def display_2d_hists(self):
fig, axes = utils.init_grid(rows=self.numobj, cols=4, figsize=(16,4*self.numobj))
if config['mec']['dithered']:
bins = [np.linspace(0, sp.sample_time * sp.numframes, 50), np.linspace(-mp.array_size[0], 0, 50),
np.linspace(0, mp.array_size[0], mp.array_size[0]),
np.linspace(0, mp.array_size[1], mp.array_size[1])]
else:
bins = [np.linspace(0, sp.sample_time * sp.numframes, 50), np.linspace(-mp.array_size[0], 0, 50), range(mp.array_size[0]),
range(mp.array_size[1])]
# if config['data']['trans_polar']:
# bins[2] = np.linspace(0, np.sqrt(((mp.array_size[0]/2)**2) * 2), mp.array_size[0])
# bins[3] = np.linspace(-np.pi,np.pi, mp.array_size[1])
coord = 'tpxy'
for o in range(self.numobj):
H, _ = np.histogramdd(self.photons[o], bins=bins)
for p, pair in enumerate([['y','x'], ['x','p'], ['x','t'], ['p','t']]):
inds = coord.find(pair[0]), coord.find(pair[1])
sumaxis = tuple(np.delete(range(len(coord)), inds))
image = np.sum(H, axis=sumaxis)
if pair in [['x','p'], ['x','t']]:
image = image.T
inds = inds[1], inds[0]
axes[o,p].imshow(image, aspect='auto', origin='lower', norm=LogNorm(),
extent=[bins[inds[0]][0],bins[inds[0]][-1],bins[inds[1]][0],bins[inds[1]][-1]])
plt.show(block=True)
def get_simple_warehouse():
dimensions = (4, 4)
grid = utils.init_grid(dimensions)
# Fill out first column, bottom to top
grid[0][0] = NavigableTileCell()
grid[0][1] = NavigableTileCell()
grid[0][2] = NavigableTileCell()
grid[0][3] = NavigableTileCell()
# Fill out second column, bottom to top
grid[1][0] = NavigableTileCell()
grid[1][1] = ShelvingCell(Direction.SOUTH)
grid[1][2] = ShelvingCell(Direction.NORTH)
grid[1][3] = NavigableTileCell()
# Fill out third column, bottom to top
grid[2][0] = NavigableTileCell()
grid[2][1] = ShelvingCell(Direction.SOUTH)
grid[2][2] = ShelvingCell(Direction.NORTH)
grid[2][3] = NavigableTileCell()
# Fill out fourth column, bottom to top
grid[3][0] = NavigableTileCell()
grid[3][1] = NavigableTileCell()
grid[3][2] = NavigableTileCell()
grid[3][3] = NavigableTileCell()
warehouse = GridWarehouse(dimensions, grid)
return warehouse
def generateHeatmap(boundaryFile,
coordval,
outfile=utils.FILE_TIFF,
dtype=utils.np.uint32,
nodata=-1):
""" coordval = { (20.31, 102.34672): 12, (latVal, lonVal): val } """
cells, lons, lats = processShapeFile(boundaryFile, onlyone=True)
def cell2rc(coords):
return (coords[1] - lats[0], coords[0] - lons[0])
active, processed_cnt = cells.get('main'), 0
if not active:
echo('ERR processing boundary, stopping here')
return
grid, transform, nodata = utils.init_grid(lons, lats, dtype, nodata,
active)
for key in coordval:
if len(key) != 2 or not key[0] or not key[1]: continue
val = coordval[key]
cell = utils.deg2cell(key)
if cell in active:
echo(f'processing {key} = {val}')
processed_cnt += 1
utils.fill_hotspot(grid, cell2rc(cell), val)
echo(f'total processed {processed_cnt}')
utils.write_tiff(outfile, grid, transform, nodata)
def generateShapes(boundaryFile,
keyval,
outfile=utils.FILE_TIFF,
dtype=utils.np.uint32,
recordfn=lambda x: x[3],
nodata=-1):
""" keyval = { 'SomeState': 1.2, 'SomeCouty': 1.3 } """
cells, lons, lats = processShapeFile(boundaryFile, recordfn)
def cell2rc(coords):
return (coords[1] - lats[0], coords[0] - lons[0])
grid, transform, nodata = utils.init_grid(lons, lats, dtype, nodata)
for key in keyval:
if not key: continue
val, active = keyval[key], cells.get(key.lower().strip())
if not active:
echo(f'ERR cannot find {key} in boundary file')
continue
echo(f'processing {key}')
for cell in active:
r, c = cell2rc(cell)
grid[r, c, 0] = val
utils.write_tiff(outfile, grid, transform, nodata)
def get_georgia_tech_library_warehouse():
larger_warehouse = get_larger_warehouse()
larger_warehouse_grid = larger_warehouse.grid
dimensions = (8, 16)
grid = utils.init_grid(dimensions)
for col_num in range(8):
for row_num in range(16):
grid[col_num][row_num] = copy.copy(
larger_warehouse_grid[col_num][row_num % 4])
return GridWarehouse(dimensions, grid)
def get_larger_warehouse():
dimensions = (8, 4)
grid = utils.init_grid(dimensions)
for row_num in range(4):
grid[0][row_num] = NavigableTileCell()
for col_num in range(1, 7):
grid[col_num][0] = NavigableTileCell()
grid[col_num][1] = ShelvingCell(Direction.NORTH)
grid[col_num][2] = ShelvingCell(Direction.SOUTH)
grid[col_num][3] = NavigableTileCell()
for row_num in range(4):
grid[7][row_num] = NavigableTileCell()
warehouse = GridWarehouse(dimensions, grid)
return warehouse
def display_2d_hists(self, ind=None):
fig, axes = utils.init_grid(rows=self.num_classes, cols=3, figsize=(16,4*self.num_classes))
# fig, axes = utils.init_grid(rows=self.num_classes, cols=4)
if ind:
fig.suptitle(f'{ind}', fontsize=16)
if not self.normalised:
bins = [np.linspace(0, sp.sample_time * sp.numframes, 50), np.linspace(-120, 0, 50), range(mp.array_size[0]),
range(mp.array_size[1])]
else:
radius = 1.
bins = [np.linspace(-radius,radius,50), np.linspace(-radius,radius,50),
np.linspace(-radius,radius,mp.array_size[0]), np.linspace(-radius,radius,mp.array_size[0])]
coord = 'tpxy'
for o in range(self.num_classes):
if ind:
H, _ = np.histogramdd(self.data[ind, (self.labels[ind] == o)], bins=bins)
else:
H, _ = np.histogramdd(self.data[self.labels==o], bins=bins)
for p, pair in enumerate([['x','y'], ['x','p'], ['x','t']]):
inds = coord.find(pair[0]), coord.find(pair[1])
sumaxis = tuple(np.delete(range(len(coord)), inds))
image = np.sum(H, axis=sumaxis)
if pair in [['x','p'], ['x','t']]:
image = image.T
inds = inds[1], inds[0]
axes[o,p].imshow(image, norm=None, aspect='auto',
extent=[bins[inds[0]][0],bins[inds[0]][-1],bins[inds[1]][0],bins[inds[1]][-1]])
axes[o,p].set_xlabel(f'{pair[1]}', fontsize=18)
axes[o,p].set_ylabel(f'{pair[0]}', fontsize=16)
axes[o, p].set_xlim([-1,1])
axes[o, p].set_ylim([-1,1])
plt.tight_layout()
plt.show(block=True)