In [1]:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import datetime
import os
# from small_script.myFunctions import *
%matplotlib inline
%load_ext autoreload
%autoreload 2
In [2]:
plt.rcParams['figure.figsize'] = [16.18033, 10]
dataset = {"old":("1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", "), 40),
"new":("1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", "), 80),
"test":(['1A2J', '1A3H', '1A5Y', '1A8Q', '1AGY', '1AKZ', '1AUZ', '1B1A', '1B31', '1B8X', '1BCO', '1BN6', '1BOH', '1BOI'], 80)}
# pdb_list, steps = dataset["old"]
def get_data(pre, pdb_list, simType="all_simulations"):
# to get last 20 frame of each run
_all = []
for p in pdb_list:
name = p.lower()[:4]
for i in range(30):
for ii in range(1):
location = pre + f"{simType}/{name}/simulation/{i}/{ii}/wham.dat"
try:
tmp = pd.read_csv(location).tail(50).reset_index()
tmp.columns = tmp.columns.str.strip()
_all.append(tmp.assign(Run=i, Name=name, Rerun=ii))
except Exception as e:
print(e)
data = pd.concat(_all)
data["Run"] = "Run" + data["Run"].astype(str)
return data
# pre = "/Users/weilu/Research/server/feb_2019/optimization_iter1/database/2gb1/"
# fileName = "movie.pdb"
def splitPDB(pre, fileName):
location = f"{pre}/{fileName}"
with open(location, "r") as f:
a = f.readlines()
i = 0
tmp = ""
for line in a:
tmp += line
# os.system(f"echo '{line}' >> {pre}frame{i}")
if line == "END\n":
with open(f"{pre}frame{i}.pdb", "w") as out:
out.write(tmp)
i += 1
tmp = ""
import subprocess
def getFromTerminal(CMD):
return subprocess.Popen(CMD,stdout=subprocess.PIPE,shell=True).communicate()[0].decode()
def getSize(p):
protein = p.lower()[:4]
pre = f"/Users/weilu/Research/server/feb_2019/iterative_optimization_test_set/all_simulations/{protein}/{protein}/ssweight"
a = getFromTerminal(f"wc {pre}")
# print(a)
n = int(a.split()[0])
return n
In [72]:
# data = pd.read_csv("/Users/weilu/Research/data/optimization/iter1_2_03-01.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/iter1_with_bias_98percent_03-04.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter1_combined_on_B_03-07.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter2_8_03-09.csv", index_col=0)
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_03-13.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter1_98_03-07.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter1_96_iterative_optimization_old_set_03-15.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/iter0_03-15.csv", index_col=0)
# data4 = pd.read_csv("/Users/weilu/Research/data/optimization/iter4_13_iterative_optimization_old_set_03-18.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/iter4_5_iterative_optimization_old_set_03-20.csv", index_col=0)
# data4 = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter1_96_03-06.csv", index_col=0)
# data4 = pd.read_csv("/Users/weilu/Research/data/optimization/withoutContact_03-03.csv", index_col=0)
# data5 = pd.read_csv("/Users/weilu/Research/data/optimization/iter4_22_iterative_optimization_old_set_03-19.csv", index_col=0)
data5 = pd.read_csv("/Users/weilu/Research/data/optimization/iter4_6_iterative_optimization_old_set_03-20.csv", index_col=0)
# data6 = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter3_10_03-12.csv", index_col=0)
data6 = pd.read_csv("/Users/weilu/Research/data/optimization/iter4_30_iterative_optimization_old_set_03-20.csv", index_col=0)
data7 = pd.read_csv("/Users/weilu/Research/data/optimization/iter5_30_iterative_optimization_old_set_03-22.csv", index_col=0)
# data8 = pd.read_csv("/Users/weilu/Research/data/optimization/iter6_30_iterative_optimization_old_set_03-25.csv", index_col=0)
data8 = pd.read_csv("/Users/weilu/Research/data/optimization/iter7_2_iterative_optimization_old_set_03-26.csv", index_col=0)
data9 = pd.read_csv("/Users/weilu/Research/data/optimization/iter7_compare_iterative_optimization_old_set_03-26.csv", index_col=0)
data10 = pd.read_csv("/Users/weilu/Research/data/optimization/iter7_normalized_iterative_optimization_old_set_03-27.csv", index_col=0)
data11 = pd.read_csv("/Users/weilu/Research/data/optimization/multiSeq_iterative_optimization_old_set_03-27.csv", index_col=0)
dataNoContact = pd.read_csv("/Users/weilu/Research/data/optimization/withoutContact_iterative_optimization_old_set_03-27.csv", index_col=0)
# data6 = pd.read_csv("/Users/weilu/Research/data/optimization/filtered_gamma_iter1_02-13.csv", index_col=0)
# data7 = pd.read_csv("/Users/weilu/Research/data/optimization/iter2_02-15.csv", index_col=0)
# d = pd.concat([data.assign(Scheme="single_memory"), data4.assign(Scheme="No contact")
# , data2.assign(Scheme="fragMemory"), data3.assign(Scheme="newContact"),
# data5.assign(Scheme="iter1")
# ])
d = pd.concat([
data.assign(Scheme="singleMemory"),
data3.assign(Scheme="iter0"),
# data2.assign(Scheme="new_iter3_10"),
# data4.assign(Scheme="new iter4"),
# data5.assign(Scheme="new iter4_2"),
data6.assign(Scheme="iter4_30_improved"),
# data7.assign(Scheme="iter5_30_improved"),
data9.assign(Scheme="iter7_compare"),
data8.assign(Scheme="iter7_2"),
data10.assign(Scheme="iter7_normalized"),
# data11.assign(Scheme="multiSeq"),
# dataNoContact.assign(Scheme="withoutContact"),
])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
# sns.boxplot("Qw", "Name", hue="Scheme", data=d)
Out[72]:
In [76]:
pre = "/Users/weilu/Research/server/april_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "noFrag"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[76]:
In [1]:
# data = pd.read_csv("/Users/weilu/Research/data/optimization/iter1_2_03-01.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/iter1_with_bias_98percent_03-04.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter1_combined_on_B_03-07.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter2_8_03-09.csv", index_col=0)
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_iterative_optimization_old_set_with_frag_03-28.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/iter7_2_iterative_optimization_old_set_with_frag_03-28.csv", index_col=0)
d = pd.concat([
data.assign(Scheme="original"),
data2.assign(Scheme="iter7"),
])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
# sns.boxplot("Qw", "Name", hue="Scheme", data=d)
In [74]:
pre = "/Users/weilu/Research/server/april_2019/"
folder = "iterative_optimization_old_set_with_frag"
pre = pre + folder + "/"
simulationType = "iter7_2"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[74]:
In [73]:
pre = "/Users/weilu/Research/server/april_2019/"
folder = "iterative_optimization_old_set_with_frag"
pre = pre + folder + "/"
simulationType = "single"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[73]:
In [68]:
pre = "/Users/weilu/Research/server/april_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "withoutContact"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[68]:
In [59]:
pre = "/Users/weilu/Research/server/april_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "multiSeq"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[59]:
In [58]:
pre = "/Users/weilu/Research/server/april_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter7_normalized"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[58]:
In [ ]:
# not good. with all new gamma.
In [57]:
pre = "/Users/weilu/Research/server/april_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter7_fast"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[57]:
In [54]:
pre = "/Users/weilu/Research/server/april_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter7_compare"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[54]:
In [51]:
pre = "/Users/weilu/Research/server/april_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter7_2"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[51]:
In [49]:
pre = "/Users/weilu/Research/server/march_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter7_30"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[49]:
In [43]:
pre = "/Users/weilu/Research/server/march_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter6_30"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[43]:
In [41]:
pre = "/Users/weilu/Research/server/march_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter5_30"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[41]:
In [38]:
pre = "/Users/weilu/Research/server/march_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter4_30"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[38]:
In [35]:
pre = "/Users/weilu/Research/server/march_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter4_6"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[35]:
In [34]:
pre = "/Users/weilu/Research/server/march_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter4_5"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[34]:
In [31]:
pre = "/Users/weilu/Research/server/march_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter4_22"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[31]:
In [28]:
pre = "/Users/weilu/Research/server/march_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "iter4_13"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[28]:
In [23]:
pre = "/Users/weilu/Research/server/march_2019/"
folder = "iterative_optimization_old_set"
pre = pre + folder + "/"
simulationType = "new_iter1_96"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{folder}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[23]:
In [24]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_old_set/"
simulationType = "iter0"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[24]:
In [16]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_old_set/"
simulationType = "single"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[16]:
In [17]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_old_set/"
simulationType = "new_iter3_10"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["old"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[17]:
In [12]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_new_temp_range/"
simulationType = "new_iter3_10"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[12]:
In [9]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_new_temp_range/"
simulationType = "new_iter2_10"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[9]:
In [24]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_new_temp_range/"
simulationType = "new_iter2_8"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[24]:
In [17]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_new_temp_range/"
simulationType = "new_iter1_combined_on_B"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[17]:
In [16]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_new_temp_range/"
simulationType = "new_iter1_98"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[16]:
In [8]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_new_temp_range/"
simulationType = "new_iter1_0"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[8]:
In [7]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_new_temp_range/"
simulationType = "new_iter1_96"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[7]:
In [6]:
pre = "/Users/weilu/Research/server/march_2019/iterative_optimization_new_temp_range/"
simulationType = "new_iter1_90"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[6]:
In [73]:
data = pd.read_csv("/Users/weilu/Research/library/test_protein_size_data.csv", index_col=0)
data.T
Out[73]:
In [88]:
Q = pd.read_csv("/Users/weilu/Research/server/feb_2019/optimization_iter1/database/1ctf_0/wham.dat")[" Qw"].values
In [91]:
Q[1999]
Out[91]:
In [92]:
[1,2] * 2
Out[92]:
In [ ]:
In [127]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "iter1_with_bias_98percent"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[127]:
In [126]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "iter1_with_bias_96percent"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[126]:
In [130]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "iter1_with_bias_2"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[130]:
In [122]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "iter1_with_bias"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
# data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/withoutContact_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[122]:
In [118]:
sns.boxplot("Name", "Qw", data=data)
Out[118]:
In [83]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_biased_sampling/"
simulationType = "bias_2"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[83]:
In [115]:
import matplotlib.pyplot as plt
import pylab as pl
plt.rcParams['figure.figsize'] = [16.18033, 2.4]
for title1, group in data.groupby("Name"):
group.hist("Rg", bins=100, sharey=True, sharex=True)
pl.suptitle(title1)
In [113]:
import matplotlib.pyplot as plt
import pylab as pl
plt.rcParams['figure.figsize'] = [16.18033, 2.4]
for title1, group in data.groupby("Name"):
group.hist("Qw", bins=100, sharey=True, sharex=True)
pl.suptitle(title1)
In [81]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "iter1_2"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list, steps = dataset["test"]
pdb_list, steps = dataset["new"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[81]:
In [15]:
# data = pd.read_csv("/Users/weilu/Research/data/optimization/iter1_2_03-01.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/iter1_with_bias_98percent_03-04.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter1_combined_on_B_03-07.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter2_8_03-09.csv", index_col=0)
data = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter2_10_03-09.csv", index_col=0)
# data = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter1_98_03-07.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/single_02-20.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/newContact_02-20.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter1_96_03-06.csv", index_col=0)
# data4 = pd.read_csv("/Users/weilu/Research/data/optimization/withoutContact_03-03.csv", index_col=0)
data5 = pd.read_csv("/Users/weilu/Research/data/optimization/newContactWithBurial_02-23.csv", index_col=0)
data6 = pd.read_csv("/Users/weilu/Research/data/optimization/new_iter3_10_03-12.csv", index_col=0)
# data6 = pd.read_csv("/Users/weilu/Research/data/optimization/filtered_gamma_iter1_02-13.csv", index_col=0)
# data7 = pd.read_csv("/Users/weilu/Research/data/optimization/iter2_02-15.csv", index_col=0)
# d = pd.concat([data.assign(Scheme="single_memory"), data4.assign(Scheme="No contact")
# , data2.assign(Scheme="fragMemory"), data3.assign(Scheme="newContact"),
# data5.assign(Scheme="iter1")
# ])
d = pd.concat([
# data.assign(Scheme="new_iter1_98"),
data2.assign(Scheme="singleMemory"),
# data3.assign(Scheme="newContact"),
data5.assign(Scheme="newContactWithBurial"),
data4.assign(Scheme="new iter1_96"),
data.assign(Scheme="new_iter2_10"),
# data.assign(Scheme="old_iter1_98"),
data6.assign(Scheme="new_iter3_10"),
# data7.assign(Scheme="iter2")
])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
Out[15]:
In [33]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_test_set/"
simulationType = "newContactWithBurial"
today = datetime.datetime.today().strftime('%m-%d')
pdb_list, steps = dataset["test"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[33]:
In [35]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_test_set/"
simulationType = "single"
today = datetime.datetime.today().strftime('%m-%d')
pdb_list, steps = dataset["test"]
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[35]:
In [37]:
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_02-27.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/newContactWithBurial_02-27.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/newContact_02-20.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/top20_02-20.csv", index_col=0)
data5 = pd.read_csv("/Users/weilu/Research/data/optimization/newContactWithBurial_02-23.csv", index_col=0)
data6 = pd.read_csv("/Users/weilu/Research/data/optimization/filtered_gamma_iter1_02-13.csv", index_col=0)
# data7 = pd.read_csv("/Users/weilu/Research/data/optimization/iter2_02pwd-15.csv", index_col=0)
# d = pd.concat([data.assign(Scheme="single_memory"), data4.assign(Scheme="No contact")
# , data2.assign(Scheme="fragMemory"), data3.assign(Scheme="newContact"),
# data5.assign(Scheme="iter1")
# ])
d = pd.concat([
# data.assign(Scheme="single_memory"),
data.assign(Scheme="singleMemory"),
# data3.assign(Scheme="newContact"),
# data4.assign(Scheme="Top20, New Frag"),
data2.assign(Scheme="newContactWithBurial"),
# data6.assign(Scheme="filtered_iter1"),
# data7.assign(Scheme="iter2")
])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
Out[37]:
In [17]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_old_set/"
simulationType = "newContactWithBurial"
today = datetime.datetime.today().strftime('%m-%d')
pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[17]:
In [27]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_old_set/"
simulationType = "single"
today = datetime.datetime.today().strftime('%m-%d')
pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
# pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[27]:
In [29]:
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_02-25.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/newContactWithBurial_02-25.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/newContact_02-20.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/top20_02-20.csv", index_col=0)
data5 = pd.read_csv("/Users/weilu/Research/data/optimization/newContactWithBurial_02-23.csv", index_col=0)
data6 = pd.read_csv("/Users/weilu/Research/data/optimization/filtered_gamma_iter1_02-13.csv", index_col=0)
# data7 = pd.read_csv("/Users/weilu/Research/data/optimization/iter2_02pwd-15.csv", index_col=0)
# d = pd.concat([data.assign(Scheme="single_memory"), data4.assign(Scheme="No contact")
# , data2.assign(Scheme="fragMemory"), data3.assign(Scheme="newContact"),
# data5.assign(Scheme="iter1")
# ])
d = pd.concat([
# data.assign(Scheme="single_memory"),
data.assign(Scheme="singleMemory"),
# data3.assign(Scheme="newContact"),
# data4.assign(Scheme="Top20, New Frag"),
data2.assign(Scheme="newContactWithBurial"),
# data6.assign(Scheme="filtered_iter1"),
# data7.assign(Scheme="iter2")
])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
Out[29]:
In [16]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "inverseBurial"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[16]:
In [14]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "newContactWithBurial"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[14]:
In [13]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "top1"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[13]:
In [12]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "top20"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[12]:
In [6]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "single"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[6]:
In [3]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_new_temp_range/"
simulationType = "newContact"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
sns.boxplot("Name", "Qw", data=data)
Out[3]:
In [15]:
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_memory_jan17.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/single_02-20.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/newContact_02-20.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/top20_02-20.csv", index_col=0)
data5 = pd.read_csv("/Users/weilu/Research/data/optimization/newContactWithBurial_02-23.csv", index_col=0)
data6 = pd.read_csv("/Users/weilu/Research/data/optimization/filtered_gamma_iter1_02-13.csv", index_col=0)
data7 = pd.read_csv("/Users/weilu/Research/data/optimization/iter2_02-15.csv", index_col=0)
# d = pd.concat([data.assign(Scheme="single_memory"), data4.assign(Scheme="No contact")
# , data2.assign(Scheme="fragMemory"), data3.assign(Scheme="newContact"),
# data5.assign(Scheme="iter1")
# ])
d = pd.concat([
# data.assign(Scheme="single_memory"),
data2.assign(Scheme="singleMemory"),
data3.assign(Scheme="newContact"),
# data4.assign(Scheme="Top20, New Frag"),
data5.assign(Scheme="newContactWithBurial"),
# data6.assign(Scheme="filtered_iter1"),
# data7.assign(Scheme="iter2")
])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
Out[15]:
In [39]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_3/"
simulationType = "iter2"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
In [37]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_2/"
simulationType = "filtered_gamma_iter1"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
In [35]:
pre = "/Users/weilu/Research/server/feb_2019/iterative_optimization_2/"
simulationType = "iter1"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
In [41]:
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_memory_jan17.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/all_simulations_01-31.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/newContact_singleFrag_02-01.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/FragOnly_01-23.csv", index_col=0)
data5 = pd.read_csv("/Users/weilu/Research/data/optimization/iter1_02-13.csv", index_col=0)
data6 = pd.read_csv("/Users/weilu/Research/data/optimization/filtered_gamma_iter1_02-13.csv", index_col=0)
data7 = pd.read_csv("/Users/weilu/Research/data/optimization/iter2_02-15.csv", index_col=0)
# d = pd.concat([data.assign(Scheme="single_memory"), data4.assign(Scheme="No contact")
# , data2.assign(Scheme="fragMemory"), data3.assign(Scheme="newContact"),
# data5.assign(Scheme="iter1")
# ])
d = pd.concat([data.assign(Scheme="single_memory"), data4.assign(Scheme="No contact")
, data3.assign(Scheme="newContact"),
data5.assign(Scheme="iter1"),
data6.assign(Scheme="filtered_iter1"),
# data7.assign(Scheme="iter2")
])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
Out[41]:
In [27]:
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_memory_jan17.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/all_simulations_01-31.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/newContact_singleFrag_02-01.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/FragOnly_01-23.csv", index_col=0)
data5 = pd.read_csv("/Users/weilu/Research/data/optimization/native_02-07.csv", index_col=0)
d = pd.concat([data.assign(Scheme="single_memory"), data4.assign(Scheme="No contact")
, data2.assign(Scheme="fragMemory"), data3.assign(Scheme="newContact"),
data5.assign(Scheme="iter1")
])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
Out[27]:
In [6]:
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_memory_jan17.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/all_simulations_01-31.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/newContact_singleFrag_02-01.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/FragOnly_01-23.csv", index_col=0)
d = pd.concat([data.assign(Scheme="single_memory"), data4.assign(Scheme="No contact")
, data2.assign(Scheme="fragMemory"), data3.assign(Scheme="newContact"),
])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
Out[6]:
In [8]:
pre = "/Users/weilu/Research/server/jan_2019/iterative_optimization_another_set/"
simulationType = "newContact_singleFrag"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
In [10]:
sns.boxplot("Name", "Qw", data=data)
Out[10]:
In [11]:
pre = "/Users/weilu/Research/server/jan_2019/iterative_optimization_another_set/"
simulationType = "top5"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
In [12]:
sns.boxplot("Name", "Qw", data=data)
Out[12]:
In [13]:
pre = "/Users/weilu/Research/server/jan_2019/iterative_optimization_another_set/"
simulationType = "top5_noeven"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
In [14]:
sns.boxplot("Name", "Qw", data=data)
Out[14]:
In [ ]:
In [5]:
pre = "/Users/weilu/Research/server/jan_2019/iterative_optimization_another_set_fragMemory/"
simulationType = "all_simulations"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
In [6]:
sns.boxplot("Name", "Qw", data=data)
Out[6]:
In [7]:
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_memory_jan17.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/all_simulations_01-31.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/newFrag_01-23.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/noFrag_single_memory_jan17.csv", index_col=0)
d = pd.concat([data.assign(Scheme="single_memory")
, data2.assign(Scheme="fragMemory"), data3.assign(Scheme="newFrag"),
data4.assign(Scheme="noFrag")])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
Out[7]:
In [24]:
data = pd.read_csv("/Users/weilu/Research/data/optimization/single_memory_jan17.csv", index_col=0)
data2 = pd.read_csv("/Users/weilu/Research/data/optimization/FragOnly_01-23.csv", index_col=0)
data3 = pd.read_csv("/Users/weilu/Research/data/optimization/newFrag_01-23.csv", index_col=0)
data4 = pd.read_csv("/Users/weilu/Research/data/optimization/noFrag_single_memory_jan17.csv", index_col=0)
d = pd.concat([data.assign(Scheme="single_memory")
, data2.assign(Scheme="FragOnly"), data3.assign(Scheme="newFrag"),
data4.assign(Scheme="noFrag")])
sns.boxplot("Name", "Qw", hue="Scheme", data=d)
Out[24]:
In [20]:
pre = "/Users/weilu/Research/server/jan_2019/iterative_optimization_another_set/"
simulationType = "FragOnly"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
In [21]:
sns.boxplot("Name", "Qw", data=data)
Out[21]:
In [ ]:
In [18]:
pre = "/Users/weilu/Research/server/jan_2019/iterative_optimization_another_set/"
simulationType = "newFrag"
today = datetime.datetime.today().strftime('%m-%d')
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType=simulationType)
data.reset_index(drop=True).to_csv(f"/Users/weilu/Research/data/optimization/{simulationType}_{today}.csv")
In [19]:
sns.boxplot("Name", "Qw", data=data)
Out[19]:
In [9]:
pre = "/Users/weilu/Research/server/jan_2019/iterative_optimization_another_set/"
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType="newContact_noFrag")
data.reset_index(drop=True).to_csv("/Users/weilu/Research/data/optimization/newContact_noFrag_single_memory_jan17.csv")
In [10]:
sns.boxplot("Name", "Qw", data=data)
Out[10]:
In [7]:
pre = "/Users/weilu/Research/server/jan_2019/iterative_optimization_another_set/"
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list, simType="noFrag")
data.reset_index(drop=True).to_csv("/Users/weilu/Research/data/optimization/noFrag_single_memory_jan17.csv")
In [8]:
sns.boxplot("Name", "Qw", data=data)
Out[8]:
In [3]:
pre = "/Users/weilu/Research/server/jan_2019/iterative_optimization_another_set/"
# pdb_list = "1R69, 1UTG, 3ICB, 256BA, 4CPV, 1CCR, 2MHR, 1MBA, 2FHA".split(", ")
pdb_list = "1FC2C, 1ENH, 2GB1, 2CRO, 1CTF, 4ICB".split(", ")
data = get_data(pre, pdb_list)
data.reset_index(drop=True).to_csv("/Users/weilu/Research/data/optimization/single_memory_jan17.csv")
In [6]:
sns.boxplot("Name", "Qw", data=data)
Out[6]:
In [ ]:
In [ ]:
# data = pd.read_csv("/Users/weilu/Research/data/optimization/single_memory_no_gamma.csv", index_col=0)
# data2 = pd.read_csv("/Users/weilu/Research/data/optimization/single_memory_old_gamma.csv", index_col=0)
# data3 = pd.read_csv("/Users/weilu/Research/data/optimization/single_memory_new_gamma.csv", index_col=0)
# d = pd.concat([data.assign(Scheme="no_gamma")
# , data3.assign(Scheme="new_gamma"), data2.assign(Scheme="old_gamma")])
# sns.boxplot("Name", "Qw", hue="Scheme", data=d)