def plot_core_occupancy(occ, path, name):
"""Plot number of compartments per core of a layer.
:param np.ndarray occ: Core occupancy to plot. Shape is equal to the number
of cores per axis.
:param str path: Where to save figure.
:param str name: Name of partition.
"""
occ = normalizeImageDim(occ)
fig, ax = plt.subplots()
im = ax.imshow(occ, cmap='Blues', vmin=0, vmax=1024)
vals = np.unique([0] + list(np.ravel(occ)))
if 1024 - np.max(vals) > 100:
vals = np.concatenate([vals, [1024]])
fig.colorbar(im,
ticks=vals[::(len(vals) // 10) + 1],
fraction=0.02,
pad=0.04)
ax.set_xticks(np.arange(0, occ.shape[1], occ.shape[1] // 10 + 1))
ax.set_yticks(np.arange(0, occ.shape[0], occ.shape[0] // 10 + 1))
ax.tick_params(which='both', left=False, bottom=False)
ax.xaxis.set_minor_locator(IndexLocator(1, 1))
ax.yaxis.set_minor_locator(IndexLocator(1, 1))
ax.grid(which='minor')
ax.set_title('Core occupancy of layer {}'.format(name))
fig.savefig(os.path.join(path, 'coreOccupancy_{}'.format(name)),
bbox_inches='tight')
def plot_multiplicity(m, path, name):
"""Plot multiplicityMap.
:param np.array m: multiplicityMap.
:param str path: Where to save figure.
:param str name: Name of partition.
"""
m = normalizeImageDim(m)
fig, ax = plt.subplots()
im = ax.imshow(m, cmap='Blues', vmin=0)
vals = np.unique(m)
fig.colorbar(im,
ticks=[0] + list(vals[::(len(vals) // 10) + 1]),
fraction=0.02,
pad=0.04)
ax.set_xticks(np.arange(0, m.shape[1], m.shape[1] // 5 + 1))
ax.set_yticks(np.arange(0, m.shape[0], m.shape[0] // 5 + 1))
ax.set_title('Multiplicity map of input to {}'.format(name))
ax.tick_params(which='both', left=False, bottom=False)
ax.xaxis.set_minor_locator(IndexLocator(1, 1))
ax.yaxis.set_minor_locator(IndexLocator(1, 1))
ax.grid(which='minor')
fig.savefig(os.path.join(path, 'multiplicityMap_{}'.format(name)),
bbox_inches='tight')
def plot_coreIdMap(m, path, name):
"""Plot coreIdMap.
:param np.array m: coreIdMap.
:param str path: Where to save figure.
:param str name: Name of partition.
"""
yy = normalizeImageDim(m)
shape = yy.shape
fig, ax = plt.subplots()
im = ax.imshow(yy, cmap='Blues', vmin=0)
vals = np.unique(yy)
fig.colorbar(im,
ticks=vals[::len(vals) // 10 + 1],
fraction=0.02,
pad=0.04)
ax.set_xticks(np.arange(0, shape[1], shape[1] // 5 + 1))
ax.set_yticks(np.arange(0, shape[0], shape[0] // 5 + 1))
ax.tick_params(which='both', left=False, bottom=False)
ax.xaxis.set_minor_locator(IndexLocator(1, 1))
ax.yaxis.set_minor_locator(IndexLocator(1, 1))
ax.grid(which='minor')
if m.ndim == 3:
num_depth_partitions = len(np.unique(m[0, 0, :]))
num_channels = m.shape[-1]
s = '' if num_depth_partitions == 1 else 's'
ss = '' if num_channels == 1 else 's'
ax.set_title('Core ID map of layer {}\n({} partition{} along '
'{} channel{}.)'.format(name, num_depth_partitions, s,
num_channels, ss))
else:
ax.set_title('Core ID map of layer {}'.format(name))
fig.savefig(os.path.join(path, 'partition_{}'.format(name)),
bbox_inches='tight')