def prune_columns(gds: GeoDataFrame):
"""Remove unneeded columns."""
columns_remove = gds.keys().difference(['osmid', 'geometry', 'main_tag'])
if len(columns_remove) == 0:
return
gds.drop(columns_remove, inplace=True)
def ax_from_frame(frame: GeoDataFrame,
size: ImageSize,
column: Union[HeightColumn, EnergyColumn],
sort_by: Union[HeightColumn, EnergyColumn],
ascending: bool = True,
legend: bool = False,
cmap: str = 'tab20'):
'''
'''
members = EnergyColumn.__members__.values() if \
isinstance(column, EnergyColumn) else \
HeightColumn if isinstance(column, HeightColumn) \
else None
if members is None:
logging.critical("Unknown Column type")
return None
valid = [str(item) for item in members]
keys = [str(item) for item in frame.keys()]
if set(valid) != set(keys):
logging.critical(
f"Generate Energy Map: Shapefile does not contain " +
f"required keys. Keys must be \n{set(valid)}, but keys are " +
f"\n{set(keys)}")
return None
if str(column) not in keys:
logging.critical(f"Generate Energy Map: *column* param {str(column)}" +
f" not valid. Must be one of {valid}")
return None
fig = plt.figure(frameon=False)
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.canvas.draw()
fig.add_axes(ax)
_max = frame[str(column)].max()
_min = frame[str(column)].min()
if legend:
frame.plot(column=str(column),
ax=ax,
vmin=_min,
vmax=_max,
legend=True,
cmap=cmap)
else:
frame.plot(column=str(column), ax=ax, vmin=_min, vmax=_max, cmap=cmap)
return fig, ax
def map_from_frame(frame: GeoDataFrame,
size: ImageSize,
bbox: BBox,
column: Union[HeightColumn, EnergyColumn],
sort_by: Union[HeightColumn, EnergyColumn],
ascending: bool = True,
legend: bool = False,
cmap: str = 'tab20') -> Optional[np.ndarray]:
'''
'''
members = EnergyColumn.__members__.values() if \
isinstance(column, EnergyColumn) else \
HeightColumn if isinstance(column, HeightColumn) \
else None
if members is None:
logging.critical("Unknown Column type")
return None
valid = [str(item) for item in members]
keys = [str(item) for item in frame.keys()]
if set(valid) != set(keys):
logging.critical(
f"Generate Energy Map: Shapefile does not contain " +
f"required keys. Keys must be \n{set(valid)}, but keys are " +
f"\n{set(keys)}")
return None
if str(column) not in keys:
logging.critical(f"Generate Energy Map: *column* param {str(column)}" +
f" not valid. Must be one of {valid}")
return None
# if str(sort_by) not in keys:
# logging.critical(
# f"Map from Geopandas: *sort_by* param {str(sort_by)}" +
# f" not valid. Must be one of {valid}")
# return None
# frame = frame.sort_values(by=str(sort_by))
fig = plt.figure(frameon=False)
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.canvas.draw()
fig.add_axes(ax)
_max = frame[str(column)].max()
_min = frame[str(column)].min()
if legend:
frame.plot(column=str(column),
ax=ax,
vmin=_min,
vmax=_max,
legend=True,
cmap=cmap)
else:
frame.plot(column=str(column), ax=ax, vmin=_min, vmax=_max, cmap=cmap)
plt.gca().set_xlim([bbox.top_left.lon, bbox.bottom_right.lon])
plt.gca().set_ylim([bbox.top_left.lat, bbox.bottom_right.lat])
plt.gca().invert_yaxis()
buf = io.BytesIO()
fig.savefig(buf, format='png', dpi=200, bbox_inches='tight', pad_inches=0)
buf.seek(0)
image = np.frombuffer(buf.getvalue(), dtype=np.uint8)
buf.close()
image = cv2.imdecode(image, 1)
plt.close(fig)
return cv2.resize(cv2.cvtColor(image, cv2.COLOR_BGR2RGB),
(size.width, size.height))
