kumanna

import numpy as np
import matplotlib.pyplot as plt

def sum_harmonics(n, t):
    result = np.zeros(t.shape)
    for i in range(n):
        result += 4 / (2 * i + 1) / np.pi * np.sin(t * (2 * i + 1))
    return result

t = np.arange(0, 2 * np.pi, 0.0001)

kumanna

import numpy as np
import matplotlib.pyplot as plt

t = np.arange(0, 1, 0.001)
x = t
plt.plot(t, x);plt.show()

# We now convolve x with itself
# and dt is t[2] - t[1]
h = t[1] - t[0]

kumanna

import numpy as np
import itertools

VECSIZE = 6
M = np.eye(6)
for r in range(6):
    print(f"FOR r = {r}:")
    for pair in [i for i in itertools.product(range(1, VECSIZE + 1), range(1, VECSIZE + 1)) if i[0] != r and i[1] != r and i[0] < i[1]]:
        print(pair)
        e1 = np.zeros(VECSIZE, dtype='int')

kumanna

myenv

kumanna

import numpy as np
import sys

def waterfill(alpha_vals, P):
    alpha_vals = np.array(alpha_vals)
    n = len(alpha_vals)
    allocation_done = False
    allocation = np.zeros(len(alpha_vals))
    while not allocation_done:
        nu_val = 1 / (P + sum(1 / alpha_vals[:n])) * n

kumanna

import numpy as np
import matplotlib.pyplot as plt

NFFT = 1024
BETA2 = -25509e-30
FS = 500e9
L = 1000000

# We have NFFT samples. Let's target a sampling rate of 500
# Gsamp/s.

kumanna

.ipynb_checkpoints/

kumanna

import numpy as np

# Generate random BPSK symbols
SYMBOLS = 1024
qpsk_symbols = (np.sign(np.random.rand(SYMBOLS) - 0.5) + 1j * np.sign(np.random.rand(SYMBOLS) - 0.5)) / np.sqrt(2)

h = np.array([1, 0.4 + 0.3j, 0.2 - 0.1j])
NCP = 4
NFFT = 64

kumanna

class Test {
    public static void main(String args[]) {
	double d = 314.159265;
	System.out.println((byte)d);
	int i = (int) d;
	System.out.println(i);
	System.out.println((byte) (i & 0xff));
	System.out.println(i >> 2);
	// How I would do it:
	int di = (int) d;

kumanna

from bottle import route, run, request, app, redirect


import beaker.middleware

session_opts = {
        'session.type': 'file',
        'session.data_dir': './session/',
        'session.auto': True,
    }