MATPLOTLIB

1.importing library

-       matplotlib is preinstalled with pyzo


            import matplotlib.pyplot as plt


-       possible dependencies:

-       numpy - extension for arrays, matrices,...

-       libpng - loading and saving png files

-       dateutil - datetime handling

-       tk/pyqt - GUI frameworks

-       possible dependecies - cartography


-       tutorials

-       http://matplotlib.org/users/beginner.html




2. pyplot basics- linecharts / scatterplot example and basic commands


            basic example - linechart


import matplotlib.pyplot as plt


plt.plot([1,2,3,7])

plt.ylabel('some numbers')

plt.show()



pyplot.plot() - plots lines/markers to the axes


                        plt.plot([1, 2, 5, 8])



                        plt.plot([1, 2, 5, 8], [1,3,5,6])



                        plt.plot([1, 2], [4,9], [1,3], [7,9])



plt.plot([1, 2], [4,9], ‘r--’, [1,3, 6], [4, 6, 8], ‘mv’) # red dashed lines, magenta triangles



                        plt.plot([1, 2, 5, 8], [1,3,5,6], linestyle=’dashed’, color=’green’,
marker=’o’, linewidth=’5’)




pyplot.axis - setting the extent of the axis


       plt.plot([1, 2, 5, 8], [1,3,5,6])

plt.axis([0, 4, 4, 50])



pyplot.show - displays a figure


pyplot.setp - controlling properties


       lines = plt.plot([1, 2, 5, 8], [1,3,5,6])

plt.setp(lines, color='r')


pyplot.xlabel/pyplot.ylabel - name of the axis

pyplot.title - sets title

pyplot.suptitle - add a title to the Figure

pyplot.figtext - add text at an arbitrary location to the Figure

pyplot.text - put title on selected position

pyplot.grid - switch grid on and off


       import matplotlib.pyplot as plt


plt.xlabel('label for X', fontsize=15)

plt.ylabel('label for Y')

plt.title('the ultimate chart', color='green')

plt.suptitle('blabla')

plt.text(60, .025, r'a random text', style='italic')

plt.axis([40, 160, 0, 0.03])

plt.grid(True)

plt.show()





3. handling more figures


       import matplotlib.pyplot as plt


plt.figure(1)

plt.plot([1, 2, 5, 8], [1,3,5,6])


plt.figure(2)

plt.plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)


plt.show()





4. other types of plots


            plt.hist([0,2,1,2,6,7,4,8,9,5,4,1,3,2,3,2], bins=10)



            plt.pie([4,5,7,12])


plt.scatter([2,5,8],[4,5,6])


plt.bar([1, 2, 3, 4],[17, 15, 52, 15])


plt.bar([1,2,3,4,5], [20, 35, 30, 35, 27], 0.1, color='g')

plt.bar([1.1,2.1,3.1,4.1,5.1], [25, 32, 34, 20, 25], 0.1, color='r')


            …


            online collection of documented examples

http://matplotlib.org/api/pyplot_api.html



5. Loading external images:

-       using matplotlib.image


       # request image from url and load it with matplotlib

import matplotlib.pyplot as plt

import matplotlib.image as mpimg

import urllib.request


with urllib.request.urlopen("http://matplotlib.sourceforge.net/_static/logo2.png") as response:

img = plt.imread(response)

plt.imshow(img)






            tutorial http://matplotlib.org/users/image_tutorial.html


6. Example- choropleth map

loading external geojson:


       import matplotlib.pyplot as plt

import json


with open ('C:/pathto/countries.geojson', 'r', encoding='utf8') as countriesJson:

countries = json.load(countriesJson)



            putting shapes on matplotlib canvas:


              for country in countries['features']:

for shape in country['geometry']['coordinates']:

for coords in shape:


x = [i for i,j in coords]

y = [j for i,j in coords]


                                  plt.plot(x, y)


              plt.axis('scaled')

plt.grid(True)

plt.show()



defining colormap:

-       http://matplotlib.org/examples/color/colormaps_reference.html


       from matplotlib.pyplot import cm


              colors = plt.get_cmap('copper', 6)



            getting number from attribute:


              income = int(country['properties']['income_grp'][0])



            coloring polygons:

-       http://stackoverflow.com/questions/10550477/how-do-i-set-color-to-rectangle-in-matplotlib


              plt.fill(x,y, facecolor=colors(income), edgecolor='black', linewidth=0.4)



       event handling

-       https://jakevdp.github.io/blog/2012/12/06/minesweeper-in-matplotlib/

-       http://matplotlib.org/users/event_handling.html


-       setting ax object


              fig = plt.figure()

ax = fig.add_subplot(111)


-       global list of polygons with attributes.


              polygons = []


              # http://matplotlib.org/api/patches_api.html

              polygon = plt.Polygon(coords)

polygons.append({'shape': polygon, 'props': country['properties'], 'income': income})

ax.add_patch(polygon)

polygon.set_facecolor(colors(income))



-       setting event listener


       fig.canvas.mpl_connect('motion_notify_event', on_move)


-       define on_move function


              def on_move(event):

for pol in polygons:

income = int(pol['props']['income_grp'][0])

pol['shape'].set_facecolor(colors(income))

for pol in polygons:

if pol['shape'].contains_point((event.x, event.y)):

pol['shape'].set_facecolor('black')

fig.canvas.draw()


            labels

-       http://matplotlib.org/api/text_api.html


-       creating text object


              text = ax.text(0,0, '', color='r')


-       redefining on_move function


              def on_move(event):

text.set_x(event.x - 300)

text.set_y(event.y - 250)

text.set_text('')


for pol in polygons:

income = int(pol['props']['income_grp'][0])

pol['shape'].set_facecolor(colors(income))

for pol in polygons:

if pol['shape'].contains_point((event.x, event.y)):

pol['shape'].set_facecolor('black')

text.set_text(pol['props']['name'])

fig.canvas.draw()





       import matplotlib.pyplot as plt

from matplotlib.pyplot import cm

import json


path = 'C:/Users/mu/Desktop/phd/vyuka/Programovani/matplot geojson/'


colors = plt.get_cmap('copper', 6)

polygons = []


def on_move(event):

text.set_x(event.x - 300)

text.set_y(event.y - 250)

text.set_text('')


for pol in polygons:

income = int(pol['props']['income_grp'][0])

pol['shape'].set_facecolor(colors(income))


for pol in polygons:

if pol['shape'].contains_point((event.x, event.y)):

pol['shape'].set_facecolor('black')

text.set_text(pol['props']['name'])

fig.canvas.draw()


fig = plt.figure()

ax = fig.add_subplot(111)

text = ax.text(0,0, '', color='r')


with open (path + 'countries.geojson', 'r', encoding='utf8') as countriesJson:

countries = json.load(countriesJson)


for country in countries['features']:

income = int(country['properties']['income_grp'][0])

for shape in country['geometry']['coordinates']:

for coords in shape:


x = [i for i,j in coords]

y = [j for i,j in coords]

polygon = plt.Polygon(coords)

polygons.append({'shape': polygon, 'props': country['properties'], 'income': income})

ax.add_patch(polygon)

polygon.set_facecolor(colors(income))

fig.canvas.mpl_connect('motion_notify_event', on_move)

plt.axis('scaled')

plt.grid(True)

plt.show()











7. Extension - basemap

            pip install basemap --allow-external basemap --allow-unverified basemap

            (SET GEOS_DIR= “C:\OSGeo4W64\lib”)


       from mpl_toolkits.basemap import Basemap
       import matplotlib.pyplot as plt
       # setup Lambert Conformal basemap.
       # set resolution=None to skip processing of boundary datasets.
       m = Basemap(width=12000000,height=9000000,projection='lcc',
                     resolution=None,lat_1=45.,lat_2=55,lat_0=50,lon_0=-107.)
       m.shadedrelief()
       plt.show()