#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 21 14:29:57 2023

@author: richardson
"""

import numpy as np

a = [1,2,7,-2,2,3,0,0,1]
na = np.array(a) # makes the list into numpy array
aM = na.reshape(3,3)# makes 3x3 array (i.e. matrix)

# print(aM)
# print(aM.T) # transpose
# print(2*aM+3) # does 2x+3 to each element of the array
# print(aM*aM) # multiplies entry by entry - not matrix mult
# print(np.dot(aM,aM)) # actual matrix mult
# print(np.dot(na,na)) # dot product of vectors
# print(np.trace(aM))

from numpy import linalg as LA
# print(LA.det(aM))
# print(LA.inv(aM)) # inverse
# print(LA.eigvals(aM))
# print((3+4j)*(2-1j)) # python uses eg 1j for i, 2j for 2i, etc.

import scipy
from scipy import linalg as LA2

# print(np.exp(aM)) # does e^x to all entries of the matrix
# print(LA.exp(aM)) no matrix exp in linalg inside numpy
# print(LA2.expm(aM)) # matrix exponential

# other scipy stuff

from scipy import integrate as IN
def ff(x):
    return np.exp(-x*x)
# print(ff(-1))
# print(ff(0))
# print(ff(1))
# print(ff(2))
# print(IN.quad(ff,0,4)) # tuple
# # first entry is the approx value of the integral
# # second entry is the abs error estimate in the value.
# print(IN.quad(ff,0,4)[0]) 
# print(IN.quad(ff,0,np.inf))
# print(np.sqrt(np.pi)/2)



####
# pandas is a statistical data package
# does most things R can do


import pandas as pd
import numpy as np

WS = pd.read_csv('sampleData.csv', header=None)
bubba = np.array(WS) # makes data into np array
bubba2 = WS.values.tolist() # makes it into a list
print(bubba)
print(bubba2)

newData = np.reshape(bubba,(4,6))
df = pd.DataFrame(newData)
filenm = "other.xlsx"
df.to_excel(excel_writer = filenm,sheet_name="Data",header=None,index=None)
df.to_csv("other.csv",header=None,index=None)