In [1]:
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
from scipy.interpolate import interp2d
import sys
import argparse
import os
import numpy as np
from numpy.random import uniform
import pandas as pd
import datetime
# %matplotlib inline
%matplotlib notebook
In [ ]:
pre = "/Users/weilu/Research/server/oct_2017/23oct/"
perturbation_table = {0:"original", 1:"p_mem", 2:"m_mem", 3:"p_lipid", 4:"m_lipid"}
folder_list = [
'memb_3_rg_0.1_lipid_1_extended',
'memb_3_rg_0.1_lipid_1_topology'
]
temp_list = [450, 500, 550]
perturbation_list = [0, 1, 2, 3, 4]
force_list = ["0.0", "0.1", "0.2"]
In [115]:
In [113]:
all_pmf_list = []
all_evpb_list = []
for folder in folder_list:
for temp in temp_list:
for perturbation in perturbation_list:
# evpb
if perturbation == 0:
location = pre + "{}/1d_dis/t_all/force_0.0/evpb-{}.dat".format(folder, temp)
else:
location = pre + \
"{}/1d_dis/t_all/force_0.0/perturbation-{}-evpb-{}.dat".format(folder, perturbation, temp)
name_list = ["Lipid", "Go", "Mem", "Rg"]
names = ["bin", "x"] + name_list
data = pd.read_table(location, skiprows=1, sep='\s+', names=names).assign(folder=folder, temp=temp, perturbation=perturbation_table[perturbation])
all_evpb_list.append(data)
# pmf
if perturbation == 0:
location = pre + "{}/1d_dis/t_all/force_0.0/pmf-{}.dat".format(folder, temp)
else:
location = pre + \
"{}/1d_dis/t_all/force_0.0/perturbation-{}-pmf-{}.dat".format(folder, perturbation, temp)
name_list = ["f", "df", "e", "s"]
names = ["bin", "x"] + name_list
data = pd.read_table(location, skiprows=2, sep='\s+', names=names).assign(folder=folder, temp=temp, perturbation=perturbation_table[perturbation])
all_pmf_list.append(data)
data = pd.concat(all_pmf_list).dropna().reset_index()
data.to_feather("/Users/weilu/Research/data/pulling/oct31_pmf.feather")
data = pd.concat(all_evpb_list).dropna().reset_index()
data.to_feather("/Users/weilu/Research/data/pulling/oct31_evpb.feather")
In [114]:
all_pmf_list = []
all_evpb_list = []
for folder in folder_list:
for temp in temp_list:
for perturbation in perturbation_list:
# evpb
if perturbation == 0:
location = pre + "{}/1d_qw/t_all/force_0.0/evpb-{}.dat".format(folder, temp)
else:
location = pre + \
"{}/1d_qw/t_all/force_0.0/perturbation-{}-evpb-{}.dat".format(folder, perturbation, temp)
name_list = ["Lipid", "Go", "Mem", "Rg"]
names = ["bin", "q"] + name_list
data = pd.read_table(location, skiprows=1, sep='\s+', names=names).assign(folder=folder, temp=temp, perturbation=perturbation_table[perturbation])
all_evpb_list.append(data)
# pmf
if perturbation == 0:
location = pre + "{}/1d_qw/t_all/force_0.0/pmf-{}.dat".format(folder, temp)
else:
location = pre + \
"{}/1d_qw/t_all/force_0.0/perturbation-{}-pmf-{}.dat".format(folder, perturbation, temp)
name_list = ["f", "df", "e", "s"]
names = ["bin", "q"] + name_list
data = pd.read_table(location, skiprows=2, sep='\s+', names=names).assign(folder=folder, temp=temp, perturbation=perturbation_table[perturbation])
all_pmf_list.append(data)
data = pd.concat(all_pmf_list).dropna().reset_index()
data.to_feather("/Users/weilu/Research/data/pulling/oct31_pmf_qw.feather")
data = pd.concat(all_evpb_list).dropna().reset_index()
data.to_feather("/Users/weilu/Research/data/pulling/oct31_evpb_qw.feather")
In [77]:
pre = "/Users/weilu/Research/server/oct_2017/23oct/"
folder_list = [
'memb_3_rg_0.1_lipid_1_extended',
'memb_3_rg_0.1_lipid_1_topology'
]
all_data_list = []
temp_list = [450, 500, 550]
perturbation_list = [0, 1, 2, 3, 4]
for folder in folder_list:
for temp in temp_list:
for perturbation in perturbation_list:
if perturbation == 0:
location = pre + "{}/1d_dis/t_all/force_0.0/pmf-{}.dat".format(folder, temp)
else:
location = pre + \
"{}/1d_dis/t_all/force_0.0/perturbation-{}-pmf-{}.dat".format(folder, perturbation, temp)
# location = pre + "{}/1d_dis/t_all/force_0.0/pmf-{}.dat".format(folder, temp)
name_list = ["f", "df", "e", "s"]
names = ["bin", "x"] + name_list
data = pd.read_table(location, skiprows=2, sep='\s+', names=names).assign(folder=folder, temp=temp, perturbation=perturbation)
all_data_list.append(data)
data = pd.concat(all_data_list)
data = data.dropna().reset_index()
data.to_feather("/Users/weilu/Research/data/pulling/oct31_pmf.feather")
In [71]:
fig, axes = plt.subplots(1, 2, figsize=(8,6))
i = 0
for label, group in data.groupby('folder'):
# processed_data = group - group.mean()
# processed_data["x"] = data["x"]
group.plot('x', "f", ax=axes[i], label=label)
i = i + 1
In [86]:
pre = "/Users/weilu/Research/server/oct_2017/23oct/"
folder_list = [
'memb_3_rg_0.1_lipid_1_extended',
'memb_3_rg_0.1_lipid_1_topology'
]
all_data_list = []
for folder in folder_list:
location = pre + "{}/1d_qw/t_all/force_0.0/evpb-500.dat".format(folder)
name_list = ["Lipid", "Go", "Mem", "Rg"]
names = ["bin", "x"] + name_list
data = pd.read_table(location, skiprows=1, sep='\s+', names=names).assign(folder=folder)
all_data_list.append(data)
data = pd.concat(all_data_list)
data = data.dropna()
In [87]:
fig, axes = plt.subplots(1, 2, figsize=(8,6))
i = 0
for label, group in data.groupby('folder'):
# processed_data = group - group.mean()
# processed_data["x"] = data["x"]
for name in name_list:
group.plot('x', name, ax=axes[i], ylim=(-550,550), label=label)
i = i + 1
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plotcontour.py pmf-400.dat -xmax 1 -xmin 0 -ymin 0 -ymax 150"
In [9]:
location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_topology/2d_qw_dis/t_all/force_0.0/"
filename = location + "pmf-500.dat"
x = 1
y = 2
z = 3
xmin, xmax = -40, 10
ymin, ymax = 0, 1
zmin, zmax = 0, 30
xlabel, ylabel = "xlabel", "ylabel"
title = "title"
titlefontsize = 28
In [5]:
location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_topology/2d_qw_dis/t_all/force_0.0/"
arguments ={
filename : location + "pmf-500.dat",
x : 1,
y : 2,
z : 3,
xmin, xmax : 0, 1,
ymin, ymax : 0, 150,
zmin, zmax : 0, 30,
xlabel, ylabel : "xlabel", "ylabel",
title : "title",
titlefontsize : 28
}
In [10]:
def plot2d(**kargs):
data = np.loadtxt(filename)
data = data[~np.isnan(data).any(axis=1)] # remove rows with nan
data = data[~(data[:,z] > zmax)] # remove rows of data for z not in [zmin zmax]
data = data[~(data[:,z] < zmin)]
xi = np.linspace(min(data[:,x]), max(data[:,x]), 20)
yi = np.linspace(min(data[:,y]), max(data[:,y]), 20)
zi = griddata((data[:,x], data[:,y]), data[:,z], (xi[None,:], yi[:,None]), method='linear')
# plt.contour(xi, yi, zi, 50, linewidths=0.25,colors='k')
jet = cm = plt.get_cmap('jet')
print(jet)
# plt.contourf(xi, yi, zi, 20, cmap='rainbow')
plt.contourf(xi, yi, zi, 30, cmap='jet')
plt.xlim(xmin, xmax)
plt.ylim(ymin, ymax)
plt.clim(zmin, zmax)
plt.colorbar()
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title, y=1.02, fontsize = titlefontsize)
#plt.tight_layout()
#plt.axis('equal')
#plt.axes().set_aspect('equal')
#plt.axes().set_aspect('scaled')
# plt.savefig(args.outname, dpi=args.dpi, bbox_inches='tight')
plt.show()
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location = "/Users/weilu/Research/server/jan_2018/ctbp_another_freeEnergy_rg_0.3_lipid_0.6_mem_1_0/rg_0.3_lipid_0.6_mem_1_350-550/2d_z_qw/force_0.0/"
filename = location + "pmf-450.dat"
data = np.loadtxt(filename)
data = data[~np.isnan(data).any(axis=1)] # remove rows with nan
data = data[~(data[:,z] > zmax)] # remove rows of data for z not in [zmin zmax]
data = data[~(data[:,z] < zmin)]
xi = np.linspace(min(data[:,x]), max(data[:,x]), 20)
yi = np.linspace(min(data[:,y]), max(data[:,y]), 20)
zi = griddata((data[:,x], data[:,y]), data[:,z], (xi[None,:], yi[:,None]), method='linear')
# plt.contour(xi, yi, zi, 50, linewidths=0.25,colors='k')
jet = cm = plt.get_cmap('jet')
print(jet)
# plt.contourf(xi, yi, zi, 20, cmap='rainbow')
plt.figure()
plt.contourf(xi, yi, zi, 30, cmap='jet')
plt.xlim(xmin, xmax)
plt.clim(zmin, zmax)
plt.colorbar()
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title, y=1.02, fontsize = titlefontsize)
#plt.tight_layout()
#plt.axis('equal')
#plt.axes().set_aspect('equal')
#plt.axes().set_aspect('scaled')
# plt.savefig(args.outname, dpi=args.dpi, bbox_inches='tight')
plt.show()
In [104]:
location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_topology/2d_qw_dis/t_all/force_0.0/"
filename = location + "pmf-550.dat"
data = np.loadtxt(filename)
data = data[~np.isnan(data).any(axis=1)] # remove rows with nan
data = data[~(data[:,z] > zmax)] # remove rows of data for z not in [zmin zmax]
data = data[~(data[:,z] < zmin)]
xi = np.linspace(min(data[:,x]), max(data[:,x]), 20)
yi = np.linspace(min(data[:,y]), max(data[:,y]), 20)
zi = griddata((data[:,x], data[:,y]), data[:,z], (xi[None,:], yi[:,None]), method='linear')
# plt.contour(xi, yi, zi, 50, linewidths=0.25,colors='k')
jet = cm = plt.get_cmap('jet')
print(jet)
# plt.contourf(xi, yi, zi, 20, cmap='rainbow')
plt.figure()
plt.contourf(xi, yi, zi, 30, cmap='jet')
plt.xlim(xmin, xmax)
plt.clim(zmin, zmax)
plt.colorbar()
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title, y=1.02, fontsize = titlefontsize)
#plt.tight_layout()
#plt.axis('equal')
#plt.axes().set_aspect('equal')
#plt.axes().set_aspect('scaled')
# plt.savefig(args.outname, dpi=args.dpi, bbox_inches='tight')
plt.show()
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plot2d()
In [29]:
location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_topology/2d_qw_dis/t_all/force_0.0/"
filename = location + "pmf-500.dat"
data = np.loadtxt(filename)
data = data[~np.isnan(data).any(axis=1)] # remove rows with nan
data = data[~(data[:,z] > zmax)] # remove rows of data for z not in [zmin zmax]
data = data[~(data[:,z] < zmin)]
xi = np.linspace(min(data[:,x]), max(data[:,x]), 20)
yi = np.linspace(min(data[:,y]), max(data[:,y]), 20)
zi = griddata((data[:,x], data[:,y]), data[:,z], (xi[None,:], yi[:,None]), method='linear')
# plt.contour(xi, yi, zi, 50, linewidths=0.25,colors='k')
jet = cm = plt.get_cmap('jet')
print(jet)
# plt.contourf(xi, yi, zi, 20, cmap='rainbow')
plt.figure()
plt.contourf(xi, yi, zi, 30, cmap='jet')
plt.xlim(xmin, xmax)
ma
plt.clim(zmin, zmax)
plt.colorbar()
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title, y=1.02, fontsize = titlefontsize)
#plt.tight_layout()
#plt.axis('equal')
#plt.axes().set_aspect('equal')
#plt.axes().set_aspect('scaled')
# plt.savefig(args.outname, dpi=args.dpi, bbox_inches='tight')
plt.show()
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%matplotlib notebook
In [28]:
location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_extended/2d_qw_dis/t_all/force_0.0/"
filename = location + "pmf-500.dat"
data = np.loadtxt(filename)
data = data[~np.isnan(data).any(axis=1)] # remove rows with nan
data = data[~(data[:,z] > zmax)] # remove rows of data for z not in [zmin zmax]
data = data[~(data[:,z] < zmin)]
xi = np.linspace(min(data[:,x]), max(data[:,x]), 20)
yi = np.linspace(min(data[:,y]), max(data[:,y]), 20)
zi = griddata((data[:,x], data[:,y]), data[:,z], (xi[None,:], yi[:,None]), method='linear')
# plt.contour(xi, yi, zi, 50, linewidths=0.25,colors='k')
jet = cm = plt.get_cmap('jet')
print(jet)
# plt.contourf(xi, yi, zi, 20, cmap='rainbow')
plt.contourf(xi, yi, zi, 30, cmap='jet')
plt.xlim(xmin, xmax)
plt.ylim(ymin, ymax)
plt.clim(zmin, zmax)
plt.colorbar()
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title, y=1.02, fontsize = titlefontsize)
#plt.tight_layout()
#plt.axis('equal')
#plt.axes().set_aspect('equal')
#plt.axes().set_aspect('scaled')
# plt.savefig(args.outname, dpi=args.dpi, bbox_inches='tight')
plt.show()
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location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_extended/1d_dis/t_all/force_0.0"
file