In [12]:

    

import altair as alt
from bs4 import BeautifulSoup
from vega_datasets import data
import gpdvega
import geopandas
import json
import shapely
import re
from matplotlib import pyplot as plt
%matplotlib inline


    

In [85]:

    

portraitRaw = open('../portrait.xml').read()
portraitSoup = BeautifulSoup(portraitRaw)
geos = portraitSoup.find_all('geo')


    

In [86]:

    

geotext = [item.text for item in geos]


    

In [87]:

    

lineNos = [int(item.parent.parent.find_previous('lb').attrs['n']) for item in geos]


    

In [88]:

    

points = [shapely.geometry.point.Point([float(x) for x in pt.strip().split()[-1::-1]]) for pt in geotext]


    

In [89]:

    

def clean(text): 
    return re.sub('\s+', ' ', text.strip().replace('\n', ' '))


    

In [90]:

    

names = [clean(item.parent.parent.find('placename').text.strip()) for item in geos]


    

In [91]:

    

gdf = geopandas.GeoDataFrame({'name': names, 'lineNo': lineNos, 'geometry': points})


    

In [92]:

    

gdf.head()


    

    
Out[92]:







  

    

      

      
name
      
lineNo
      
geometry
    
  
  

    

      
0
      
Leicester Abbey
      
10112
      
POINT (-1.132563 52.640379)
    
    

      
1
      
Leicester Abbey
      
10116
      
POINT (-1.132563 52.640379)
    
    

      
2
      
Mozambique Channel
      
10132
      
POINT (41.280858 -18.615949)
    
    

      
3
      
the longest river in America
      
10133
      
POINT (-90.199404 38.627003)
    
    

      
4
      
Wicklow Hotel
      
10154
      
POINT (-6.260651 53.342872)
    
  

In [21]:

    

gdf2 = geopandas.read_file('mapData/ne_50m_land.shp')


    

In [22]:

    

gdf.head()


    

    
Out[22]:







  

    

      

      
name
      
lineNo
      
geometry
    
  
  

    

      
0
      
Leicester Abbey
      
10112
      
POINT (-1.132563 52.640379)
    
    

      
1
      
Leicester Abbey
      
10116
      
POINT (-1.132563 52.640379)
    
    

      
2
      
Mozambique Channel
      
10132
      
POINT (41.280858 -18.615949)
    
    

      
3
      
the longest river in America
      
10133
      
POINT (-90.199404 38.627003)
    
    

      
4
      
Wicklow Hotel
      
10154
      
POINT (-6.260651 53.342872)
    
  

In [23]:

    

gdf2.head()


    

    
Out[23]:







  

    

      

      
scalerank
      
featurecla
      
min_zoom
      
geometry
    
  
  

    

      
0
      
0
      
Land
      
1.5
      
POLYGON ((179.99921875 -16.16855468750001, 179...
    
    

      
1
      
0
      
Land
      
4.0
      
POLYGON ((177.2341796875 -17.14707031250001, 1...
    
    

      
2
      
0
      
Land
      
4.0
      
POLYGON ((127.37265625 0.7913085937499886, 127...
    
    

      
3
      
0
      
Land
      
3.0
      
POLYGON ((-81.33481445312499 24.65048828124999...
    
    

      
4
      
0
      
Land
      
4.0
      
POLYGON ((-80.82939453124999 24.803662109375, ...
    
  

In [24]:

    

gdf.crs = {'init': 'epsg:4326'}
# gdf.crs = {'init': 'epsg:27700'}
# gdf2.crs = {'init': 'epsg:27700'}


    

In [25]:

    

gdf.crs


    

    
Out[25]:





{'init': 'epsg:4326'}

In [26]:

    

mercator, britain, americas, web = (4326, 27700, 2163, 3857)
#gdf = gdf.to_crs(epsg=web)


    

In [27]:

    

gdf.crs, gdf2.crs


    

    
Out[27]:





({'init': 'epsg:4326'}, {'init': 'epsg:4326'})

In [28]:

    

def lineToPercent(lineNo): 
    """ Convert the line number to a percentage in the narrative time of the novel,
    i.e., 0% is the beginning of the novel, 100% is the end. """
    maxLines = {1: 1848, 2: 1458, 3: 1584, 4: 922, 5: 2794}
    totalLines = sum(maxLines.values())
    chap = int(str(lineNo)[0])
    linesIntoChap = lineNo - (chap * 10000)
    preceedingLines = sum([maxLines[i] for i in range(1, chap)])
    return (preceedingLines + linesIntoChap) / totalLines


    

In [29]:

    

gdf['percentNarrative'] = gdf['lineNo'].apply(lineToPercent)


    

In [30]:

    

gdf.head()


    

    
Out[30]:







  

    

      

      
name
      
lineNo
      
geometry
      
percentNarrative
    
  
  

    

      
0
      
Leicester Abbey
      
10112
      
POINT (-1.132563 52.640379)
      
0.013014
    
    

      
1
      
Leicester Abbey
      
10116
      
POINT (-1.132563 52.640379)
      
0.013479
    
    

      
2
      
Mozambique Channel
      
10132
      
POINT (41.280858 -18.615949)
      
0.015338
    
    

      
3
      
the longest river in America
      
10133
      
POINT (-90.199404 38.627003)
      
0.015454
    
    

      
4
      
Wicklow Hotel
      
10154
      
POINT (-6.260651 53.342872)
      
0.017894
    
  

In [93]:

    

# Slice so that it's only showing the British Isles
gdf = gdf.cx[-11:1,50:58]
gdf2 = gdf2.cx[-11:1,50:58]

# Reproject
gdf = gdf.to_crs(epsg=web)
gdf2 = gdf2.to_crs(epsg=web)


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-93-0869ec2b53a4> in <module>
      5 
      6 # Reproject
----> 7 gdf = gdf.to_crs(epsg=web)
      8 gdf2 = gdf2.to_crs(epsg=web)

/nix/store/drqyglqj0y7nqs9fi15c07ll7klms9nz-python3-3.7.3-env/lib/python3.7/site-packages/geopandas/geodataframe.py in to_crs(self, crs, epsg, inplace)
    441         else:
    442             df = self.copy()
--> 443         geom = df.geometry.to_crs(crs=crs, epsg=epsg)
    444         df.geometry = geom
    445         df.crs = geom.crs

/nix/store/drqyglqj0y7nqs9fi15c07ll7klms9nz-python3-3.7.3-env/lib/python3.7/site-packages/geopandas/geoseries.py in to_crs(self, crs, epsg)
    295         from fiona.crs import from_epsg
    296         if self.crs is None:
--> 297             raise ValueError('Cannot transform naive geometries.  '
    298                              'Please set a crs on the object first.')
    299         if crs is None:

ValueError: Cannot transform naive geometries.  Please set a crs on the object first.

In [32]:

    

# Setting the figsize width here (20) seems to take effect,
# but not setting the figsize height (40)
fig, ax = plt.subplots(figsize=(20,20))

gdf2.plot(ax=ax, color='white', edgecolor='black')
gdf.plot(ax=ax, marker='o', c=(gdf.percentNarrative * 256), cmap='Reds', markersize=70, alpha=0.7)

plt.ylim([6400000, 7650000])
plt.xticks([])
plt.yticks([])
plt.savefig('/home/jon/Code/article-jjq/images/portrait-map.svg')
plt.show()


    

In [33]:

    

# Setting the figsize width here (20) seems to take effect,
# but not setting the figsize height (40)
fig, ax = plt.subplots(figsize=(20,20))

gdf2.plot(ax=ax, color='white', edgecolor='black')
gdf.plot(ax=ax, marker='o', c=(gdf.percentNarrative * 256), cmap='Greys', markersize=70, alpha=0.7)

plt.ylim([6400000, 7650000])
plt.xticks([])
plt.yticks([])
plt.savefig('/home/jon/Code/article-jjq/images/portrait-map-bw.svg')
plt.show()