%pylab inline
import matplotlib.pyplot as plt # side-stepping mpl backend
import matplotlib.gridspec as gridspec # subplots
import numpy as np

from matplotlylib import fig_to_plotly 
username = 'IPython.Demo'
api_key = '1fw3zw2o13'

fig1 = plt.figure()

x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)

y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)

plt.subplot(2, 1, 1)
plt.plot(x1, y1, 'yo-')
plt.title('A tale of 2 subplots')
plt.ylabel('Damped oscillation')

plt.subplot(2, 1, 2)
plt.plot(x2, y2, 'r.-')
plt.xlabel('time (s)')
plt.ylabel('Undamped')

plt.show()

fig_to_plotly(fig1, username, api_key, notebook= True)

fig2 = plt.figure()

N = 50
x = np.random.rand(N)
y = np.random.rand(N)
area = np.pi * (15 * np.random.rand(N))**2 # 0 to 15 point radiuses

plt.scatter(x, y, s=area, alpha=0.5)

fig_to_plotly(fig2, username, api_key, notebook= True)

fig3 = plt.figure()

font = {'family' : 'serif',
        'color'  : 'darkred',
        'weight' : 'normal',
        'size'   : 16,
        }

x = np.linspace(0.0, 5.0, 100)
y = np.cos(2 * np.pi * x) * np.exp(-x)

plt.plot(x, y, 'k')
plt.title('Damped exponential decay', fontdict=font)
plt.text(2, 0.65, r'$\cos(2 \pi t) \exp(-t)$', fontdict=font)
plt.xlabel('time (s)', fontdict=font)
plt.ylabel('voltage (mV)', fontdict=font)

# Tweak spacing to prevent clipping of ylabel
plt.subplots_adjust(left=0.15)

fig_to_plotly(fig3, username, api_key, notebook= True)

x = linspace(0, 5, 10)
y = x ** 2

fig4 = plt.figure()

subplot(1,2,1)
plot(x, y, 'r--')
subplot(1,2,2)
plot(y, x, 'g*-');

fig_to_plotly(fig4, username, api_key, notebook= True)

fig5 = plt.figure()

npts = 5000
xs = 2*rand(npts)-1
ys = 2*rand(npts)-1
r = xs**2+ys**2
ninside = (r<1).sum()
figsize(6,6) # make the figure square
title("Approximation to pi = %f" % (4*ninside/float(npts)))
plot(xs[r<1],ys[r<1],'b.')
plot(xs[r>1],ys[r>1],'r.')
figsize(8,6) # change the figsize back to 4x3 for the rest of the notebook

fig_to_plotly(fig5, username, api_key, notebook= True)

fig6 = plt.figure()

from scipy.fftpack import fft,fftfreq

npts = 4000
nplot = npts/10
t = linspace(0,120,npts)
def acc(t): return 10*sin(2*pi*2.0*t) + 5*sin(2*pi*8.0*t) + 2*rand(npts)

signal = acc(t)
FFT = abs(fft(signal))
freqs = fftfreq(npts, t[1]-t[0])

subplot(211)
plot(t[:nplot], signal[:nplot])
subplot(212)
plot(freqs,20*log10(FFT),',')

fig_to_plotly(fig6, username, api_key, notebook = True)

import scipy as sp
from numpy.fft import *

L = 20
n = 128
x = linspace(-L/2., L/2., n, endpoint=False)

fig7 = plt.figure()

u = exp(-x**2)
plot(x,u)

fig_to_plotly(fig7, username, api_key, notebook = True)

from matplotlib.colors import hsv_to_rgb
rcdef = plt.rcParams.copy()

def g(x):
    return (1.0-1/(1+x**2))**0.2

fig8 = plt.figure()

plt.rcParams.update(rcdef)# reset plt.rcParams to default
x=np.linspace(0,10, 1000)
y=g(x)
f=lambda z: (1.0-1.0/(1+z**2))**0.5
h=lambda z: (1.0-1.0/(1+z**2))**0.4
plt.plot(x,y)
plt.plot(x, f(x), 'r')
plt.plot(x, h(x), 'g')

fig_to_plotly(fig8, username, api_key, notebook = True)

fig9 = plt.figure()

X=np.linspace(0,8,800)
Y=X-np.floor(X)
plt.rcParams['figure.figsize'] = 5, 3 
plt.title('The graph of fract(x)')
plt.plot(X,Y,'r')

fig_to_plotly(fig9, username, api_key, notebook = True)