s_min, self.s_max)
trend = multi(trend1, trend2)
self.y = trend.y
# Мультипликативная модель №2
if self.option == 12:
trend1 = Trend()
trend1.generating_trend_line()
trend2 = Trend()
trend2.generating_trend_random(self.s_min, self.s_max)
trend = multi(trend1, trend2)
self.y = trend.y
# График кусочной функции
if self.option == 13:
trend = Trend()
trend.generating_piecewise_function(self.s_min, self.s_max)
self.y = trend.y
# График гармонический процесс
if self.option == 17:
trend = Trend()
trend.generating_harmonic_process()
if self.c != 0:
self.y = self.y + self.c
else:
self.y = trend.y
self.flag_normalisation = 0
self.normalisation_axis()
# График полигармонического процесса
# x(t) = x1(t) + x2(t) = x3(t)
# xi(t) = Ai * sin(2piFit)
# A1 = 25 f1 = 11
# A2 = 35 f2 = 41
# A3 = 30 f3 = 141
if self.option == 19:
trend1 = Trend()
trend2 = Trend()
trend3 = Trend()
trend1.a_0 = 25
trend1.f_0 = 11
trend1.generating_harmonic_process()
trend2.a_0 = 35
trend2.f_0 = 41
trend2.generating_harmonic_process()
trend3.a_0 = 30
trend3.f_0 = 141
trend3.generating_harmonic_process()
trend4 = sum_trend(trend1, trend2)
trend = sum_trend(trend4, trend3)
self.y = trend.y
# График Рандом + спайки
if self.option == 20:
trend_1 = Trend()
trend_1.generating_trend_random(self.s_min, self.s_max)
trend_2 = Trend()
trend_2.generating_random_spikes(self.s_min, self.s_max)
trend = sum_trend(trend_1, trend_2)
self.y = trend.y
self.flag_normalisation = 0
self.axis_max = np.amax(self.y) * 1.2
self.axis_min = np.amin(self.y) * 1.2
# График Гармонический процесс + trend
if self.option == 25:
trend_1 = Trend()
trend_2 = Trend()
trend_1.generating_harmonic_process()
trend_2.generating_trend_line()
trend = sum_trend(trend_1, trend_2)
self.y = trend.y
# График Гармонический процесс + спайки
if self.option == 26:
trend_1 = Trend()
trend_2 = Trend()
trend_1.generating_harmonic_process()
trend_2.generating_random_spikes(self.s_min, self.s_max)
trend = sum_trend(trend_1, trend_2)
self.y = trend.y
self.flag_normalisation = 0
self.normalisation_axis()
# График ГП(гармонический процесс) + спайки + рандом + trend
if self.option == 27:
trend_1 = Trend()
trend_2 = Trend()
trend_3 = Trend()
trend_4 = Trend()
trend_1.generating_harmonic_process()
trend_2.generating_random_spikes(self.s_min, self.s_max)
trend_3.generating_trend_random(self.s_min, self.s_max)
trend_4.generating_trend_line()
trend = (trend_1, trend_2)
trend = (trend, trend_3)
trend = (trend, trend_4)
self.y = trend.y
self.flag_normalisation = 0
self.normalisation_axis()
# График из файла
if self.option == 28:
trend = Trend()
trend.generating_trend_from_file()
self.y = trend.y
self.flag_normalisation = 0
self.normalisation_axis()
# График ГП + экспонента (кардиограма)
if self.option == 29:
self.n = 200
self.x = np.arange(0, self.n)
# self.delta_t = 0.005
# self.display_n = self.n
self.s_max = 1
trend_1 = Trend()
trend_1.n = self.n
trend_1.x = self.x
trend_1.delta_t = 0.005
trend_1.generating_harmonic_process()
trend_2 = Trend()
trend_2.n = self.n
trend_2.x = self.x
trend_2.generating_exhibitor()
# Получили тренд сердцебиения
trend = multi(trend_1, trend_2)
# self.y = trend.y
# self.normalization()
# trend.y = self.y
self.n = 1000
trend_3 = Trend()
trend_3.generating_spikes(100)
trend = convolution(trend_3, trend)
self.y = trend.y
self.x = trend.x
self.s_max = 100
self.s_min = -self.s_max
# Реализация фильтров
# Низких частот
if self.option == 30:
trend = Trend()
trend.generation_trend_filter_potter()
self.y = trend.y
self.x = trend.x
self.n = trend.n
self.display_n = trend.display_n
self.dt = trend.dt
# Фильтр высоких частот
if self.option == 31:
trend = Trend()
trend.generating_trend_high_potter()
self.y = trend.y
self.x = trend.x
self.n = trend.n
self.display_n = trend.display_n
self.dt = trend.dt
# Полосовой фильтр
if self.option == 32:
trend = Trend()
trend.generating_trend_bandpass_filter()
self.y = trend.y
self.x = trend.x
self.n = trend.n
self.display_n = trend.display_n
self.dt = trend.dt
# Режекторный фильтр
if self.option == 33:
trend = Trend()
trend.generating_trend_notch_filter()
self.y = trend.y
self.x = trend.x
self.n = trend.n
self.display_n = trend.display_n
self.dt = trend.dt
# Звук ma.wav
if self.option == 34:
self.name_of_wav_file = "../input files/custom.wav"
sound_trend = Sound(self.name_of_wav_file)
self.x = sound_trend.x
self.y = sound_trend.y * self.c
self.rate = sound_trend.rate
self.n = len(self.x)
self.flag_checking_display_n = 1
# Звук my_voice.wav
if self.option == 35:
self.name_of_wav_file = "../input files/my_voice.wav"
sound_trend = Sound(self.name_of_wav_file)
self.x = sound_trend.x
self.y = sound_trend.y * self.c
self.rate = sound_trend.rate
self.n = len(self.x)
self.flag_checking_display_n = 1
# Экзамен
if self.option == 36:
trend = Trend()
trend.generating_trend_from_file_exam()
self.y = trend.y
self.flag_normalisation = 0
self.normalisation_axis()
# Модель Input: кардиограма, заполненная нулями с 200 до 1000
if self.option == 37:
self.n = 200
self.x = np.arange(0, self.n)
self.s_max = 1
trend_1 = Trend()
trend_1.n = self.n
trend_1.x = self.x
trend_1.delta_t = 0.005
trend_1.generating_harmonic_process()
trend_2_n = 800
trend_2_y = np.zeros(trend_2_n)
self.n = 1000
self.x = np.arange(0, self.n)
self.y = np.concatenate([trend_1.y, trend_2_y])
print(self.y)
self.s_max = 100
self.s_min = -self.s_max
