def mfcc(data=EMPTY, pos=None, repeatable=True):
global last_operation, dataset
ssub = int(spectrum_subtraction.get())
range_ = int(range_mfcc.get())
cmap_ = var_cmap.get()
if data is EMPTY:
window = dataset.windows[int(range_window.get())]
data = gui.plot(ax, dsp.MFCC, range_, cmap_, ssub, window=window)
else:
if pos is not None and not args.disable_window:
window = dataset.windows[pos]
else:
window = None
gui.plot(ax,
dsp.MFCC,
range_,
cmap_,
ssub,
data=data,
window=window)
# TODO: inference for MFCCs
#if cnn_model:
# infer(data, pos)
last_operation = (mfcc, data, window, pos)
fig.tight_layout()
canvas.draw()
if repeatable:
repeat(mfcc)
def mfsc(data=EMPTY, pos=None, repeatable=True):
global last_operation, dataset
print(pos)
ssub = int(spectrum_subtraction.get())
range_ = int(range_mfsc.get())
cmap_ = var_cmap.get()
if data is EMPTY:
window = dataset.windows[int(range_window.get())]
data = gui.plot(ax, dsp.MFSC, range_, cmap_, ssub, window=window)
else:
if pos is not None and not args.disable_window:
window = dataset.windows[pos]
else:
window = None
gui.plot(ax,
dsp.MFSC,
range_,
cmap_,
ssub,
data=data,
window=window)
if cnn_model:
print(window)
a, b, c = window[0], window[1], window[2]
infer(data[a:b, :c])
last_operation = (mfsc, data, window, pos)
fig.tight_layout()
canvas.draw()
if repeatable:
repeat(mfsc)
def fft(repeatable=True):
global last_operation
ssub = int(spectrum_subtraction.get())
data = gui.plot(ax, dsp.FFT)
last_operation = (fft, data, None, None)
fig.tight_layout()
canvas.draw()
if repeatable:
repeat(fft)
def raw_wave(repeatable=True):
global last_operation
range_ = int(range_amplitude.get())
data = gui.plot(ax, dsp.RAW_WAVE, range_=range_)
last_operation = (raw_wave, data, None, None)
fig.tight_layout()
canvas.draw()
if repeatable:
repeat(raw_wave)
def spectrogram(data=EMPTY, pos=0, repeatable=True):
global last_operation, dataset
ssub = int(spectrum_subtraction.get())
range_ = int(range_spectrogram.get())
cmap_ = var_cmap.get()
if data is EMPTY:
window = dataset.windows[int(range_window.get())]
data = gui.plot(ax, dsp.SPECTROGRAM, range_, cmap_, ssub)
else:
window = dataset.windows[pos]
gui.plot(ax,
dsp.SPECTROGRAM,
range_,
cmap_,
ssub,
data=data,
window=None)
last_operation = (spectrogram, data, window, pos)
fig.tight_layout()
canvas.draw()
if repeatable:
repeat(spectrogram)
def MST(v):
if (gui.t != 0):
for i in range(0, len(main.adjacency_matrix)):
for j in range(i, len(main.adjacency_matrix[i])):
if (main.adjacency_matrix[i][j] == 1):
print("assign weight to edge", i + 1, "to", j + 1)
temp = int(input())
off_y = (gui.y_matrix[j] - gui.y_matrix[i]) / 2
off_x = (gui.x_matrix[j] - gui.x_matrix[i]) / 2
gui.canvas.create_text(gui.x_matrix[i] + off_x,
gui.y_matrix[i] + off_y,
text=str(temp),
font="Times 20 italic bold")
main.adjacency_matrix[i][j] = temp
main.adjacency_matrix[j][i] = temp
g = Graph(len(main.adjacency_matrix))
g.graph = []
g.graph.extend(main.adjacency_matrix)
g.primsAlgo()
print("how many weights you want to change ?")
z = int(input())
if (z > 0):
for i in range(0, z):
print(
"Type the edge of which you want to change weight in fromat ->",
"e1 e2 w")
s = list(map(int, input().split()))
main.adjacency_matrix[s[0] - 1][s[1] - 1] = s[2]
gui.canvas.delete("all")
#print(gui.x_matrix)
#print(gui.y_matrix)
tag_name = str(s[0] - 1) + str(s[1] - 1)
gui.canvas.delete(tag_name)
gui.plot(main.adjacency_matrix)
def elapsed_time():
gui.plot(ax, dsp.ELAPSED_TIME)
def filterbank():
data = gui.plot(ax, dsp.FILTERBANK)
canvas.draw()