Solution :
You can use the following definition of euclidean_distance(a,b)
def euclidean_distance(a,b):
return np.sqrt(sum((e1-e2)**2 for e1, e2 in zip(a,b)))
Here sum will sum up the square values (e1-e2)2 and zip will return an iterator of tuples where the first item in each passed iterator is paired together.
Code :
import numpy as np
def euclidean_distance(a,b):
return np.sqrt(sum((e1-e2)**2 for e1, e2 in zip(a,b)))
A=np.array(range(100))
B=np.array(range(1,101))
print(euclidean_distance(A,B))
Code demo for reference :
3 Compute Euclidean distance using Numpy Arrays • The Euclidean distance d is given by the...
I'm being asked to compute the probablity density at
(0,0) using the above KDE function. i finished the previous related
part. Not entirely sure of the syntax needed to enter the equation
using NumPy.
Code for previous related part for reference:
Exercise 3 Based on the KDE function: Compute the probablity density at [e,e], i.e., f((0, 0)). This should return a scalar value. (2 points) : def compute (data, h): ##CODE HERE## return x i We turn our attention to...
In Python import numpy as np Given the array a = np.array([[1, 2, 3], [10, 20, 30], [100, 200, 300]]), compute and print the sums over all rows (should give [6, 60, 600]) the sums over all columns (the sum of he first column is 111) the maximum of the array the maxima over all rows the mean of the sub-array formed by omitting the first row and column the products over the first two columns (hint: look for an...
How to rewrite the following functions using only numpy array operations (universal functions, aggregations, boolean indexing) without using loops def mean_squared_error (v , p ): n = len ( v [0]) result = 0 for i in range ( n ): result += ( v [0][ i ] - p [0])**2 + ( v [1][ i ] - p [1])**2 result = result / n return result I tried doing it like this but nothing printed out def mean_squared_error2 (v,...
I need to create the "nnclassifier using the euclidean distance formula to find nearest neighbor. I am using the inis dataset from seabom. I have loaded the data and split the database into values and species. I have created a function to find the nearest neighbor by also calculating the euclidean distance and appending them to a distance list. I am able to see the positions of the nearest neighbors. Smart numpy as Import pandas as pd Import seaborn as...
D Question 12 1.5 pts Check the true statements about NumPy arrays: O A single instantiated NumPy array can store multiple types (e.g., ints and strings) in its individual element positions. A NumPy array object can be instantiated using multiple types (e.g., ints and strings) in the list passed to its constructor O Memory freeing will require a double-nested loop. The number of bits used to store a particular NumPy array object is fixed. O The numpy.append(my.array, new_list) operation mutates...
Recreate the one hundred element arrays of sin and cos you
created in Exercise 3.10. Print these arrays out to a file in the
form of a table. The first line of the table should contain the first
element of both arrays, the second line the second element, an so
on. Keep the file as we will use it later.
Exercise 3.10:
My solution to 3.10:
import math
from numpy import zeros
array1 = zeros(100, float)
for x in range(100):...
Python, given a code in class i just need help with the third
bullet point ; using a and n (defined in the second picture of
python code) find the first digit for k! for k =1,...,n. you dont
have to type in all this code just help me write the code in the
first picture where it says: def benford(a):
b = [0 for d in range(1,10)]
#Do everthything in here
return b
2.2 Generating data In this assignment...
python
1
import matplotlib.pyplot as plt
2
import numpy as np
3
4
abscissa = np.arange(20)
5
plt.gca().set_prop_cycle(
’
color
’
, [
’
red
’
,
’
green
’
,
’
blue
’
,
’
black
’
])
6
7
class MyLine:
8
9
def __init__(self,
*
args,
**
options):
10
#TO DO: IMPLEMENT FUNCTION
11
pass
12
13
def draw(self):
14
plt.plot(abscissa,self.line(abscissa))
15
16
def get_line(self):
17
return "y = {0:.2f}x + {1:.2f}".format(self.slope,
self.intercept)
18
19
def __str__(self):...
Perform the following program and present flowchart Using Arduino create a program that averages two arrays of N elements where N is a whole number. A temperature control process has two temperature sensors A and B. From each sensor N samples are taken and stored in a different array. You need to average the values of the two sensors in another array and print it on the screen. The voltage range of the sensors ranges from 0 to 5 Volts...
solve it in c+*
Part II: Dynamic Arrays and Pointer Arithmetic Q5: Implement a subset function for a dynamic array which returns a new dynamic array that is a subset of the original. (15pt) input parameters: array - (the array and any related parameters) start - index of the first element end - index of the last element This function returns a new dynamic array containing the elements from the start thru the end indices of the original array. All...