In [1]:

    

from droplet_planning import svg_polygons_to_df
from path_helpers import path
from dmf_device_ui.tesselate import tesselate_shapes_frame
from dmf_device_ui.plot import plot_shapes
from dmf_device_ui.point_query import get_shapes_pymunk_space

%matplotlib inline


    

    




Loading chipmunk for Windows (32bit) [C:\Users\Christian\Documents\microdrop-1.0\python-2.7.9\lib\site-packages\pymunk\chipmunk.dll]

In [2]:

    

device_svg = 'static/device.svg'

# Read SVG polygons into dataframe, one row per polygon vertex.
df_electrodes = svg_polygons_to_df(device_svg)

# Tesselate electrode polygons into convex shapes (triangles), for
# compatability with `pymunk`.
df_electrode_tesselations = tesselate_shapes_frame(df_electrodes, ['path_id'])

# Create `pymunk` space and add a body for each convex shape.  Each
# body is mapped to the original `path_id` through `electrode_bodies`.
electrodes_space, electrode_bodies = \
    get_shapes_pymunk_space(df_electrode_tesselations,
                            ['path_id', 'triangle_i'])


    

In [3]:

    

axis = plot_shapes(df_electrode_tesselations, ['path_id', 'triangle_i'],
                   fc='none')
plot_shapes(df_electrodes, ['path_id'], alpha=.3, axis=axis)


    

    
Out[3]:





<matplotlib.axes._subplots.AxesSubplot at 0xa40b350>






    

In [4]:

    

shape = electrodes_space.point_query_first((275, 100))
if shape:
    print electrode_bodies[shape.body]


    

    




electrode32