adiamb

###PYTHON#############
#Purpose : jsontocsv
#Author : Aditya Ambati 
#date : May 17 2017
#update : version 1
#####import libraries
import json
import sys
import pandas as pd
def json_to_csv(path, outfile):

adiamb

import numpy as np
import random
len(np.random.rand(10000))
=np.random.rand(10000)
def quicksort(array):
	less =[]
	equal =[]
	greater =[]
	if len(array) > 1:
		pivot = np.median(array)

adiamb

###PYTHON#############
#Purpose : use sequential keras feed forward network to predict DQ0602 binding 
#Author : Aditya Ambati 
#date : june2 2017
#update : version 1
#####import libraries
import pandas as pd
import numpy as np
import numpy

adiamb

###PYTHON#############
#Purpose : Analyze frameshifts in the MS-tryspin/chemotrypsin digests
#Author : Aditya Ambati 
#date : June7 2017
#update : version 1
#####import libraries
from itertools import chain
import pandas as pd
import numpy as np
%matplotlib

adiamb

###PYTHON#############
#Purpose : train a neural network to classify CIFAR 10 images
#Author : Aditya Ambati 
#date : June 10 2017
#update : version 1
#####import libraries
import pandas as pd
import numpy as np
import re
import numpy

adiamb

import numpy as np
import pandas as pd
from sklearn.manifold import TSNE
%matplotlib
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
csf = pd.read_csv('/Users/adityaambati/Downloads/CSF_FINAL_Jan18.csv', header=0)

csfvars=csf.iloc[:, 11:] ## remove clinical data 
Xtr=np.zeros((len(csfvars), 616))

adiamb

###PYTHON#############
#Purpose : Build a DB of mutations found in the MS-tryspin/chemotrypsin digests
#Author : Aditya Ambati 
#date : May 26 2017
#update : version 1
#####import libraries
from itertools import chain
import pandas as pd
import numpy as np
%matplotlib

adiamb

###PYTHON#############
#Purpose : Build fasta files with point mutations for NS1, PB1, PA & other influenza proteins excepting NA, HA, M1 & PB2 (already done !)
#Author : Aditya Ambati 
#date : June 12 2017
#update : version 1
#####import libraries
from itertools import chain
import pandas as pd
import numpy as np
%matplotlib

adiamb

###PYTHON#############
#Purpose : Build a DB of mutations found in the MS-tryspin/chemotrypsin digests 1st pass
#Author : Aditya Ambati 
#date : june13 2017
#update : version 1
#####import libraries
from itertools import chain
import pandas as pd
import numpy as np
%matplotlib

adiamb

import numpy as np
import pandas as pd
from sklearn.manifold import TSNE
%matplotlib
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from keras.models import Sequential
from keras.layers.core import Dense, Activation, Dropout
from keras.models import Sequential, load_model
from keras.layers import Dense, Dropout, BatchNormalization, Activation