#!/usr/bin/env python
# coding: utf-8

# # Creating Interactive Teaching Narratives Using Jupyter Notebooks
# 
# *Tony Hirst*
# 
# `@psychemedia`

# ## A Jupyter notebook is:

# - an interactive enviroMNent accessed via a browser

# - that can be served on your own computer or over the web

# - that can display rich text- like $\sqrt{3x-1}+(1+x)^2$ - inline, as well as `inline code` fragments

# - embed images, videos, audio players, etc

# ## Notebooks can be used as calculators

# In[1]:


#Do some sums


# ## Notebooks can be used to work with data

# - load data in from CSV or Excel files, web locations, or create directly

# In[24]:


get_ipython().run_line_magic('matplotlib', 'inline')
import matplotlib.pyplot as plt
import numpy as np


# In[25]:


#Define a variable
frequency=1

#Define a list of numbers
# in the range 0..1 with step size 0.2
timestamps=np.arange(0.0,1.0,0.02)

timestamps


# ## Notebooks can plot charts

# In[26]:


plt.plot(timestamps,np.sin(2*np.pi*timestamps*frequency));


# In[5]:


frequency=5


# ## Notebooks Can Be Used to Create Simple Interactives

# In[6]:


from ipywidgets import interact

def pltsin(f):
    plt.plot(timestamps,np.sin(2*np.pi*timestamps*f))


# In[7]:


interact(pltsin,f=(0,10,1));


# ## Notebooks can embed maps

# In[8]:


import folium
mymap = folium.Map(location=[52.0236, -0.7088], zoom_start=15,
                   width=600, height=300, tiles='Stamen Terrain')


# In[9]:


#Add two markers to the map
#folium.Marker([52.0239, -0.7072], popup='OU Library').add_to(mymap)
#folium.Marker([52.0242, -0.7112], popup='Jennie Lee Building').add_to(mymap)

mymap


# ## Notebooks Can Call Arbitrary Webservices

# In[10]:


import requests
postcode = 'MK7 6AA'

r=requests.get('https://api.postcodes.io/postcodes/{PC}'.format(PC=postcode)).json()['result']
lat=r['latitude']; lon=r['longitude']; pc=r['parliamentary_constituency']
mymap = folium.Map(location=[lat, lon], zoom_start=15, width=600, height=300)

#Create a popup message
popupstr = 'Location of {PC} in the {pc} constituency'.format(PC=postcode,pc=pc)

#Display a marker for the location
folium.Marker([lat, lon], popup=popupstr).add_to(mymap)
mymap


# ## And That's Just for Starters...

# - work with musical notation, create and embed sounds

# - use notebooks as a rich authoring environment

# - export to Microsoft Word, PDF or HTML

# - create slideshows like this...

# ## A Wide Range of Third Party Packages Have Notebook Support

# In[11]:


import MDAnalysis as mda
import nglview as nv
from nglview.datafiles import PDB, XTC
import warnings
warnings.filterwarnings("ignore")

u = mda.Universe(PDB, XTC)

protein = u.select_atoms('protein')
nv.show_mdanalysis(protein)


# ## Diagrams Using Graphviz `dot` language

# In[39]:


# http://www.graphviz.org/content/fsm
from graphviz import Digraph
f = Digraph('finite_state_machine')
f.attr(rankdir='LR', size='8,5')

f.attr('node', shape='doublecircle')
f.node('LR_0') ;f.node('LR_3');

f.attr('node', shape='circle')
f.edge('LR_0', 'LR_2', label='SS(B)'); f.edge('LR_0', 'LR_1', label='SS(S)')
f.edge('LR_1', 'LR_3', label='S($end)'); f.edge('LR_2', 'LR_2', label='SS(b)')

f


# ## Not Just Science and Engineering...

# For music, we need to set up some mess - though there are ways round this...

# In[40]:


from music21 import *

environment.UserSettings()['lilypondPath']='/usr/bin/lilypond'
environment.set('pdfPath', '/usr/bin/musescore')
environment.set('graphicsPath', '/usr/bin/musescore')
environment.set("musescoreDirectPNGPath", "/usr/bin/musescore")
environment.set("musicxmlPath", "/usr/bin/musescore")

from IPython.display import Image


# ### But then things get easier

# In[14]:


c = chord.Chord("C4 E4 G4")
c.isConsonant()
c.show('lily.png')
Image(filename=c.write('lily.png'))


# In[15]:


myBach = corpus.parse('bach/bwv57.8')
alto = myBach.parts['Alto']

alto.show('lily.png')
Image(filename=alto.write('lily.png'))


# ## Electrical Circuits

# In[16]:


import SchemDraw as schem
import SchemDraw.elements as e

d = schem.Drawing()
V1 = d.add(e.SOURCE_V, label='5V')
d.add(e.LINE, d='right', l=d.unit*.75)
S1 = d.add(e.SWITCH_SPDT2_CLOSE, d='up', anchor='b', rgtlabel='$t=0$')
d.add(e.LINE, d='right', xy=S1.c,  l=d.unit*.75)
d.add(e.RES, d='down', label='$100\Omega$', botlabel=['+','$v_o$','-'])
d.add(e.LINE, to=V1.start)
d.add(e.CAP, xy=S1.a, d='down', toy=V1.start, label='1$\mu$F')
d.add(e.DOT)
d.draw(showplot=False)


# ## Scientific Drawings - Asymptote

# In[17]:


drawingspec = '''
import math; import graph; import geometry;
size(12cm); xaxis("$x$"); yaxis("$y$");
real theta1={theta1}; real theta2={theta2};
real L1=0.45; real L2=0.48;
pair l1p = (L1*sin(theta1), L1*cos(theta1));
pair l2p = l1p + (L2*sin(theta1+theta2), L2*cos(theta1+theta2));
draw((0,0)--l1p--l2p); draw(l1p--l1p*1.5, dashed); dot(l2p); draw((0,0)--l2p, dashed); 
label("$J1(0,0)$", (0,0), NW); label("$J2(u,v)$", l1p, NW); label("$H(x,y)$", l2p, NE);
draw("$L1$",(0,0)-0.02*I*l1p--l1p-0.02*I*l1p, red, Arrows, Bars, PenMargins);
draw("$L2$", l1p-0.02*I*l2p--l2p-0.02*I*l2p, red, Arrows, Bars, PenMargins);
draw("$\\theta_1$", arc((0,1),(0,0),l1p,0.1), blue, PenMargins);
draw("$\\theta_2$", arc(l1p,0.1,degrees(l1p),degrees(l2p-l1p),CW), blue, PenMargins);
draw("$\\alpha$", arc((1,0),(0,0),l2p,0.2), blue, PenMargins);
'''


# In[18]:


import subprocess # to run asymptote
import shlex


# ## Our Drawings are Now Reproducible and Maintainable

# In[19]:


f=open('/tmp/pa10-firstjoint.asy', 'w')

theta1='-pi/2'  ;   theta2='pi/3'

f.write(drawingspec.format(theta1=theta1,theta2=theta2)); f.close()
subprocess.call(shlex.split('asy /tmp/pa10-firstjoint.asy -f png -o pa10-firstjoint.png'))
Image('pa10-firstjoint.png')


# ## Doing Symbolic Maths

# In[20]:


#Import sympy packages
import math
from sympy import *
from sympy import init_printing
init_printing()

b,c,B,C=symbols(['b','c','B','C'])


# In[21]:


#A simple example of the sine rule
exp=Eq(b/sin(B),c/sin(C))
exp


# ## `sympy` Symbolic Maths Packages Lets You Solve Equations

# In[49]:


#We can solve for b:
distance_b = solve(exp)[0][b]
Eq(b, distance_b)


# In[50]:


#Then we can substitute in values
Eq(Eq(b,distance_b), distance_b.subs({c:27404,B:math.radians(45),C:math.radians(60)}))


# ## To get started with notebooks

# - Temporary / disposable trial notebooks: `try.jupyter.org`

# - Personal notebooks: `notebooks.azure.com` (not OU account?)

# - Install on your own computer - via `Anaconda`, one of the many *Docker* containers, or the OU TM351 VM

# - Try out the OU / FutureLearn *Learn to Code for Analysis* MOOC

# - Join the lobbying for an OU hosted notebook server