def qerror(ax: Axis, som, **kwargs) -> None:
"""Plot quantization error."""
props = {
'lw': 3,
'alpha': .8,
}
props.update(kwargs)
ax.plot(som.quantization_error, **props)
def umatrix3d(ax: Axis, som, **kwargs) -> None:
"""Plot the U-matrix in three dimensions.
Args:
ax: Axis subplot.
som: SOM instance.
Note:
Figure aspect is set to 'eqaul'.
"""
props = {
'cmap': 'terrain',
}
props.update(kwargs)
ax.plot_surface(*np.mgrid[:som.dx, :som.dy], som.umatrix(), **props)
def cluster_by(ax: Axis, som, data: Array, target: Array, **kwargs) -> None:
"""Plot bmu colored by ``traget``.
Args:
ax: Axis subplot.
som: SOM instance.
data: Input data.
target: Target labels.
"""
props = {
's': 50,
'c': target,
'marker': 'o',
}
props.update(kwargs)
bmu = som.match(data)
bmu_xy = np.fliplr(np.atleast_2d(bmu)).T
ax.scatter(*bmu_xy, **props)
def label_target(ax: Axis, som, data: Array, target: Array, **kwargs) -> None:
"""Add target labels for each bmu.
Args:
ax: Axis subplot.
som: SOM instance.
data: Input data.
target: Target labels.
"""
props = {
'fontsize': 9,
'ha': 'left',
'va': 'bottom',
}
props.update(kwargs)
bmu = som.match(data)
bmu_xy = np.fliplr(np.atleast_2d(bmu)).T
for x, y, t in zip(*bmu_xy, target):
ax.text(x, y, t, fontdict=props)
def hit_counts(ax: Axis,
som,
transform: Optional[Callable] = None,
**kwargs) -> None:
"""Plot the winner histogram.
Each unit is colored according to the number of times it was bmu.
Args:
ax: Axis subplot.
som: SOM instance.
mode: Choose either 'linear', or 'log'.
"""
props = {
'interpolation': None,
'origin': 'lower',
'cmap': 'Greys',
}
props.update(kwargs)
data = som.hit_counts.reshape(som.shape)
if transform is not None:
data = transform(data)
ax.imshow(data, **props)
def _generic_contour(ax: Axis,
data: Array,
outline: bool = False,
**kwargs) -> None:
"""Contour plot.
Args:
ax: Axis subplot.
data: Two-dimensional array.
"""
sdx, sdy = data.shape
overwrites = {
'extent': (-0.5, sdy - 0.5, -0.5, sdx - 0.5),
}
kwargs.update(overwrites)
_ = ax.contourf(data, **kwargs)
_ = ax.set_xticks(range(sdy))
_ = ax.set_yticks(range(sdx))
if outline:
ax.contour(data, cmap='Greys_r', alpha=.7)
ax.set_aspect('equal')
def data_2d(ax: Axis, data: Array, colors: Array, **kwargs) -> None:
"""Scatter plot a data set with two-dimensional feature space.
This just the usual scatter command with some reasonable defaults.
Args:
ax: The axis subplot.
data: The data set.
colors: Colors for each elemet in ``data``.
Returns:
PathCollection.
"""
props = {
'alpha': 0.2,
'c': colors,
'cmap': 'plasma',
'edgecolors': 'None',
's': 10
}
props.update(kwargs)
aplot.outward_spines(ax)
_ = ax.scatter(*data.T, **props)
def wire(ax: Axis,
som,
unit_size: Union[int, float, Array] = 100.0,
line_width: Union[int, float] = 1.0,
highlight: Optional[Array] = None,
labels: bool = False,
**kwargs) -> None:
"""Plot the weight vectors of a SOM with two-dimensional feature space.
Neighbourhood relations are indicate by connecting lines.
Args:
ax: The axis subplot.
som: SOM instance.
unit_size: Size for each unit.
line_width: Width of the wire lines.
highlight: Index of units to be marked in different color.
labels: If ``True``, attach a box with coordinates to each unit.
Returns:
vlines, hlines, bgmarker, umarker
"""
if isinstance(unit_size, np.ndarray):
marker_size = tools.scale(unit_size, 10, 110)
elif isinstance(unit_size, float) or isinstance(unit_size, int):
marker_size = np.repeat(unit_size, som.n_units)
else:
msg = (f'Argument of parameter ``unit_size`` must be real scalar '
'or one-dimensional numpy array.')
raise ValueError(msg)
marker_size_bg = marker_size + marker_size / 100 * 30
bg_color: str = 'w'
hl_color: str = 'r'
line_props = {
'color': 'k',
'alpha': 0.7,
'lw': 1.0,
'zorder': 9,
}
line_props.update(kwargs)
marker_bg_props = {
's': marker_size_bg,
'c': bg_color,
'edgecolors': None,
'zorder': 11,
}
marker_hl_props = {
's': marker_size,
'c': unit_color,
'alpha': line_props['alpha'],
}
if highlight is not None:
bg_color = np.where(highlight, hl_color, bg_color)
rsw = som.weights.reshape(som.shape, 2)
v_wx, v_wy = rsw.T
h_wx, h_wy = np.rollaxis(rsw, 1).T
vlines = ax.plot(v_wx, v_wy, **line_props)
hlines = ax.plot(h_wx, h_wy, **line_props)
bgmarker = ax.scatter(v_wx,
v_wy,
s=marker_size_bg,
c=bg_color,
edgecolors='None',
zorder=11)
umarker = ax.scatter(v_wx,
v_wy,
s=marker_size,
c=unit_color,
alpha=alpha,
edgecolors='None',
zorder=12)
font = {
'fontsize': 4,
'va': 'bottom',
'ha': 'center',
}
bbox = {
'alpha': 0.7,
'boxstyle': 'round',
'edgecolor': '#aaaaaa',
'facecolor': '#dddddd',
'linewidth': .5,
}
if labels is True:
for (px, py), (ix, iy) in zip(som.weights, np.ndindex(shape)):
ax.text(px + 1.3, py, f'({ix}, {iy})', font, bbox=bbox, zorder=13)
ax.set_aspect('equal')
return None