def get_grad_P(qn, te, grad_P, temp):
'''
Returns the electron pressure gradient (in 1D) on the E-field grid using P = nkT and
finite difference.
INPUT:
qn -- Grid charge density
te -- Grid electron temperature
DX -- Grid separation, used for diagnostic purposes. Defaults to simulation dx.
inter_type -- Linear (0) or cubic spline (1) interpolation.
NOTE: Interpolation is needed because the finite differencing causes the result to be deposited on the
B-grid. Moving it back to the E-grid requires an interpolation. Cubic spline is desired due to its smooth
derivatives and its higher order weighting (without the polynomial craziness)
'''
grad_P[:] = qn * kB * te / q # Not actually grad P, just using this array to store Pe
# Putting [:] after array points to memory locations,
# and prevents deferencing
for ii in nb.prange(1, qn.shape[0]):
temp[ii] = (grad_P[ii] - grad_P[ii - 1]) / dx
temp[0] = temp[qn.shape[0] - 3]
aux.interpolate_to_center_cspline1D(temp, grad_P)
grad_P[0] = grad_P[qn.shape[0] - 3]
grad_P[qn.shape[0] - 2] = grad_P[1]
grad_P[qn.shape[0] - 1] = grad_P[2]
return
def get_grad_P(qn, te, inter_type=1):
'''
Returns the electron pressure gradient (in 1D) on the E-field grid using P = nkT and
finite difference.
INPUT:
qn -- Grid charge density
te -- Grid electron temperature
DX -- Grid separation, used for diagnostic purposes. Defaults to simulation dx.
inter_type -- Linear (0) or cubic spline (1) interpolation.
NOTE: Interpolation is needed because the finite differencing causes the result to be deposited on the
B-grid. Moving it back to the E-grid requires an interpolation. Cubic spline is desired due to its smooth
derivatives and its higher order weighting (without the polynomial craziness)
'''
grad_pe_B = np.zeros(qn.shape[0])
grad_P = np.zeros(qn.shape[0])
Pe = qn * kB * te / q
for ii in np.arange(1, qn.shape[0]):
grad_pe_B[ii] = (Pe[ii] - Pe[ii - 1])
grad_pe_B[0] = grad_pe_B[qn.shape[0] - 3]
# Re-interpolate to E-grid
if inter_type == 0:
grad_P = interpolate_to_center_linear_1D(grad_pe_B)
elif inter_type == 1:
grad_P = interpolate_to_center_cspline1D(grad_pe_B)
grad_P[0] = grad_P[qn.shape[0] - 3]
grad_P[qn.shape[0] - 2] = grad_P[1]
grad_P[qn.shape[0] - 1] = grad_P[2]
grad_P /= dx
return grad_P