def plot_Upair_crossval_sigma():
# plot collective variable potentials
n_pair_gauss = 40
lin_pot = False
fixed_a = True
using_U0 = True
using_cv = False
fix_back = True
fix_exvol = False
using_cv_r0 = False
using_D2 = False
n_cross_val_sets = 5
pair_symmetry = "shared"
n_cv_test_funcs = 100
n_cv_basis_funcs = 40
bond_cutoff = 4
r_vals = np.linspace(0.1, 2, 300)
methods = ["force-matching", "eigenpair", "eigenpair"]
a_coeffs = [1, 0.027, 0.000135]
plt.figure()
for i in range(len(methods)):
cg_method = methods[i]
a_coeff = a_coeffs[i]
cg_savedir = util.Ucg_dirname(cg_method, M, using_U0, fix_back,
fix_exvol, bond_cutoff, using_cv,
n_cv_basis_funcs=n_cv_basis_funcs, n_cv_test_funcs=n_cv_test_funcs,
a_coeff=a_coeff, n_pair_gauss=n_pair_gauss, cv_lin_pot=lin_pot,
pair_symmetry=pair_symmetry)
print(cg_savedir)
Ucg, cv_r0_basis, cv_r0_test = util.create_polymer_Ucg( msm_savedir,
n_beads, M, beta, fix_back, fix_exvol, using_cv, using_D2,
n_cv_basis_funcs, n_cv_test_funcs, n_pair_gauss, bond_cutoff,
cv_lin_pot=lin_pot, a_coeff=a_coeff, pair_symmetry=pair_symmetry)
coeff = np.load(cg_savedir + "/rdg_fixed_sigma_cstar.npy")
Upair = Ucg.Upair_values(coeff, r_vals)[0]
#Upair -= Upair.min()
if cg_method == "force-matching":
label = "FM"
else:
label = r"EG $a = {:.2e}$".format(a_coeff)
plt.plot(r_vals, beta*Upair, label=label, lw=2)
plt.xlim(0.25, 1.25)
plt.ylim(-1, 3)
plt.legend()
plt.xlabel("$r$ (nm)")
plt.ylabel(r"$U_{\mathrm{pair}}(r)$ (k$_B$T)")
plt.savefig("plots/Upair_crossval_sigma.pdf")
plt.savefig("plots/Upair_crossval_sigma.png")
def plot_Ucv_crossval_sigma():
# plot collective variable potentials
n_pair_gauss = None
lin_pot = True
fixed_a = True
using_U0 = True
using_cv = True
fix_back = True
fix_exvol = False
using_cv_r0 = False
using_D2 = False
n_cross_val_sets = 5
pair_symmetry = None
n_cv_test_funcs = 100
n_cv_basis_funcs = 40
bond_cutoff = 4
methods = ["force-matching", "eigenpair", "eigenpair"]
a_coeffs = [1, 0.027, 0.000135]
plt.figure()
for i in range(len(methods)):
cg_method = methods[i]
a_coeff = a_coeffs[i]
cg_savedir = util.Ucg_dirname(cg_method, M, using_U0, fix_back,
fix_exvol, bond_cutoff, using_cv,
n_cv_basis_funcs=n_cv_basis_funcs, n_cv_test_funcs=n_cv_test_funcs,
a_coeff=a_coeff, n_pair_gauss=n_pair_gauss, cv_lin_pot=lin_pot,
pair_symmetry=pair_symmetry)
print(cg_savedir)
Ucg, cv_r0_basis, cv_r0_test = util.create_polymer_Ucg( msm_savedir,
n_beads, M, beta, fix_back, fix_exvol, using_cv, using_D2,
n_cv_basis_funcs, n_cv_test_funcs, n_pair_gauss, bond_cutoff,
cv_lin_pot=lin_pot, a_coeff=a_coeff, pair_symmetry=pair_symmetry)
cv_grid = np.linspace(1.3*cv_r0_basis.min(), 1.2*cv_r0_basis.max(), 200)
coeff = np.load(cg_savedir + "/rdg_fixed_sigma_cstar.npy")
Ucv = Ucg.Ucv_values(coeff, cv_grid)
Ucv -= Ucv.min()
if cg_method == "force-matching":
label = "FM"
else:
label = r"EG $a = {:.2e}$".format(a_coeff)
plt.plot(cv_grid, beta*Ucv, label=label, lw=2)
#plt.legend(title=r"$n_{basis}$ $n_{test}$", fontsize=12)
plt.legend()
plt.xlabel("TIC1 $\psi_1$")
plt.ylabel(r"$U_{\mathrm{cv}}(\psi_1)$ (k$_B$T)")
plt.savefig("plots/Ucv_crossval_sigma.pdf")
plt.savefig("plots/Ucv_crossval_sigma.png")
def compare_Ucv_for_free_a_coeff():
n_basis_test = [[40, 40], [40, 100], [100, 100], [100, 200]]
#n_basis_test = [[40, 40], [40, 100], [100, 100]]
plt.figure()
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))
for n_basis, n_test in n_basis_test:
print(" {} {}".format(n_basis, n_test))
temp_eg_savedir = eg_savedir + "_{}_{}_crossval_{}".format(n_basis, n_test, n_cross_val_sets)
eg_coeff = np.load(temp_eg_savedir + "/rdg_cstar.npy")
D = 1./eg_coeff[-1]
cg_savedir = util.Ucg_dirname(cg_method, M, using_U0, fix_back, fix_exvol,
bond_cutoff, using_cv, n_cv_basis_funcs=n_basis,
n_cv_test_funcs=n_test, a_coeff=a_coeff)
Ucg, cv_r0_basis, cv_r0_test = util.create_polymer_Ucg(
msm_savedir, n_beads, M, beta, fix_back, fix_exvol, using_cv,
using_D2, n_basis, n_test, n_pair_gauss,
bond_cutoff)
U = Ucg.Ucv_values(coeff, cv_r0_basis[:,0])
#plt.plot(cv_r0_basis, U, label=r"$n_{{basis}} = {}$ $n_{{test}} = {}$".format(n_basis, n_test))
ln1 = ax1.plot(cv_r0_basis, U, label=r"${}$ ${}$".format(n_basis, n_test))
ax2.plot(cv_r0_basis, D*np.ones(len(cv_r0_basis)))
temp_fm_savedir = fm_savedir + "_{}_{}_crossval_{}".format(n_basis, n_test, n_cross_val_sets)
if os.path.exists(temp_fm_savedir + "/rdg_cstar.npy"):
fm_coeff = np.load(temp_fm_savedir + "/rdg_cstar.npy")
U_fm = np.zeros(len(cv_r0_basis))
for i in range(len(fm_coeff)):
U_fm += fm_coeff[i]*Ucg.cv_U_funcs[i](cv_r0_basis[:,0])
U_fm -= U_fm.min()
ax1.plot(cv_r0_basis, U_fm, ls="--", color=ln1[0].get_color(), label=r"${}$ FM".format(n_basis))
ax1.legend(title=r"$n_{basis}$ $n_{test}$", fontsize=12)
ax1.set_xlabel("TIC1")
ax1.set_ylabel(r"$U_{cg}$ (k$_B$T)")
ax2.set_xlabel("TIC1")
ax2.set_ylabel(r"$D$")
fig.savefig("plots/compare_Ucg_ntest_nbasis.pdf")
fig.savefig("plots/compare_Ucg_ntest_nbasis.png")
def plot_Ucv_for_EG_FM_bondcuts_3_4():
method_code = ["EG", "EG", "FM", "FM"]
cg_method = ["eigenpair", "eigenpair", "force-matching", "force-matching"]
bondcut = [4, 3, 4, 3]
linesty = ["-", "--", "-", "--"]
colors = ["k", "k", "r", "r"]
legend = ["spectral", "spectral", "force match", "force match"]
a_coeff = [0.027, 0.027, None, None]
plt.figure()
for i in range(len(method_code)):
print("{} |i - j| >= {}".format(legend[i], bondcut[i]))
cg_savedir = util.Ucg_dirname(cg_method[i],
M,
using_U0,
fix_back,
fix_exvol,
bondcut[i],
using_cv,
n_cv_basis_funcs=n_basis,
n_cv_test_funcs=n_test,
a_coeff=a_coeff[i])
os.chdir(cg_savedir)
if os.path.exists("alpha_sigma_valid_mse.npy"):
label = r"{} $|i - j|$ >= ${}$".format(legend[i], bondcut[i])
vl_mse = np.load("alpha_sigma_valid_mse.npy")
sigma_idx, alpha_idx = np.load("best_sigma_alpha_idx.npy")
new_sigma = np.load("scaled_sigma_vals.npy")
at_best_alpha = vl_mse[:, alpha_idx, 0]
#plt.plot(new_sigma, at_best_alpha, color=colors[i], ls=linesty[i], label=label)
plt.plot(new_sigma, at_best_alpha, label=label)
os.chdir("..")
plt.legend(loc=2)
#plt.ylim(1e-3, 1e12)
plt.ylim(1e-10, 1e12)
plt.semilogy()
plt.xlabel(r"Scaled radius $\sigma_{ex}$ (nm)")
plt.ylabel(r"Crossval score")
plt.savefig("plots/compare_crossval_vs_scaled_sigma.pdf")
plt.savefig("plots/compare_crossval_vs_scaled_sigma.png")
name = "c" + str(n_beads)
T = 300
kb = 0.0083145
beta = 1./(kb*T)
if a_coeff is None:
fixed_a = False
else:
fixed_a = True
using_D2 = False
n_cross_val_sets = 5
cg_savedir = util.Ucg_dirname(cg_method, M, using_U0, fix_back,
fix_exvol, bond_cutoff, using_cv,
n_cv_basis_funcs=n_cv_basis_funcs, n_cv_test_funcs=n_cv_test_funcs,
a_coeff=a_coeff, n_pair_gauss=n_pair_gauss, cv_lin_pot=lin_pot,
pair_symmetry=pair_symmetry)
print(cg_savedir)
# create potential energy function
Ucg, cv_r0_basis, cv_r0_test = util.create_polymer_Ucg( msm_savedir,
n_beads, M, beta, fix_back, fix_exvol, using_cv, using_D2,
n_cv_basis_funcs, n_cv_test_funcs, n_pair_gauss, bond_cutoff,
cv_lin_pot=lin_pot, a_coeff=a_coeff, pair_symmetry=pair_symmetry)
if cg_method == "force-matching":
# only get trajectories that have saved forces
temp_forcenames = glob.glob("run_*/" + name + "_forces_*.dat")
n_dim = 3 * n_beads
name = "c" + str(n_beads)
T = 300
kb = 0.0083145
beta = 1. / (kb * T)
#n_pair_gauss = 10
using_D2 = False
n_cross_val_sets = 5
cg_savedir = util.Ucg_dirname("force-matching",
M,
using_U0,
fix_back,
fix_exvol,
bond_cutoff,
using_cv,
n_cv_basis_funcs=n_cv_basis_funcs,
n_cv_test_funcs=n_cv_test_funcs,
n_pair_gauss=n_pair_gauss,
pair_symmetry=pair_symmetry)
print(cg_savedir)
#print("building basis function database...")
Ucg, cv_r0_basis, cv_r0_test = util.create_polymer_Ucg(
msm_savedir,
n_beads,
M,
beta,
fix_back,
#plt.semilogy()
#plt.xlabel(r"Scaled radius $\sigma_{\mathrm{ex}}$ (nm)")
#plt.ylabel(r"Crossval score")
#plt.savefig("plots/compare_crossval_vs_scaled_sigma_nobc_3.pdf")
#plt.savefig("plots/compare_crossval_vs_scaled_sigma_nobc_3.png")
plt.figure()
for i in range(len(method_code)):
print("{} |i - j| >= {}".format(legend[i], bondcut[i]))
cg_savedir = util.Ucg_dirname(cg_method[i],
M,
using_U0,
fix_back,
fix_exvol,
bondcut[i],
using_cv,
n_cv_basis_funcs=n_basis,
n_cv_test_funcs=n_test,
a_coeff=a_coeff[i])
if os.path.exists(cg_savedir + "/rdg_fixed_sigma_cstar.npy"):
coeff = np.load(cg_savedir + "/rdg_fixed_sigma_cstar.npy")
Ucg, cv_r0_basis, cv_r0_test = util.create_polymer_Ucg(
msm_savedir,
n_beads,
M,
beta,
fix_back,
fix_exvol,