pyheatmap

Python library, provides various utilities for rendering heat maps.

Install dependencies and execute run.sh to see the result.

Input data format of all tools is the same "x,y[,weight]":

0.1,0.3,3.0
0.5,0.6,6.0
0.12,0.74       # weight defaults to 1.0
...

mapcoords.py

Receives file or stream of points and normalizes points coordinates given their bounding rectangle. Output points X,Y coordinates fall in range [0, 1].

Usage example:
```
python pyheatmap/mapcoords.py \
   --area=46,57,180,191 \
   resources/positions.csv > my_points_normalized.csv
```
heataccum.py

Receives file or stream of points and outputs accumulated values. It uses grid space partitioning and collapses points within specified threshold into single point, accumulating the weights. This allows to feed it very large set of points and receive an accumulated summary that can be used for final rendering. It also normalizes the 'weight' component of the input points, the point in grid with biggest weight will have weight of 1.0.

Usage example:
```
python pyheatmap/heataccum.py \
   --grid=100,100 \
   my_points_normalized.csv > heat.csv
```
heatmap.py

Renders heat map points on top of the background image. Input is points in format "x,y,weight":
```
0.1,0.3,1.0
 0.5,0.6,1.0
 ...
```
Weight parameter is optional (defaults to 1.0). Coordinates expected to be normalized in image space and fall into [0, 1] range.

Usage example:
```
python pyheatmap/heatmap.py \
   --palette=resources/palette.png \
   --bg=resources/usa.jpg \
   --dot=35 \
   --opacity=0.8 \
   resources/heat.csv
```

And of course you can pipe everything together (check run.sh for example)!

Dependencies