Programming languages

How to fix GCC error: implicit declaration of function …

Problem:

While trying to compile your C/C++ program, you see an error message like

../src/main.c:48:9: error: implicit declaration of function 'StartBenchmark' [-Werror=implicit-function-declaration]
         StartBenchmark();

Solution:

implicit declaration of function means that you are trying to use a function that has not been declared. In our example above, StartBenchmark is the function that is implicitly declared.

This is how you call a function:

StartBenchmark();

This is how you declare a function:

void StartBenchmark();

The following bullet points list the most common reasons and how to fix them:

  1. Missing #include: Check if the header file that contains the declaration of the function is #included in each file where you call the function (especially the file that is listed in the error message), before the first call of the function (typically at the top of the file). Header files can be included via other headers,
  2. Function name typo: Often the function name of the declaration does not exactly match the function name that is being called. For example, startBenchmark() is declared while StartBenchmark() is being called. I recommend to fix this by copy-&-pasting the function name from the declaration to wherever you call it.
  3. Bad include guard: The include guard that is auto-generated by IDEs often looks like this:
    #ifndef _EXAMPLE_FILE_NAME_H
    #define _EXAMPLE_FILE_NAME_H
    // ...
    #endif

    Note that the include guard definition _EXAMPLE_FILE_NAME_H is not specific to the header filename that we are using (for example Benchmark.h). Just the first of all header file names wil

  4. Change the order of the #include statements: While this might seem like a bad hack, it often works just fine. Just move the #include statements of the header file containing the declaration to the top. For example, before the move:
    #include "Benchmark.h"
    #include "other_header.h"

    after the move:

    #include "Benchmark.h"
    #include "other_header.h"
Posted by Uli Köhler in C/C++, GCC errors

How to measure performance on the PIC32

First, use MPLab Harmony Configurator 3 to enable the CORETIMER module for your project. No special configuration is neccessary.

The PIC32 Core Timer always runs at half the CPU frequency. For example, if the CPU is running at 200 MHz, the Core Timer will run at 100 MHz.

You an then use

uint32_t CORETIMER_CounterGet();

to get the current value of the core timer. Additionally, you can get the frequency of the Core Timer in Hz using

uint32_t CORETIMER_FrequencyGet();

Use the following snippet to measure how long it takes to run a specific function:

uint32_t t0 = CORETIMER_CounterGet();
run_my_func();
uint32_t t1 = CORETIMER_CounterGet();

After that, you can compute the number of seconds it took to run the function using e.g.

uint32_t tdelta = t1 - t0;
float seconds = tdelta / (float)CORETIMER_FrequencyGet();

or the number of milliseconds:

uint32_t tdelta = t1 - t0;
float milliseconds = tdelta / (CORETIMER_FrequencyGet() / 1000.0);

or the number of microseconds:

uint32_t tdelta = t1 - t0;
float microseconds = tdelta / (CORETIMER_FrequencyGet() / 1000000.0);

 

Posted by Uli Köhler in C/C++, Electronics, Embedded

How to fix pandas to_sql() AttributeError: ‘DataFrame’ object has no attribute ‘cursor’

Problem:

You are trying to save your DataFrame in an SQL database using pandas to_sql(), but you see an exception like

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-21-3788db1a4131> in <module>
      7 db = sqlalchemy.create_engine('sqlite:///timeseries.db' class="ansi-blue-fg">)
      8 
----> 9 df.to_sql('timeseries', df)

~/miniconda3/lib/python3.8/site-packages/pandas/core/generic.py in to_sql(self, name, con, schema, if_exists, index, index_label, chunksize, dtype, method)
   2603         from pandas.io import sql
   2604 
-> 2605         sql.to_sql(
   2606             self,
   2607             name,

~/miniconda3/lib/python3.8/site-packages/pandas/io/sql.py in to_sql(frame, name, con, schema, if_exists, index, index_label, chunksize, dtype, method)
    587         )
    588 
--> 589     pandas_sql.to_sql(
    590         frame,
    591         name,

~/miniconda3/lib/python3.8/site-packages/pandas/io/sql.py in to_sql(self, frame, name, if_exists, index, index_label, schema, chunksize, dtype, method)
   1825             dtype=dtype,
   1826         )
-> 1827         table.create()
   1828         table.insert(chunksize, method)
   1829 

~/miniconda3/lib/python3.8/site-packages/pandas/io/sql.py in create(self)
    719 
    720     def create(self):
--> 721         if self.exists():
    722             if self.if_exists == "fail":
    723                 raise ValueError(f"Table '{self.name}' already exists.")

~/miniconda3/lib/python3.8/site-packages/pandas/io/sql.py in exists(self)
    706 
    707     def exists(self):
--> 708         return self.pd_sql.has_table(self.name, self.schema)
    709 
    710     def sql_schema(self):

~/miniconda3/lib/python3.8/site-packages/pandas/io/sql.py in has_table(self, name, schema)
   1836         query = f"SELECT name FROM sqlite_master WHERE type='table' AND name={wld};"
   1837 
-> 1838         return len(self.execute(query, [name]).fetchall()) > 0
   1839 
   1840     def get_table(self, table_name, schema=None):

~/miniconda3/lib/python3.8/site-packages/pandas/io/sql.py in execute(self, *args, **kwargs)
   1677             cur = self.con
   1678         else:
-> 1679             cur = self.con.cursor()
   1680         try:
   1681             cur.execute(*args, **kwargs)

~/miniconda3/lib/python3.8/site-packages/pandas/core/generic.py in __getattr__(self, name)
   5137             if self._info_axis._can_hold_identifiers_and_holds_name(name):
   5138                 return self[name]
-> 5139             return object.__getattribute__(self, name)
   5140 
   5141     def __setattr__(self, name: str, value) -> None:

AttributeError: 'DataFrame' object has no attribute 'cursor'

Solution:

You’re calling to_sql() with the wrong arguments! The second argument needs to be the database connection (e.g. an sqlalchemy engine)! You’re probably calling it like this:

df.to_sql('timeseries', df)

but the second argument needs to be db (or whatever your database connection object is named), not df!

Full working example for to_sql()

import pandas as pd
# Load pre-built time series example dataset
df = pd.read_csv("https://datasets.techoverflow.net/timeseries-example.csv", parse_dates=["Timestamp"])
df.set_index("Timestamp", inplace=True)

import sqlalchemy
db = sqlalchemy.create_engine('sqlite:///timeseries.db')

df.to_sql('timeseries', db, if_exists="replace")
Posted by Uli Köhler in pandas, Python

How to export Pandas dataset to SQLite database

In our previous post we showed how to connect to an SQLite database using sqlalchemy.

In this blogpost, we’ll show how you can export a pandas DataFrame – for example, our time series example dataset – to the SQLite database.

First, we’ll load the example data frame:

import pandas as pd
# Load pre-built time series example dataset
df = pd.read_csv("https://datasets.techoverflow.net/timeseries-example.csv", parse_dates=["Timestamp"])
df.set_index("Timestamp", inplace=True)

Now we can open the SQLite database as shown in our previous post

import sqlalchemy
db = sqlalchemy.create_engine('sqlite:///timeseries.db')

and export the DataFrame to the database:

df.to_sql('timeseries', db, if_exists="replace")

I always recommend using if_exists="replace" (i.e. if the table already exists, replace it) for a quicker development process.

The database looks like this when viewed in an SQLite viewer like HeidiSQL:

Complete code example

import pandas as pd
# Load pre-built time series example dataset
df = pd.read_csv("https://datasets.techoverflow.net/timeseries-example.csv", parse_dates=["Timestamp"])
df.set_index("Timestamp", inplace=True)

import sqlalchemy
db = sqlalchemy.create_engine('sqlite:///timeseries.db')

df.to_sql('timeseries', db, if_exists="replace")

 

Posted by Uli Köhler in pandas, Python

How to create SQLite database using SQLAlchemy

The following code will create my-sqlite.db in the current directory using sqlalchemy:

import sqlalchemy
db = sqlalchemy.create_engine('sqlite:///my-sqlite.db')

Note that you need three slashes in sqlite:/// in order to use a relative path for the DB. If you want an absolute path, use four slashes: sqlite:////.

Posted by Uli Köhler in Python

How to make bounding box larger by a percentage in Python

If we have a bounding box (xmin, xmax, ymin, ymax), we can use the following algorithm to resize the bounding box by e.g. 15% on each side:

xmin -= 0.15 * (xmax - xmin)
xmax += 0.15 * (xmax - xmin)
ymin -= 0.15 * (ymax - ymin)
ymax += 0.15 * (ymax - ymin)

Note that this will reisze the bounding box by 15% (=0.15) on each side, i.e. the total width of the resulting bounding box will be 15% * 2 = 30% larger!

Why it works

xmin -= 0.15 * (xmax - xmin)

is the same as

xmin -= 0.15 * [width of the bounding box]

 

 

Posted by Uli Köhler in Python

How to get bounding box of a country using Natural Earth data and Cartopy

In this example, we’ll determine the bounding box of Kenya using the public domain Natural Earth dataset and the Cartopy library.

Rendering just the bounding box of Kenya (with the actual country being highlighted in green) looks like this:

How to get the bounding box

First we use Cartopy’s cartopy.io.shapereader.natural_earth() function that will automatically download Natural Earth data (if it has already been downloaded, the cached data will be used):

shpfilename = shpreader.natural_earth(resolution='10m',
                                      category='cultural',
                                      name='admin_0_countries')
reader = shpreader.Reader(shpfilename)

Now we can filter for Kenya just like we did in our previous post on How to highlight a specific country using Cartopy:

kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

and get the bounding box using kenya.bounds:

lon_min, lat_min, lon_max, lat_max = kenya.bounds

Complete example code

This code will render the image shown above:

import cartopy.crs as ccrs
import cartopy.feature as cf
from cartopy.feature import ShapelyFeature
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
# Show only Africa
#ax.set_extent([-23, 55, -35, 40])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

import cartopy.io.shapereader as shpreader
# Read shape file
shpfilename = shpreader.natural_earth(resolution='10m',
                                      category='cultural',
                                      name='admin_0_countries')
reader = shpreader.Reader(shpfilename)
# Filter for a specific country
kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]
# Determine bounding box
lon_min, lat_min, lon_max, lat_max = kenya.bounds
ax.set_extent([lon_min, lon_max, lat_min, lat_max])

# Display Kenya's shape
shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

# Save figure as SVG
plt.savefig("Kenya-Bounding-Box-Tight.svg")

 

Posted by Uli Köhler in Cartopy, Geography, Python

How to plot Shapefile data in Cartopy

In order to display shapefile data in Cartopy, we can first use the cartopy.io.shapereader package to read the shape data and then convert the geometry we want to display to a cartopy.feature.ShapelyFeature.

In the following example, we’ll read the Natural Earth ne_110m_admin_0_countries.shp and
Note that there’s an easier way to plot Natural Earth data using shpreader.natural_earth – see How to highlight a specific country using Cartopy and we’ll use the Natural Earth dataset just as an example!

import cartopy.io.shapereader as shpreader
# Read shape file
reader = shpreader.Reader("ne_110m_admin_0_countries.shp")
# Filter for a specific country
kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

# Display Kenya's shape
shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

Complete code example

import cartopy.crs as ccrs
import cartopy.feature as cf
from cartopy.feature import ShapelyFeature
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
# Show only Africa
ax.set_extent([-23, 55, -35, 40])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

import cartopy.io.shapereader as shpreader
# Read shape file
reader = shpreader.Reader("ne_110m_admin_0_countries.shp")
# Filter for a specific country
kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

# Display Kenya's shape
shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

# Save figure as SVG
plt.savefig("Africa-Highlight-Kenya.svg")
Posted by Uli Köhler in Cartopy, Geography, Python

How to highlight a specific country using Cartopy

In our previous posts, e.g. How to draw Africa map using Cartopy we showed how to draw an overview map of an entire continent using Cartopy. This post provides an example of how to highlight a specific country in that map. In this example, we’ll highlight Kenya

The general approach is:

  1. Use cartopy.io.shapereader.natural_earth to download Natural Earth data that contains the shape of Kenya
  2. Convert it to a cartopy.feature.ShapelyFeature
  3. Display said feature

Displaying Kenya’s Natural Earth shape in cartopy

First, we create a Reader for the Natural Earth data. Cartopy will automatically download the data if it has not been cached.

import cartopy.io.shapereader as shpreader

shpfilename = shpreader.natural_earth(resolution='110m',
                                      category='cultural',
                                      name='admin_0_countries')
reader = shpreader.Reader(shpfilename)

Now we can select Kenya by name from the records:

kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

In order to display that geometry, we use

shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

Complete example code

import cartopy.crs as ccrs
import cartopy.feature as cf
from cartopy.feature import ShapelyFeature
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
# Show only Africa
ax.set_extent([-23, 55, -35, 40])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Read Natural Earth data
import cartopy.io.shapereader as shpreader

shpfilename = shpreader.natural_earth(resolution='110m',
                                      category='cultural',
                                      name='admin_0_countries')
reader = shpreader.Reader(shpfilename)
kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

# Display Kenya's shape
shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

# Save figure as SVG
plt.savefig("Africa-Highlight-Kenya.svg")

 

Posted by Uli Köhler in Cartopy, Geography, Python

How to draw Europe map using Cartopy

We can easily draw an Africa Map using Cartopy by setting the extents to [-13, 45, 30, 70]:

ax.set_extent([-13, 45, 30, 70])

Complete code example

The code above produces the image shown above:

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt

proj = ccrs.Miller()
ax = plt.axes(projection=proj)
ax.set_extent([-13, 45, 30, 70])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
ax.add_feature(cf.BORDERS)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Europe.svg")

 

Posted by Uli Köhler in Cartopy, Geography, Python

How to make Cartopy coastline or border lines thicker (line width)

By standard, Cartopy draws every feature with the same line width:

ax.add_feature(cf.COASTLINE)
ax.add_feature(cf.BORDERS)

We can easily increasing the line width by adding e.g. lw=2 to the ax.add_feature() call:

ax.add_feature(cf.COASTLINE, lw=2)
ax.add_feature(cf.BORDERS)

Complete code example

This example produces the image with a wider coast line line width as shown above

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
ax.set_extent([-23, 55, -35, 40])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
ax.add_feature(cf.BORDERS)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Africa-Standard.svg")

 

Posted by Uli Köhler in Cartopy, Geography, Python

How to draw Africa map using Cartopy

We can easily draw an Africa Map using Cartopy by setting the extents to [-23, 55, -35, 40]:

ax.set_extent([-23, 55, -35, 40])

Complete code example

The code above produces the image shown above:

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
ax.set_extent([-23, 55, -35, 40])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
ax.add_feature(cf.BORDERS)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Africa.svg")

 

Posted by Uli Köhler in Cartopy, Geography, Python

How to draw straight line between two coordinates using Cartopy

In our previous posts Minimal Geodetic example using Cartopy and How to increase Geodetic resolution / accuracy / smoothness in Cartopy we have shown how to create a geodetic line on a map. While a geodetic is defined to be the shortest line on the Earth’s surface, it is not a straight line on a map projection.

In order to plot a geodetic we use:

plt.plot([lon1, lon2], [lat1, lat2], transform=ccrs.Geodetic())

In order to plot a straight line, we need to use the same projection as we used to create the map instead of transform=ccrs.Geodetic().

For example, if we created the map using

plt.axes(projection=ccrs.PlateCarree())

we need to plot the line using transform=ccrs.PlateCarree()

plt.plot([lon1, lon2], [lat1, lat2], transform=ccrs.PlateCarree())

In order to avoid errors, I strongly recommend using just one instance of the projection and assigning it to a common variable, for example:

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
plt.plot([-75, 77.23], [43, 28.61], transform=proj)

Note that for reasons currently unknown to me at the moment, this only works for some projections at the moment. Using ccrs.PlateCarree() and ccrs.Miller() works, but using ccrs.Mollweide() does not work!

Complete example

This code reproduces the image shown above:

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
ax.stock_img()
ax.add_feature(cf.BORDERS)
# Add straight line between two points
# Format: plot([lon1, lon2], [lat1, lat2])
plt.plot([-75, 77.23], [43, 28.61], linestyle='--',
         color='blue', linewidth=8,
         transform=proj)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Cartopy-Straight-Line-PlateCarree.svg")

 

Posted by Uli Köhler in Cartopy, Geography, Python

How to increase Geodetic resolution / accuracy / smoothness in Cartopy

In our previous post we have detailed how to draw a geodetic in Cartopy. However, as you can see in the resulting map, the geodetic line is broken up into several clearly visible segments:

In order to fix that, we need to subclass the original projection of the plot. In this example, we’re subclassing ccrs.Mollweide():

import cartopy.crs as ccrs

class HighResMollweide(ccrs.Mollweide):
    @property
    def threshold(self): return 100.0

Note that the default threshold for the Mollweide projection is 100000.0 – you can check for yourself using print(ccrs.Mollweide().threshold)

Now we can use that projection in plt.axes():

ax = plt.axes(projection=HighResMollweide())

Complete example code

This code reproduced the high-resolution geodetic image shown above:

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt

class HighResMollweide(ccrs.Mollweide):
    @property
    def threshold(self): return 100.0

ax = plt.axes(projection=HighResMollweide())
ax.stock_img()
ax.add_feature(cf.BORDERS)
# Add geodetic between two points
# Format: plot([lon1, lon2], [lat1, lat2])
plt.plot([-75, 77.23], [43, 28.61],
         color='blue', linewidth=2,
         transform=ccrs.Geodetic()
         )
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Cartopy-Geodetic-HiRes.svg")

Thanks to @ajdawson on StackOverflow for the original hint on how to solve this!

Posted by Uli Köhler in Cartopy, Geography, Python

Minimal Geodetic example using Cartopy

This minimal example shows you how to plot a geodetic line between two points. It is closely based on the cartopy with matplotlib intro.

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt
ax = plt.axes(projection = ccrs.Mollweide())
ax.stock_img()
ax.add_feature(cf.BORDERS)
# Add geodetic between two points
# Format: plot([lon1, lon2], [lat1, lat2])
plt.plot([-75, 77.23], [43, 28.61],
         color='blue', linewidth=2,
         transform=ccrs.Geodetic()
         )

 

Complete example code

This code reproduces the image shown above:

import cartopy.crs as ccrs
import cartopy.feature as cf
ax = plt.axes(projection = ccrs.Mollweide())
ax.stock_img()
ax.add_feature(cf.BORDERS)
# Add geodetic between two points
# Format: plot([lon1, lon2], [lat1, lat2])
plt.plot([-75, 77.23], [43, 28.61],
         color='blue', linewidth=2,
         transform=ccrs.Geodetic()
         )
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Cartopy-Geodetic.svg")

 

Posted by Uli Köhler in Cartopy, Geography, Python

How to add colored background to Cartopy map

Want to get from this black and white map

to this colored map

in just one line of code? Simply use cartopy’s stock_img():

ax.stock_img()

Complete example code

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt
ax = plt.axes(projection = ccrs.Mollweide())
ax.stock_img()
ax.add_feature(cf.COASTLINE)
ax.add_feature(cf.BORDERS)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Cartopy-Colored.svg")

Posted by Uli Köhler in Cartopy, Geography, Python

How to draw country borders in Cartopy

Use

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt
ax = plt.axes(projection = ccrs.Mercator())
# This will add borders
ax.add_feature(cf.BORDERS)

The following code shows you a minimal example of how to plot country borders (and coastlines) using cartopy:

import cartopy.crs as ccrs
import cartopy.feature as cf
ax = plt.axes(projection = ccrs.Mercator())
ax.add_feature(cf.COASTLINE)
ax.add_feature(cf.BORDERS)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Cartopy-Borders.svg")

Posted by Uli Köhler in Cartopy, Geography, Python

Cartopy minimal example with Coastlines

This example shows you a minimal example of how to plot coastlines using cartopy:

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt
ax = plt.axes(projection = ccrs.Mercator())
ax.add_feature(cf.COASTLINE)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Cartopy-Coastlines.svg")

Posted by Uli Köhler in Cartopy, Geography, Python

How to draw Africa-focused map using matplotlib basemap

Note that matplotlib basemap is deprecated in favour of cartopy !

Also see:

This code allows you to draw an map that is focused on Africa using matplotlib basemap:

my_map = Basemap(projection='ortho', lat_0=10, lon_0=13, resolution='l')

Complete example code

This code reproduces the image shown above:

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
my_map = Basemap(projection='ortho', lat_0=10, lon_0=13, resolution='l')
my_map.drawcoastlines(linewidth=1)
my_map.drawcountries(linewidth=0.5)

# Make plot larger
plt.gcf().set_size_inches(20, 10)
# Save to file
plt.savefig("Africa.svg")

 

Posted by Uli Köhler in Geography, Python