Author: tlinnet
Date: Tue Jun 17 14:53:49 2014
New Revision: 24033
URL: http://svn.gna.org/viewcvs/relax?rev=24033&view=rev
Log:
More fixes for numpy index in lib functions.
Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion
models for Clustered analysis.
Modified:
branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_3d.py
branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_star.py
branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py
Modified: branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_3d.py
URL:
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_3d.py?rev=24033&r1=24032&r2=24033&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_3d.py (original)
+++ branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_3d.py Tue Jun 17
14:53:49 2014
@@ -133,10 +133,10 @@
for mi in range(NM):
# Extract the values from the higher dimensional arrays.
- R2A_si_mi=r20a[0][si][mi][0][0]
- R2B_si_mi=r20b[0][si][mi][0][0]
- dw_si_mi = dw[0][si][mi][0][0]
- num_points_si_mi = int(num_points[0][si][mi][0])
+ R2A_si_mi=r20a[0, si, mi, 0, 0]
+ R2B_si_mi=r20b[0, si, mi, 0, 0]
+ dw_si_mi = dw[0, si, mi, 0, 0]
+ num_points_si_mi = int(num_points[0, si, mi, 0])
# The matrix R that contains all the contributions to the
evolution, i.e. relaxation, exchange and chemical shift evolution.
R = rcpmg_3d(R1A=r10a, R1B=r10b, R2A=R2A_si_mi, R2B=R2B_si_mi,
pA=pA, pB=pB, dw=dw_si_mi, k_AB=k_AB, k_BA=k_BA)
@@ -144,10 +144,10 @@
# Loop over the time points, back calculating the R2eff values.
for di in range(num_points_si_mi):
# Extract the values from the higher dimensional arrays.
- tcp_si_mi_di = tcp[0][si][mi][0][di]
- inv_tcpmg_si_mi_di = inv_tcpmg[0][si][mi][0][di]
- power_si_mi_di = int(power[0][si][mi][0][di])
- r20a_si_mi_di = r20a[0][si][mi][0][di]
+ tcp_si_mi_di = tcp[0, si, mi, 0, di]
+ inv_tcpmg_si_mi_di = inv_tcpmg[0, si, mi, 0, di]
+ power_si_mi_di = int(power[0, si, mi, 0, di])
+ r20a_si_mi_di = r20a[0, si, mi, 0, di]
# Initial magnetisation.
Mint = M0
@@ -169,9 +169,9 @@
# The next lines calculate the R2eff using a two-point
approximation, i.e. assuming that the decay is mono-exponential.
Mx = Mint[1] / pA
if Mx <= 0.0 or isNaN(Mx):
- back_calc[0][si][mi][0][di] = r20a_si_mi_di
+ back_calc[0, si, mi, 0, di] = r20a_si_mi_di
else:
- back_calc[0][si][mi][0][di] = - inv_tcpmg_si_mi_di *
log(Mx)
+ back_calc[0, si, mi, 0, di] = - inv_tcpmg_si_mi_di *
log(Mx)
# Replace data in array.
# If dw is zero.
Modified: branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_star.py
URL:
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_star.py?rev=24033&r1=24032&r2=24033&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_star.py
(original)
+++ branches/disp_spin_speed/lib/dispersion/ns_cpmg_2site_star.py Tue
Jun 17 14:53:49 2014
@@ -142,10 +142,10 @@
for mi in range(NM):
# Extract the values from the higher dimensional arrays.
- R2A_si_mi=r20a[0][si][mi][0][0]
- R2B_si_mi=r20b[0][si][mi][0][0]
- dw_si_mi = dw[0][si][mi][0][0]
- num_points_si_mi = int(num_points[0][si][mi][0])
+ R2A_si_mi=r20a[0, si, mi, 0, 0]
+ R2B_si_mi=r20b[0, si, mi, 0, 0]
+ dw_si_mi = dw[0, si, mi, 0, 0]
+ num_points_si_mi = int(num_points[0, si, mi, 0])
# The matrix that contains only the R2 relaxation terms
("Redfield relaxation", i.e. non-exchange broadening).
Rr[0, 0] = -R2A_si_mi
@@ -164,10 +164,10 @@
# Loop over the time points, back calculating the R2eff values.
for di in range(num_points_si_mi):
# Extract the values from the higher dimensional arrays.
- tcp_si_mi_di = tcp[0][si][mi][0][di]
- inv_tcpmg_si_mi_di = inv_tcpmg[0][si][mi][0][di]
- power_si_mi_di = int(power[0][si][mi][0][di])
- r20a_si_mi_di = r20a[0][si][mi][0][di]
+ tcp_si_mi_di = tcp[0, si, mi, 0, di]
+ inv_tcpmg_si_mi_di = inv_tcpmg[0, si, mi, 0, di]
+ power_si_mi_di = int(power[0, si, mi, 0, di])
+ r20a_si_mi_di = r20a[0, si, mi, 0, di]
# This matrix is a propagator that will evolve the
magnetization with the matrix R for a delay tcp.
eR_tcp = matrix_exponential(R*tcp_si_mi_di)
@@ -184,9 +184,9 @@
# The next lines calculate the R2eff using a two-point
approximation, i.e. assuming that the decay is mono-exponential.
Mx = Moft[0].real / M0[0]
if Mx <= 0.0 or isNaN(Mx):
- back_calc[0][si][mi][0][di] = 1e99
+ back_calc[0, si, mi, 0, di] = 1e99
else:
- back_calc[0][si][mi][0][di]= -inv_tcpmg_si_mi_di *
log(Mx)
+ back_calc[0, si, mi, 0, di]= -inv_tcpmg_si_mi_di *
log(Mx)
# Replace data in array.
# If dw is zero.
Modified: branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py
URL:
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py?rev=24033&r1=24032&r2=24033&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py (original)
+++ branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py Tue Jun 17
14:53:49 2014
@@ -142,11 +142,11 @@
# Loop over offsets:
for oi in range(NO):
- r20a_si_mi_oi = R20A[si][mi][oi][0]
- r20b_si_mi_oi = R20B[si][mi][oi][0]
- dw_si_mi_oi = dw[si][mi][oi][0]
- dwH_si_mi_oi = dwH[si][mi][oi][0]
- num_points_si_mi_oi = num_points[si][mi][oi]
+ r20a_si_mi_oi = R20A[si, mi, oi, 0]
+ r20b_si_mi_oi = R20B[si, mi, oi, 0]
+ dw_si_mi_oi = dw[si, mi, oi, 0]
+ dwH_si_mi_oi = dwH[si, mi, oi, 0]
+ num_points_si_mi_oi = num_points[si, mi, oi]
# Populate the m1 and m2 matrices (only once per function
call for speed).
populate_matrix(matrix=m1, R20A=r20a_si_mi_oi,
R20B=r20b_si_mi_oi, dw=-dw_si_mi_oi - dwH_si_mi_oi, k_AB=k_AB, k_BA=k_BA)
# D+ matrix component.
@@ -155,8 +155,8 @@
# Loop over the time points, back calculating the R2eff
values.
for i in range(num_points_si_mi_oi):
# The M1 and M2 matrices.
- M1 = matrix_exponential(m1*tcp[si][mi][oi][i]) #
Equivalent to D+.
- M2 = matrix_exponential(m2*tcp[si][mi][oi][i]) #
Equivalent to Z-.
+ M1 = matrix_exponential(m1*tcp[si, mi, oi, i]) #
Equivalent to D+.
+ M2 = matrix_exponential(m2*tcp[si, mi, oi, i]) #
Equivalent to Z-.
# The complex conjugates M1* and M2*
M1_star = conj(M1) # Equivalent to D+*.
@@ -173,7 +173,7 @@
M2_M1_M1_M2_star = dot(M2_M1_star, M1_M2_star)
# Special case of 1 CPMG block - the power is zero.
- if power[si][mi][oi][i] == 1:
+ if power[si, mi, oi, i] == 1:
# M1.M2.
A = M1_M2
@@ -187,9 +187,9 @@
D = M2_M1_star
# Matrices for even number of CPMG blocks.
- elif power[si][mi][oi][i] % 2 == 0:
+ elif power[si, mi, oi, i] % 2 == 0:
# The power factor (only calculate once).
- fact = int(floor(power[si][mi][oi][i] / 2))
+ fact = int(floor(power[si, mi, oi, i] / 2))
# (M1.M2.M2.M1)^(n/2).
A = square_matrix_power(M1_M2_M2_M1, fact)
@@ -206,7 +206,7 @@
# Matrices for odd number of CPMG blocks.
else:
# The power factor (only calculate once).
- fact = int(floor((power[si][mi][oi][i] - 1) / 2))
+ fact = int(floor((power[si, mi, oi, i] - 1) / 2))
# (M1.M2.M2.M1)^((n-1)/2).M1.M2.
A = square_matrix_power(M1_M2_M2_M1, fact)
@@ -230,9 +230,9 @@
Mx = dot(dot(F_vector, (A_B + C_D)), M0)
Mx = Mx.real / 2.0
if Mx <= 0.0 or isNaN(Mx):
- back_calc[si][mi][oi][i] = 1e99
+ back_calc[si, mi, oi, i] = 1e99
else:
- back_calc[si][mi][oi][i]= -inv_tcpmg[si][mi][oi][i]
* log(Mx / pA)
+ back_calc[si, mi, oi, i]= -inv_tcpmg[si, mi, oi, i]
* log(Mx / pA)
def r2eff_ns_mmq_2site_sq_dq_zq(M0=None, F_vector=array([1, 0], float64),
m1=None, m2=None, R20A=None, R20B=None, pA=None, pB=None, dw=None, dwH=None,
k_AB=None, k_BA=None, inv_tcpmg=None, tcp=None, back_calc=None,
num_points=None, power=None):
@@ -292,10 +292,10 @@
# Loop over offsets:
for oi in range(NO):
- r20a_si_mi_oi = R20A[si][mi][oi][0]
- r20b_si_mi_oi = R20B[si][mi][oi][0]
- dw_si_mi_oi = dw[si][mi][oi][0]
- num_points_si_mi_oi = num_points[si][mi][oi]
+ r20a_si_mi_oi = R20A[si, mi, oi, 0]
+ r20b_si_mi_oi = R20B[si, mi, oi, 0]
+ dw_si_mi_oi = dw[si, mi, oi, 0]
+ num_points_si_mi_oi = num_points[si, mi, oi]
# Populate the m1 and m2 matrices (only once per function
call for speed).
populate_matrix(matrix=m1, R20A=r20a_si_mi_oi ,
R20B=r20b_si_mi_oi, dw=dw_si_mi_oi, k_AB=k_AB, k_BA=k_BA)
@@ -304,19 +304,19 @@
# Loop over the time points, back calculating the R2eff
values.
for i in range(num_points_si_mi_oi):
# The A+/- matrices.
- A_pos = matrix_exponential(m1*tcp[si][mi][oi][i])
- A_neg = matrix_exponential(m2*tcp[si][mi][oi][i])
+ A_pos = matrix_exponential(m1*tcp[si, mi, oi, i])
+ A_neg = matrix_exponential(m2*tcp[si, mi, oi, i])
# The evolution for one n.
evol_block = dot(A_pos, dot(A_neg, dot(A_neg, A_pos)))
# The full evolution.
- evol = square_matrix_power(evol_block,
power[si][mi][oi][i])
+ evol = square_matrix_power(evol_block, power[si, mi, oi,
i])
# The next lines calculate the R2eff using a two-point
approximation, i.e. assuming that the decay is mono-exponential.
Mx = dot(F_vector, dot(evol, M0))
Mx = Mx.real
if Mx <= 0.0 or isNaN(Mx):
- back_calc[si][mi][oi][i] = 1e99
+ back_calc[si, mi, oi, i] = 1e99
else:
- back_calc[si][mi][oi][i] = -inv_tcpmg[si][mi][oi][i]
* log(Mx / pA)
+ back_calc[si, mi, oi, i] = -inv_tcpmg[si, mi, oi, i]
* log(Mx / pA)
r24033 - in /branches/disp_spin_speed/lib/dispersion: ns_cpmg_2site_3d.py ns_cpmg_2site_star.py ns_mmq_2site.py