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add_gradients.py
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Sun, Jun 2, 15:38

add_gradients.py
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from types import SimpleNamespace
import numpy as np
from pypulseq.calc_duration import calc_duration
from pypulseq.make_arbitrary_grad import make_arbitrary_grad
from pypulseq.opts import Opts
from pypulseq.points_to_waveform import points_to_waveform
def add_gradients(grads: list, system=Opts(), max_grad: int = 0, max_slew: int = 0) -> np.ndarray:
"""
Superpose several gradient events.
Parameters
----------
grads : list
List of 'SimpleNamespace' gradient events.
system : Opts, optional
System limits. Default is a system limits object initialised to default values.
max_grad : float, optional
Maximum gradient amplitude. Default is 0.
max_slew : float, optional
Maximum slew rate. Default is 0.
Returns
-------
grad : SimpleNamespace
Superimposition of gradient events from `grads`.
"""
max_grad = max_grad if max_grad > 0 else system.max_grad
max_slew = max_slew if max_slew > 0 else system.max_slew
if len(grads) < 2:
raise Exception()
# First gradient defines channel
channel = grads[0].channel
# Find out the general delay of all gradients and other statistics
delays, firsts, lasts, durs = [], [], [], []
for ii in range(len(grads)):
delays.append(grads[ii].delay)
firsts.append(grads[ii].first)
lasts.append(grads[ii].last)
durs.append(calc_duration(grads[ii]))
# Convert to numpy.ndarray for fancy-indexing later on
firsts, lasts = np.array(firsts), np.array(lasts)
common_delay = min(delays)
total_duration = max(durs)
waveforms = dict()
max_length = 0
for ii in range(len(grads)):
g = grads[ii]
if g.type == 'grad':
waveforms[ii] = g.waveform
elif g.type == 'trap':
if g.flat_time > 0: # Triangle or trapezoid
times = [g.delay - common_delay,
g.delay - common_delay + g.rise_time,
g.delay - common_delay + g.rise_time + g.flat_time,
g.delay - common_delay + g.rise_time + g.flat_time + g.fall_time]
amplitudes = [0, g.amplitude, g.amplitude, 0]
else:
times = [g.delay - common_delay,
g.delay - common_delay + g.rise_time,
g.delay - common_delay + g.rise_time + g.flat_time]
amplitudes = [0, g.amplitude, 0]
waveforms[ii] = points_to_waveform(times=times, amplitudes=amplitudes,
grad_raster_time=system.grad_raster_time)
else:
raise ValueError('Unknown gradient type')
if g.delay - common_delay > 0:
# Stop for numpy.arange is not g.delay - common_delay - system.grad_raster_time like in Matlab
# so as to include the endpoint
t_delay = np.arange(0, g.delay - common_delay, step=system.grad_raster_time)
waveforms[ii] = np.insert(waveforms[ii], 0, t_delay)
num_points = len(waveforms[ii])
max_length = num_points if num_points > max_length else max_length
w = np.zeros(max_length)
for ii in range(len(grads)):
wt = np.zeros(max_length)
wt[0:len(waveforms[ii])] = waveforms[ii]
w += wt
grad = make_arbitrary_grad(channel, w, system, max_slew=max_slew, max_grad=max_grad, delay=common_delay)
grad.first = np.sum(firsts[np.where(delays == common_delay)])
grad.last = np.sum(lasts[np.where(durs == total_duration)])
return grad

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