arrayoperations

---
title: "pythonandR array operations"
author: "Theophano Mitsa"
date: "August 1, 2019"
output: html_document
---

```{r setup, include=FALSE}
  library(reticulate)
use_python("C:/Users/Theo/Anaconda3/python.exe")
knitr::opts_chunk$set(echo = TRUE)
```

## R Markdown

Discover the Python that will be used
```{r}
py_discover_config()
```


1-D Vectors and type in R

```{r }

a1<-c(1,3,4)
a1
typeof(a1)
```


```{python}
import numpy as np
a=np.array([1,3,4])
print(type(a))
```
A zero vector and array in R
```{r}
a0<-vector("numeric",7)
a0
a00<-array(0,dim=c(2,3))
a00
```
A zero array in Python
```{python}
import numpy as np
a=np.zeros((2,3))
print(a)
```
A sequence in R
```{r}
s=seq(1,10,2)
s
s1<-1:5
names(s1)<-c("cat","frog","dog","bird","ant")
s1
```

A sequence in Python
```{python}
import numpy as np
s=np.arange(1,10,2)
print(s)
s2=np.linspace(0,100,20)
print(s2)
```
Accesing an array in R
```{r}
#Note array indices in R start at 1
a<-c(5,4,2,2,5)
a[1]

```
Accesing an array in Python
```{python}
#NOTE HERE INDICES START AT 0
a=[23,34,49,12,11]
print(type(a))
print(a[0])
import numpy as np
b=np.array([12,23,19,34])
print(b[0])
```
2-D array and matrix creation in r
NOTE: THERE IS NO DIFFERENCE BETWEEN A 2-D ARRAY AND MATRIX IN R

```{r}
set.seed(3)
arr4<-array(c(1,2,4,9,10,3), dim=c(2,3))
arr4
arr1<-array(rnorm(6,12,3),dim=c(2,3))
mat11<-matrix(c(2,9,5,3,9,10,1,4,10),nrow=3)
dimnames(arr1)=list(c("dep1","dep2"),c("Tom","Jim","Sam"))
arr1

set.seed(3)
mat1<-matrix(rnorm(6,12,3), nrow=2)
dimnames(mat1)=list(c("dep1","dep2"),c("Tom","Jim","Sam"))
mat1
identical(arr1,mat1)

```


Now let's try 2-D arrays in Python
```{python}
import numpy as np

b=np.array([(3,2,1),(1,3,4)])
print(b)
```
Reshape a matrix in R
```{r}
library(pracma)
mat11<-matrix(c(2,9,5,3,9,10),nrow=3)
print(mat11)
mat2<-Reshape(mat11,2,3)
print(mat2)
```

Reshaping-copying-creating a view of an array in Python
```{python}
import numpy as np
x=np.arange(1,5)
print(x)
a=np.array([(10,20,30),(5,6,7)])
g=a.reshape(3,-1)
print(g)
#Create a copy
xx=x
xx is x
#Create a view
xv=x.view()
xv is x
```

Mathematical functions with arrays and matrices in R
```{r}

am=matrix(c(1,9,16,25),nrow=2)
ams=sqrt(am)
print(am[,1])
print(ams)
l=sum(am)
print(l)
mm=rowMeans(am)
print(mm)
msa=rowSums(am)
mc=colMeans(am)
mcs=colSums(am)
```


Mathematical functions with arrays in Python
```{python}
import numpy as np
a=np.array([(10,20,30),(5,6,7)])
c=np.sqrt(a)
s=a.sum()
max=a.max()
print(s)
print(max)
k=a.argmax()
sr=a.sum(axis=0)
mr=a.mean(axis=0)
print(a[...,0])
```

Matrix algebra in R
```{r}
mat1=matrix(c(3,2,1,1,3,4,10,30,20),nrow=3)
MT=t(mat1)
MI=solve(mat1)
#DOT PRODUCT
PR=mat1%*%MI
print(PR)
# Element by element multipl
C=mat1*MT
#Eigen values and eigenvectors
y=eigen(mat1)
#eigen values
print(y$val)

```
Matrix algebra in Python, which is implemented using numpy arrays
```{python}

import numpy as np

b=np.array([(3,2,1),(1,3,4),(10,30,20)])
c=b.T
d=np.linalg.inv(b)
print(c)
print(d)
e=b.dot(d)
print(e)

```


Sample in R
```{r}
set.seed(5)
sample(1:30, 6, replace=TRUE)
```
Sample in Python
```{python}
import numpy as np
import random
ar0=np.arange(1,10,1)
ar0list=ar0.tolist()
#WITH REPLACEMENT
random.seed(3)
print ("choosing 7 random items from a sequence with replacement ",random.choices(ar0list,k=7))
#WITHOUT REPLACEMENT
random.seed(2)
print ("choosing 7 random items from a sequence without replacement ",random.sample(ar0list,k=7))


```