def test_waveforms(self):
"""
Tests waveforms against matlab code results.
"""
expected_gy = get_data_with_key(TEST_DIR, TEST_FILE, "gy")
Np = 32
fov = 7
smax = 15000
gmax = 4
gamma = 4257
dt = 4e-6
kmax = 1 / (fov / Np) / 2
area = kmax / gamma
gy = minimum_time_gradient(area, gmax, smax, dt)
self.assertTrue(np.allclose(expected_gy, gy))
def test_waveforms(self):
"""
Tests waveforms against matlab code results.
"""
expected_gy = get_data_with_key(TEST_DIR, TEST_FILE, "gy")
Np = 32
fov = 7
smax = 15000
gmax = 4
gamma = 4257
dt = 4e-6
kmax = 1/(fov/Np)/2
area = kmax / gamma
gy = minimum_time_gradient(area, gmax, smax, dt)
self.assertTrue(np.allclose(expected_gy, gy))
def generate_readout(self, Nf, Fov_r, bwpp, negate=-1, pre_delay=0, readout_delay=1):
"""
Input:
Nf: The number of frequency encodes
Fov_r: The desired field of view (cm)
bwpp: The desired bandwidth per pixel (Hz/pixel)
Output:
gro: Gradient waveform.
rowin: Indices corresponding to the readout portion of the gradient.
"""
res = Fov_r / Nf
Wkx = 1 / res
area = Wkx / self._gamma
G = bwpp / res / self._gamma
Tro = Wkx / self._gamma / G
Tramp = G / self._s_max
t1 = Tramp
t2 = t1 + Tro
T = Tramp * 2 + Tro
N = int(np.floor(T / self._dt))
t = np.arange(1, N + 1) * self._dt
idx1 = np.where(t < t1)
idx2 = np.where((t >= t1) & (t < t2))
idx3 = np.where(t >= t2)
gro = np.zeros(N)
gro[idx1] = self._s_max * t[idx1]
gro[idx2] = G
gro[idx3] = T * self._s_max - self._s_max * t[idx3]
areaTrapz = (T + Tro) * G/2
gpre = minimum_time_gradient(areaTrapz/2, self._g_max, self._s_max, self._dt)
rowin = pre_delay + gpre.size + readout_delay + np.asarray(idx2)
gro = np.concatenate((np.zeros(pre_delay), negate * gpre, np.zeros(readout_delay), gro))
return gro, rowin
def generate_phase_encodes(self, Np, For_p, delay=0):
"""
Input:
Np: The number of phase encodes
Fov_p: The desired field of view (cm)
Output:
grpe: Gradient waveform.
petable: Indices corresponding to the readout portion of the gradient.
"""
kmax = 1 / (For_p / Np) / 2
area = kmax / self._gamma
grpe = minimum_time_gradient(area, self._g_max, self._s_max, self._dt)
petable = delay + np.arange(Np/2 - .5, -Np/2 + .5 - 1, -1) / (Np/2)
grpe = np.concatenate((np.zeros(delay), grpe))
return grpe, petable
