import plotly
plotly.__version__

import matplotlib.pyplot as plt   # side-stepping mpl's backend
import plotly.plotly as py
import plotly.tools as tls
from plotly.graph_objs import *
%matplotlib inline
py.sign_in("IPython.Demo", "1fw3zw2o13")

fig1 = plt.figure()

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-2.0, 2.0, 10000) # The x-values
sigma = np.linspace(0.4, 1.0, 4) # Some different values of sigma

# Here we evaluate a Gaussians for each sigma
gaussians = [(2*np.pi*s**2)**-0.5 * np.exp(-0.5*x**2/s**2) for s in sigma]

ax = plt.axes()

for s,y in zip(sigma, gaussians):
    ax.plot(x, y, lw=1.25, label=r"$\sigma = %3.2f$"%s)

formula = r"$y(x)=\frac{1}{\sqrt{2\pi\sigma^2}}e^{-\frac{x^2}{2\sigma^2}}$"

ax.text(0.05, 0.80, formula, transform=ax.transAxes, fontsize=20)
ax.set_xlabel(r"$x$", fontsize=18)
ax.set_ylabel(r"$y(x)$", fontsize=18)
ax.legend()
plt.show()

py.iplot_mpl(fig1) 

from plotly.graph_objs import Data, Layout, Figure

help(Figure)

# Convert MPL figure to Plotly
my_fig = tls.mpl_to_plotly(fig1)

# Take a quick look at the Plotly representation of the MPL figure
print my_fig.to_string()

# Strip out the data from the Figure
my_data = my_fig.get_data()
my_data

py.iplot_mpl(fig1, strip_style = True) 

tls.embed('MattSundquist', '1559')

library(plotly)

p <- plotly(username="MattSundquist", key="c6393zudwx")

trace1 <- list(
  x = c(1, 2, 3, 4), 
  y = c(1, 4, 9, 16), 
  name = "$\alpha_{1c} = 352 \pm 11 \text{ km s}^{-1}$", 
  type = "scatter"
)
trace2 <- list(
  x = c(1, 2, 3, 4), 
  y = c(0.5, 2, 4.5, 8), 
  name = "$\beta_{1c} = 25 \pm 11 \text{ km s}^{-1}$", 
  type = "scatter"
)
data <- list(trace1, trace2)
layout <- list(
  xaxis = list(title = "$\sqrt{(n_\text{c}(t|{T_\text{early}}))}$"), 
  yaxis = list(title = "$d, r \text{ (solar radius)}$")
)

response <- p$plotly(data, kwargs=list(layout=layout, filename="latex", fileopt="overwrite"))
url <- response$url
filename <- response$filename

tls.embed('MattSundquist', '613')

zeta = [0.01 .02 0.05 0.1 .2 .5 1 ];
colors = ['r' 'g' 'b' 'c' 'm' 'y' 'k'];

w = logspace(-1, 1, 1000);

figure;
for i = 1:7
    a = w.^2 - 1;
    b = 2*w*zeta(i);
    gain = sqrt(1./(a.^2 + b.^2));
    loglog(w, gain, 'color', colors(i), 'linewidth', 2);
    hold on;
end

% Set the axis limits
axis([0.1 10 0.01 100]);

% title and labels
title('|G|(\omega) vs \omega');
xlabel('\omega');
ylabel('|G|(\omega)');

fig2plotly()

tls.embed('MATLAB-Demos', '4')

# CSS styling within IPython notebook
from IPython.core.display import HTML
import urllib2
def css_styling():
    url = 'https://raw.githubusercontent.com/plotly/python-user-guide/master/custom.css'
    styles = urllib2.urlopen(url).read()
    return HTML(styles)

css_styling()