def InTheWeedsPlot(OutBase,UnfoldObj,RefoldObj=[],Example=None,
Bins=[50,75,100,150,200,500,1000],**kwargs):
"""
Plots a detailed energy landscape, and saves
Args:
OutBase: where to start the save
UnfoldObj: unfolding objects
RefoldObj: refolding objects
Bins: how many bins to use in the energy landscape plots
<min/max>_landscape_kT: bounds on the landscape
Returns:
nothing
"""
# get the IWT
kT = 4.1e-21
for b in Bins:
LandscapeObj = InverseWeierstrass.\
FreeEnergyAtZeroForce(UnfoldObj,NumBins=b,RefoldingObjs=RefoldObj)
# make a 2-D histogram of everything
if (Example is not None):
fig = PlotUtilities.figure(figsize=(8,8))
ext_nm = Example.Separation*1e9
IWT_Util.ForceExtensionHistograms(ext_nm,
Example.Force*1e12,
AddAverage=False,
nBins=b)
PlotUtilities.savefig(fig,OutBase + "0_{:d}hist.pdf".format(b))
# get the distance to the transition state etc
print("DeltaG_Dagger is {:.1f}kT".format(Obj.DeltaGDagger))
fig = PlotUtilities.figure(figsize=(12,12))
plot_single_landscape(LandscapeObj,add_meta_half=True,
add_meta_free=True,**kwargs)
PlotUtilities.savefig(fig,OutBase + "1_{:d}IWT.pdf".format(b))
def run():
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
# run a comparison of fwd,rev,both
base = "../Data/"
plot_both = dict(color='b', linestyle='--', label="Bi-directional")
plot_unfold = dict(color='m', linestyle=':', label="Only unfold")
plot_refold = dict(color='r', linestyle='-', label="Only refold")
input_files = [
[base + "UnfoldandRefold.pxp", "", plot_both],
[base + "JustUnfold.pxp", "-unfold_only 1", plot_unfold],
[base + "JustRefold.pxp", "-refold_only 1", plot_refold],
]
fig = PlotUtilities.figure(figsize=(3.5, 6))
f_one_half_N = 12e-12
for f, extra_str, plot_opt in input_files:
# run just the 'normal' IO
x_nm, G_kT, tilt = run_single(n_pairs=50,
v=50e-9,
f_one_half=f_one_half_N,
input_file=f,
extra_str=extra_str)
# save out the data
header = "# (C) PRH \n #Extension (nm),\t G (kT), \t G_tilt (kT)"
fname = f.split("/")[-1] + ".csv"
np.savetxt(X=np.array((x_nm, G_kT, tilt)).T,
fname=fname,
header=header,
delimiter=",")
ax1 = plt.subplot(2, 1, 1)
plt.plot(x_nm, G_kT, **plot_opt)
label_y = ("$G_0$ ($k_\mathrm{B}$T)")
PlotUtilities.lazyLabel("", label_y, "")
PlotUtilities.no_x_label(ax=ax1)
plt.subplot(2, 1, 2)
plt.plot(x_nm, tilt, **plot_opt)
label_y = ("$G_\mathrm{F_{1/2}=" + "{:.0f}".format(f_one_half_N*1e12) +\
"pN}$ ($k_\mathrm{B}$T)")
PlotUtilities.lazyLabel("x (nm)", label_y, "")
PlotUtilities.savefig(fig, "example_unfold_refold.png")
# run just the 'normal' IO
x_nm,G_kT,tilt = \
run_single(n_pairs=16,v=20e-9,input_file="../Data/input.pxp")
fig = PlotUtilities.figure()
plt.plot(x_nm, G_kT, 'r-')
PlotUtilities.lazyLabel("x (nm)", "$G_0$ ($k_\mathrm{B}$T)", "")
PlotUtilities.savefig(fig, "example_bidirectional.png")
def TomPlot(LandscapeObj,OutBase,UnfoldObj,RefoldObj,idx,f_one_half_N=0e-12):
# get a forward and reverse
ToX = lambda x: x * 1e9
ToForceY = lambda y: y * 1e12
fig = PlotUtilities.figure(figsize=(8,4))
plt.subplot(1,2,1)
SubplotArgs = dict(alpha=0.4,linewidth=0.5)
FilterN = 500
Unfold = FEC_Util.GetFilteredForce(UnfoldObj[idx],FilterN)
Refold = FEC_Util.GetFilteredForce(RefoldObj[idx],FilterN)
UnfoldX = ToX(Unfold.Extension)
UnfoldY = ToForceY(Unfold.Force)
FoldX = ToX(Refold.Extension)
FoldY = ToForceY(Refold.Force)
plt.plot(UnfoldX,UnfoldY,color='r',label="Unfolding",
**SubplotArgs)
plt.plot(FoldX,FoldY,color='b',label="Refolding",
**SubplotArgs)
fontdict = dict(fontsize=13)
x_text_dict = dict(x=60, y=22.5, s="2 nm", fontdict=fontdict,
withdash=False,
rotation="horizontal")
y_text_dict = dict(x=59, y=27, s="5 pN", fontdict=fontdict, withdash=False,
rotation="vertical")
PlotUtilities.ScaleBar(x_kwargs=dict(x=[60,62],y=[24,24]),
y_kwargs=dict(x=[60,60],y=[25,30]),
text_x=x_text_dict,text_y=y_text_dict)
PlotUtilities.legend(loc=[0.4,0.8],**fontdict)
plt.subplot(1,2,2)
Obj = IWT_Util.TiltedLandscape(LandscapeObj,f_one_half_N=f_one_half_N)
plt.plot(Obj.landscape_ext_nm,Obj.OffsetTilted_kT)
plt.xlim([56,69])
plt.ylim([-1,4])
yoffset = 1
x_text_dict = dict(x=58.5, y=yoffset+1.5, s="2 nm", fontdict=fontdict,
withdash=False,rotation="horizontal")
y_text_dict = dict(x=57, y=yoffset+2.5, s=r"1 k$_\mathrm{b}$T",
fontdict=fontdict, withdash=False,
rotation="vertical")
PlotUtilities.ScaleBar(x_kwargs=dict(x=[58,60],
y=[yoffset+1.75,yoffset+1.75]),
y_kwargs=dict(x=[58,58],y=[yoffset+2,yoffset+3]),
text_x=x_text_dict,text_y=y_text_dict,
kill_axis=True)
PlotUtilities.savefig(fig,OutBase + "TomMockup" + str(idx) + ".png",
subplots_adjust=dict(bottom=-0.1))
# save out the data exactly as we want to plot it
common = dict(delimiter=",")
ext = str(idx) + ".txt"
np.savetxt(X=np.c_[UnfoldX,UnfoldY],fname=OutBase+"Unfold" + ext,**common)
np.savetxt(X=np.c_[FoldX,FoldY],fname=OutBase+"Fold"+ext,**common)
np.savetxt(X=np.c_[Obj.landscape_ext_nm,Obj.OffsetTilted_kT],
fname=OutBase+"Landscape"+ext,**common)