def test_data():
n = 100
t = np.arange(n) # [0 .. n-1]
# triangle
# x = np.concatenate((np.arange(0,n/2,1), np.arange(n/2,0,-1)))
# step
x = ti.step(t - n/2) * 10
# ramp
# x = ramp(t - n/2)
# normalized random
# x = np.cumsum(np.random.randn(n))
# x = np.sin(8 * np.pi/n * t) + (.1 * t)
# x = 20 * np.sin(2 * 2*np.pi/n * t)
# Add noise:
x = x + 1.2 * np.random.randn(len(x))
assert len(ti.sma(x, 10)) == len(x)
assert len(ti.ema(x, 10)) == len(x)
assert len(ti.linear_fit(x, 10)) == len(x)
assert len(ti.iir_lowpass(x, 2, 10)) == len(x)
assert len(ti.moving_min(x, 10)) == len(x)
assert len(ti.moving_max(x, 10)) == len(x)
assert len(ti.aema(x, 10)) == len(x)
assert len(ti.rate_of_change(x, 20)) == len(x)
assert len(ti.acceleration(x, 20)) == len(x)
def test_step():
t = np.arange(-5, 5, 1)
s = ti.step(t)
assert len(s) == len(t)
def _main():
print("test_indicator = {}".format(ti.test_indicator('XBB.TO')))
t = np.arange(-5, 5, 1)
s = ti.step(t)
r = ti.ramp(t)
plt.plot(t, s, marker='x', linestyle='None', label='step')
plt.plot(t,
r,
marker='o',
markerfacecolor='None',
linestyle='None',
label='ramp')
plt.legend()
plt.show()
t = np.linspace(0, 4 * np.pi, 50)
s = np.sin(t)
c = np.cos(t)
o = ti.cross_over(s, c)
u = ti.cross_under(s, c)
fig = plt.figure()
ax = fig.add_subplot(211)
ax.plot(t, s, marker='.', label='sin')
ax.plot(t, c, marker='x', label='cos')
ax.legend()
ax2 = fig.add_subplot(212)
ax2.plot(t,
o,
marker='^',
markerfacecolor='None',
linestyle='None',
label='cross over')
ax2.plot(t,
u,
marker='v',
markerfacecolor='None',
linestyle='None',
label='cross under')
ax2.legend()
plt.show()
n = 100
t = np.arange(n) # [0 .. n-1]
# triangle
# x = np.concatenate((np.arange(0,n/2,1), np.arange(n/2,0,-1)))
# step
x = ti.step(t - n / 2) * 10
# ramp
#x = ramp(t - n/2)
# normalized random
# x = np.cumsum(np.random.randn(n))
# x = np.sin(8 * np.pi/n * t) + (.1 * t)
# x = 20 * np.sin(2 * 2*np.pi/n * t)
# Add noise:
x = x + 1.2 * np.random.randn(len(x))
fig = plt.figure()
ax = fig.add_subplot(211)
ax.plot(t, x, 'o', label='raw')
ax.plot(t, ti.sma(x, 10), label='sma')
ax.plot(t, ti.ema(x, 10), label='ema')
ax.plot(t, ti.linear_fit(x, 10), label='linear_fit')
ax.plot(t, ti.iir_lowpass(x, 1, 10), label='iir_lowpass')
ax.plot(t, ti.moving_min(x, 10), label='moving_min')
ax.plot(t, ti.moving_max(x, 10), label='moving_max')
ax.plot(t, ti.aema(x, 10), label='aema')
ax.grid(True)
ax.legend()
ax2 = fig.add_subplot(212)
ax2.plot(t, ti.rate_of_change(x, 20), 'x', label='rate_of_change')
ax2.plot(t, ti.acceleration(x, 20), 'o--', label='acceleration')
ax2.grid(True)
ax2.legend()
plt.show()