def polygon(rmem=20., **params):
"polygon of pore + membrane for plotting"
setup = SetupNoGeo(**params)
params = nano.Params(pughpore.params) | setup.geop
r = [0.5*params.l3, 0.5*params.l2, 0.5*params.l1, 0.5*params.l0,
0.5*params.l4, rmem]
ztop = params.hpore/2.
zbot = -ztop
z = [zbot, ztop - params.h2, ztop - params.h1, ztop, zbot + params.h4,
zbot + params.hmem]
# indices: [(0,0), (0,1), (1,1), (1,2), ..., (5,5), (5,0)]
return [(r[i / 2 % 6], z[(i+1) / 2 % 6]) for i in range(12)]
def get_results(name, params, setup=setup_default, calc=True):
# setup is function rw = setup(params) that sets up rw
# check existing saved rws
data = None
if fields.exists(name, **params):
data = load_results(name, **params)
N = len(data.times)
else:
N = 0
# determine number of missing rws and run
N_missing = params["N"] - N
if N_missing > 0 and calc:
new_params = nanopores.Params(params, N=N_missing)
rw = setup(new_params)
run(rw, name)
rw.save(name)
data = load_results(name, **params)
# return results
elif data is None:
data = load_results(name, **params)
return data
import nanopores.geometries.pughpore as pughpore
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter
import numpy as np
import os
import sys
import nanopores.tools.fields as f
HOME = os.path.expanduser("~")
PAPERDIR = os.path.join(HOME, "papers", "paper-howorka")
FIGDIR = os.path.join(PAPERDIR, "figures", "")
DATADIR = os.path.join(HOME, "Dropbox", "nanopores", "fields")
f.set_dir_mega()
number = False
geop = nano.Params(pughpore.params)
hpore = geop.hpore
fieldsname = 'events3_onlyone_5'
params = dict(avgbind1=2e7,
avgbind2=3e4,
P_bind1=8.e-2,
P_bind2=0 * 3e-1,
z0=hpore / 2. + 0.)
#cmap=matplotlib.cm.get_cmap('viridis')
data = f.get_fields(fieldsname, **params)
figname = fieldsname + '_%.1e_%.1e_%.1e_%.1e' % (
params["avgbind1"], params["avgbind2"], params["P_bind1"],
params["P_bind2"]) + str(params["z0"])
t = data["t"]
tdata = np.array(t)
from matplotlib import gridspec
import matplotlib.path as mplPath
import numpy as np
from get_F import Force, Current
from nanopores.models.pughpore import polygon
from nanopores.models.pughpoints import plot_polygon
import matplotlib.pyplot as plt
import nanopores as nano
import nanopores.geometries.pughpore as pughpore
#import os
up = nano.Params(pughpore.params, k=3)
l0 = up.l0
l1 = up.l1
l2 = up.l2
l3 = up.l3
h1 = up.h1
h2 = up.h2
hpore = up.hpore
#import nanopores.tools.fields as f
#HOME = os.path.expanduser("~")
#PAPERDIR = os.path.join(HOME, "papers", "paper-howorka")
#FIGDIR = os.path.join(PAPERDIR, "figures", "")
#DATADIR = os.path.join(HOME,"Dropbox", "nanopores", "fields")
#f.set_dir(DATADIR)
# 30
#
import nanopores.tools.box as box
import nanopores.geometries.pughpore as pughpore
from nanopores.geometries.curved import Sphere
#from nanopores.models.mysolve import pbpnps
import nanopores.physics.simplepnps as simplepnps
import solvers
up = nano.user_params(
#up = nano.Params( # for iPython
h=2.,
Qmol=-1.,
Nmax=1e5,
R=30.,
)
geop = nano.Params(R=up.R, H=80., x0=[0., 0., 15.])
physp = nano.Params(
Qmol=up.Qmol,
bulkcon=300.,
dnaqsdamp=.5,
bV=-0.1,
)
solverp = nano.Params(
h=up.h,
frac=0.2,
Nmax=up.Nmax,
imax=30,
tol=1e-2,
cheapest=False,
)
import nanopores.geometries.pughpore as pughpore
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter
import numpy as np
import os
import sys
import nanopores.tools.fields as f
HOME = os.path.expanduser("~")
PAPERDIR = os.path.join(HOME, "Dropbox", "nanopores")
FIGDIR = os.path.join(PAPERDIR, "figures", "")
DATADIR = os.path.join(HOME, "Dropbox", "nanopores", "fields")
f.set_dir_mega()
number = False
geop = nanopores.Params(pughpore.params)
hpore = geop.hpore
fieldsname = 'eventsnew_both_1_'
params = dict(avgbind1=23e6,
avgbind2=3e4,
P_bind1=0.035,
P_bind2=3e-1,
z0=hpore / 2. + 0.)
drop, th = f.get("events_pugh_experiment", "drop", "t")
th = [1e0 * time for time in th]
#cmap=matplotlib.cm.get_cmap('viridis')
data = f.get_fields(fieldsname, **params)
figname = fieldsname + '_%.1e_%.1e_%.1e_%.1e' % (
params["avgbind1"], params["avgbind2"], params["P_bind1"],
fields.update()
F, Fel, Fdrag = fields.get_functions(name, "F", "Fel", "Fdrag", **params)
D, dist = fields.get_functions(name_D, "D", "dist", **params)
if __name__ == "__main__":
Fplot = nano.user_param(Fplot=False)
Dplot = nano.user_param(Dplot=False)
if Fplot:
plt = nanopore.Plotter(dim=2)
plt.plot_vector(F, title="F", interactive=True)
#plt.plot_vector(Fel, title="Fel")
#plt.plot_vector(Fdrag, title="Fdrag", interactive=True)
pore = WeiPore()
params = nano.Params(pore.default, **params)
sam, au, sin, _ = pore.polygons(params)
poly = MultiPolygon(Polygon(sam), Polygon(au), Polygon(sin)).nodes
streamlines(polygon=poly,
rx=100.,
ry=100.,
Nx=100,
Ny=100,
maxvalue=None,
F=F)
nano.showplots()
if Dplot:
plt = nanopore.Plotter(dim=2)
#plt.plot(dist, "dist")
plt.plot(D[1], "D", interactive=True)
#F, geo, phys = forcefields.F_geo_phys(p.overwrite, **fparams)
F, geo, phys = forcefields.F_geo_phys(**fparams)
# get additional boundary force
if bforce:
Fb, _ = boundary_force(mesh=geo.mesh, **fparams)
F = F + Fb
result = calculate_selectivity(F, geo, phys, **sparams)
result["params"] = params
return result
if __name__ == "__main__":
import numpy
results = nanopores.Params(selectivity(**default))
t = results.time
J = results.current
rel = results.release
params = results.params
plt.figure(0)
plt.semilogx(t, rel, "x-")
plt.xlabel("time [s]")
plt.ylabel("% release")
plt.title("reservoir size: %.0f nm" % (params["Ry"], ))
plt.ylim(ymin=0.)
def avg(J):
n = len(J)
J0 = list(numpy.array(J)[n * 0.2:n * 0.5])
default = nano.Params(
geop=nano.Params(
geoname="wei",
dim=2,
x0=None,
rMolecule=0.5,
receptor=None,
lcMolecule=0.1,
lcCenter=0.4,
),
physp=nano.Params(
Qmol=-1.,
bulkcon=1000.,
dnaqsdamp=.5,
bV=-0.1,
rDPore=.9,
Membraneqs=-0.0,
ahemqs=None,
ahemuniformqs=False,
posDTarget=True,
),
solverp=nano.Params(
h=1.,
frac=0.2,
Nmax=2e4,
imax=30,
tol=1e-2,
cheapest=False,
stokesiter=False, #True
diffusivity_data=None,
reconstruct=False,
fluid="fluid",
hybrid=True,
))
def load_results(name, **params):
data = fields.get_fields(name, **params)
data = nanopores.Params({k: _load(data[k]) for k in data})
print "Found %d simulated events." % len(data.times)
return data
# (c) 2016 Gregor Mitscha-Baude
" 1D PNP, modelling reservoirs and membrane far away from pore "
import nanopores as nano
import solvers
geop = nano.Params(
R = 35.,
H = 70.,
)
physp = nano.Params(
bulkcon = 1000.,
bV = -1.,
)
geo, pnp = solvers.solve1D(geop, physp)
solvers.visualize1D(geo, pnp)
nano.showplots()
params = nanopores.Params(
# simulation params
geoname="alphahem",
dim=2,
rMolecule=.5,
h=1.,
Nmax=1e5,
Qmol=-2.,
bV=0.5,
posDTarget=False,
R=21,
Hbot=21,
Htop=21,
geop=dict(R=21, Hbot=21, Htop=21),
ahemqs=None,
ahemuniformqs=False,
# random walk params
N=10000, # number of (simultaneous) random walks
dt=0.01, # time step [ns]
walldist=1., # in multiples of radius, should be >= 1
rstart=1.,
zstart=1.,
initial="disc", # oder "sphere"
# binding params
t_bind=1000.,
p_bind=1.,
eps_bind=0.1,
# stopping criterion: max time (w/o binding) and radius
Tmax=10000.,
Rmax=20.,
zstop=-1.28,
)
default = nano.Params(
geop = nano.Params(
dim = 3,
R = pughpore.params["R"],
H = pughpore.params["H"],
l0 = pughpore.params["l0"],
l1 = pughpore.params["l1"],
l2 = pughpore.params["l2"],
l3 = pughpore.params["l3"],
l4 = pughpore.params["l4"],
diamPore = 6., # will override l0,.. if set
diamDNA = 2.5, # will override l0,.. if diamPore set
x0 = pughpore.params["x0"],
rMolecule = pughpore.params["rMolecule"],
lcMolecule = pughpore.params["lcMolecule"],
center_z_at_x0 = False,
),
physp = nano.Params(
Qmol = 5., # charge of trypsin at pH 8.
bulkcon = 1000.,
dnaqsdamp = 0.7353,
bV = -0.1,
rDPore = .9,
bulkbc = True,
Membraneqs = -0.0,
),
solverp = nano.Params(
h = 1.5,
frac = 0.2,
Nmax = 6e5,
imax = 40,
tol = 1e-2,
cheapest = False,
stokesiter = False, #True
diffusivity_data = None,
diffusivity = None,
))
