def makearbitrarygrad(kwargs):
"""
Makes a Holder object for an arbitrary gradient Event.
Parameters
----------
kwargs : dict
Key value mappings of RF Event parameters_params and values.
Returns
-------
grad : Holder
Trapezoidal gradient Event configured based on supplied kwargs.
"""
channel = kwargs.get("channel", "z")
system = kwargs.get("system", Opts())
waveform = kwargs.get("waveform")
max_grad_result = kwargs.get("max_grad", 0)
max_slew_result = kwargs.get("max_slew", 0)
max_grad = max_grad_result if max_grad_result > 0 else system.max_grad
max_slew = max_slew_result if max_slew_result > 0 else system.max_slew
g = waveform
slew = (g[0][1:] - g[0][0:-1]) / system.grad_raster_time
if max(abs(slew)) > max_slew:
raise ValueError('Slew rate violation {:f}'.format(
max(abs(slew)) / max_slew * 100))
if max(abs(g[0])) > max_grad:
raise ValueError('Gradient amplitude violation {:f}'.format(
max(abs(g)) / max_grad * 100))
grad = Holder()
grad.type = 'grad'
grad.channel = channel
grad.waveform = g
grad.t = np.array([[x * system.grad_raster_time
for x in range(len(g[0]))]])
return grad
def get_block(self, block_index):
"""
Returns Block at position specified by block_index.
Parameters
----------
block_index : int
Index of Block to be retrieved.
Returns
-------
block : dict
Block at position specified by block_index.
"""
block = {}
event_ind = self.block_events[block_index]
if event_ind[0] > 0:
delay = Holder()
delay.type = 'delay'
delay.delay = self.delay_library.data[event_ind[0]]
block['delay'] = delay
elif event_ind[1] > 0:
rf = Holder()
rf.type = 'rf'
lib_data = self.rf_library.data[event_ind[1]]
amplitude, mag_shape, phase_shape = lib_data[0], lib_data[1], lib_data[
2]
shape_data = self.shape_library.data[mag_shape]
compressed = Holder()
compressed.num_samples = shape_data[0][0]
compressed.data = shape_data[0][1:]
compressed.data = compressed.data.reshape(
(1, compressed.data.shape[0]))
mag = decompress_shape(compressed)
shape_data = self.shape_library.data[phase_shape]
compressed.num_samples = shape_data[0][0]
compressed.data = shape_data[0][1:]
compressed.data = compressed.data.reshape(
(1, compressed.data.shape[0]))
phase = decompress_shape(compressed)
rf.signal = 1j * 2 * np.pi * phase
rf.signal = amplitude * mag * np.exp(rf.signal)
rf.t = [(x * self.rf_raster_time)
for x in range(1,
max(mag.shape) + 1)]
rf.t = np.reshape(rf.t, (1, len(rf.t)))
rf.freq_offset = lib_data[3]
rf.phase_offset = lib_data[4]
if max(lib_data.shape) < 6:
lib_data = np.append(lib_data, 0)
rf.dead_time = lib_data[5]
block['rf'] = rf
grad_channels = ['gx', 'gy', 'gz']
for i in range(1, len(grad_channels) + 1):
if event_ind[2 + (i - 1)] > 0:
grad, compressed = Holder(), Holder()
type = self.grad_library.type[event_ind[2 + (i - 1)]]
lib_data = self.grad_library.data[event_ind[2 + (i - 1)]]
grad.type = 'trap' if type == 't' else 'grad'
grad.channel = grad_channels[i - 1][1]
if grad.type == 'grad':
amplitude = lib_data[0]
shape_id = lib_data[1]
shape_data = self.shape_library.data[shape_id]
compressed.num_samples = shape_data[0][0]
compressed.data = np.array([shape_data[0][1:]])
g = decompress_shape(compressed)
grad.waveform = amplitude * g
grad.t = np.array([[
x * self.grad_raster_time for x in range(1, g.size + 1)
]])
else:
grad.amplitude, grad.rise_time, grad.flat_time, grad.fall_time = [
lib_data[x] for x in range(4)
]
grad.area = grad.amplitude * (
grad.flat_time + grad.rise_time / 2 + grad.fall_time / 2)
grad.flat_area = grad.amplitude * grad.flat_time
block[grad_channels[i - 1]] = grad
if event_ind[5] > 0:
lib_data = self.adc_library.data[event_ind[5]]
if max(lib_data.shape) < 6:
lib_data = np.append(lib_data, 0)
adc = Holder()
adc.num_samples, adc.dwell, adc.delay, adc.freq_offset, adc.phase_offset, adc.dead_time = [
lib_data[x] for x in range(6)
]
adc.type = 'adc'
block['adc'] = adc
return block