Bubble charts encode data in the area of circles. Although less perceptually-accurate than bar charts, they can pack hundreds of values into a small space. This implementation is an improvement on Static bubble chart adding mouse tooltip and cluster attributes. The data shows the Flare class hierarchy.
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#!/usr/bin/env python | |
import numpy as np | |
# Specify length of signal | |
N = 512; | |
# Generate time domain signal | |
x = np.random.rand(N).astype('complex') | |
# Evaluate signal power in the time domain |
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m = np.matrix('5 2; -6 4; 1 1') | |
s = np.matrix('7; 9; 4') | |
np.linalg.inv(m.H * m) * m.H*s |
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import numpy as np | |
N = 20 | |
Nfft = 64 | |
#hn = np.random.rand(N) | |
hn = np.ones(N) | |
hnr = hn*np.arange(N) | |
Tg = np.real(np.fft.fft(hnr, Nfft) / np.fft.fft(hn, Nfft)) |
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#!/usr/bin/env python | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import pdb | |
# zoneplte | |
W = 96 | |
H = 96 |
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#!/usr/bin/env python | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import pdb | |
def lms(u, d, M, step, leak=0, initCoeffs=None, N=None, returnCoeffs=False): | |
if N is None: | |
N = len(u)-M+1 |
In line: define
in block:
Block equations:
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#!/usr/bin/env python | |
import numpy as np | |
import matplotlib.pyplot as plt | |
C = 1 | |
for N in range(20,300,70): | |
tit = 'N = ' + str(N) | |
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function [C r] = BlahutArimoto(p) | |
disp('BlahutArimoto') | |
% Capacity of discrete memoryless channel | |
% Blahut-Arimoto algorithm | |
% Input | |
% p: m x n matrix | |
% p is the transition matrix for a channel with m inputs and n outputs |
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#include <iostream> | |
using namespace std; | |
int main() | |
{ | |
int arr[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9}; | |
for(auto i : arr){ | |
cout << arr[i] <<endl; | |
} | |
return 0; |
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