def showInference(bn,ie,size="4",cmap=INFOcmap):
"""
Shows a bn annoted with results from inference : entropy and mutual informations
"""
vals={bn.variable(n).name():ie.H(n) for n in bn.ids()}
gr=getBN(bn,size,_normalizeVals(vals,hilightExtrema=False),cmap)
mi=min(vals.values())
ma=max(vals.values())
fig = mpl.figure.Figure(figsize=(8,3))
canvas = fc(fig)
ax1 = fig.add_axes([0.05, 0.80, 0.9, 0.15])
norm = mpl.colors.Normalize(vmin=mi, vmax=ma)
cb1 = mpl.colorbar.ColorbarBase(ax1, cmap=cmap,
norm=norm,
orientation='horizontal')
cb1.set_label('Entropy')
png=print_figure(canvas.figure,"png") # from IPython.core.pylabtools
png_legend="<img style='vertical-align:middle' src='data:image/png;base64,%s'>"%encodestring(png).decode('ascii')
IPython.display.display(IPython.display.HTML("<div align='center'>"+
gr.data+
"</div><div align='center'>"+
"<font color='"+_proba2bgcolor(0.01,cmap)+"'>"+str(mi)+"</font>"
+png_legend+
"<font color='"+_proba2bgcolor(0.99,cmap)+"'>"+str(ma)+"</font>"
"</div>"))
def xkcd_plot(x,
ys,
jiggleScale=5,
xmin=0,
xmax=-1,
ymin=0,
ymax=-1,
ylim_min=1e-5,
ylim_max=10,
xticks=[[4.75, 4.75]],
plotname="xkcd.png",
useLabels=False,
the_labs=None):
xticks = []
for xt in x:
# print 'tick locations' ,xt
xticks.append([xt, xt])
nx = np.linspace(x[0], x[-1], num=257, endpoint=True)
#xmin = 0# x[0] - x[0] * .1
#xmax = x[-1] + x[-1] * .1
maxofys = np.max(ys)
ylim_max = maxofys * 1.1
# Add the jiggles
scale = jiggleScale
yn = []
newscale = 0
for y in ys:
newscale = np.max([newscale, scale * np.max(y)])
scale = newscale
for y in ys:
yy = np.interp(nx, x, y)
if not useLabels:
yy += rand_func() * scale
yn.append(yy)
ys = yn
x = nx
# Set up a figure
fig = Figure()
canvas = fc(fig)
# Plot the data
ax = fig.add_subplot(1, 1, 1)
colors = ['c', 'r', 'g', 'b', 'y']
verticaloffset = .003
plts = []
for i in range(len(ys)):
# lay down a white line first to create overlap effect
# ax.plot(x[xmin:xmax], ys[i][ymin:ymax], 'white', lw=7)
pzzz, = ax.plot(x[xmin:xmax],
ys[i][ymin:ymax] + verticaloffset,
colors[i % len(colors)],
lw=2)
plts.append(pzzz)
ax.set_xlim(x[0] * .9, x[-1] * 1.2)
# Poor man's x-axis. There's probably a better way of doing this.
# xaxis = nx
xaxis = [ylim_min] * 257
if not useLabels:
xaxis += rand_func() * scale / 2.5 - (ylim_max - ylim_min) * .02
# print "axis endpoints", x[0], x[-1], xaxis[0], xaxis[-1]
xxaxis = ((x[0:-1] - x[0] - 2) * 1.1 + (x[0] + 1.5) * 1.1)
if useLabels:
ax.legend(plts, the_labs, loc='upper left')
ax.set_ylim(np.min(xaxis) * 4, ylim_max * 1.1)
# Poor man's x-ticks
# for x in xticks:
# yaxis = [-0.001, 0.001]
# ax.plot(x, yaxis, 'k', lw=1.5)
# ax.set_yscale('log')
# ax.set_xscale('log')
# XKCD font. This won't work on your machine. Install the font
# and change the path to the place where you installed it.
#prop = fm.FontProperties(fname='/Users/damon/Library/Fonts/Humor-Sans.ttf')
# ax.text(4.5, -0.5, 'PEAK', size=11)
# Turn off decoration
if not useLabels:
ax.plot(xxaxis, xaxis[0:-1], 'k', lw=2)
ax.arrow(xxaxis[-1],
xaxis[-2],
0.1,
0,
fc='k',
width=(ylim_max - ylim_min) * .001,
head_width=(ylim_max - ylim_min) * .03,
head_length=.2)
ax.set_xticks([])
ax.set_yticks([])
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_frame_on(False)
return fig
# Turn off all clipping
def noclip(ax):
"Turn off all clipping in axes ax; call immediately before drawing"
ax.set_clip_on(False)
artists = []
artists.extend(ax.collections)
artists.extend(ax.patches)
artists.extend(ax.lines)
artists.extend(ax.texts)
artists.extend(ax.artists)
for a in artists:
a.set_clip_on(False)
noclip(ax)
# Save
fig.savefig(plotname)
b = signal.firwin(20, 0.15, window=('kaiser', 8))
response = signal.lfilter(b,1,coeffs)+1
return response
# Make some data
x = linspace(1.0, 9.0, num=257, endpoint=True)
y1 = 1.5 + 10.0 * (sin(x) * sin(x) / sqrt(x)) * exp(-0.5 * (x - 5.0) * (x - 5.0))
y2 = 3.0 + 10.0 * (sin(x) * sin(x) / sqrt(x)) * exp(-0.5 * (x - 7.0) * (x - 7.0))
y1 *= rand_func()
y2 *= rand_func()
x *= rand_func()
# Set up a figure
fig = figure()
canvas = fc(fig)
# Plot the data
ax = fig.add_subplot(1, 1, 1)
ax.plot(x, y1, 'c', lw=2)
ax.plot(x, y2, 'white', lw=7)
ax.plot(x, y2, 'r', lw=2)
ax.set_ylim(0, 8)
ax.set_xlim(0, 10)
# Poor man's x-axis. There's probably a better way of doing this.
yaxis = [1.0] * 257 * rand_func(3)
xaxis = linspace(0.5,9,257)
#xaxis *= rand_func()
ax.plot(xaxis, yaxis, 'k', lw=2)
ax.arrow(9, 1, 0.1, 0, fc='k', lw=2, head_width=0.2, head_length=0.15)
# Poor man's x-tick
# Make some data
x = linspace(1.0, 9.0, num=257, endpoint=True)
y1 = 1.5 + 10.0 * (sin(x) * sin(x) / sqrt(x)) * exp(-0.5 * (x - 5.0) *
(x - 5.0))
y2 = 3.0 + 10.0 * (sin(x) * sin(x) / sqrt(x)) * exp(-0.5 * (x - 7.0) *
(x - 7.0))
y1 *= rand_func()
y2 *= rand_func()
x *= rand_func()
# Set up a figure
fig = figure()
canvas = fc(fig)
# Plot the data
ax = fig.add_subplot(1, 1, 1)
ax.plot(x, y1, 'c', lw=2)
ax.plot(x, y2, 'white', lw=7)
ax.plot(x, y2, 'r', lw=2)
ax.set_ylim(0, 8)
ax.set_xlim(0, 10)
# Poor man's x-axis. There's probably a better way of doing this.
yaxis = [1.0] * 257 * rand_func(3)
xaxis = linspace(0.5, 9, 257)
#xaxis *= rand_func()
ax.plot(xaxis, yaxis, 'k', lw=2)
ax.arrow(9, 1, 0.1, 0, fc='k', lw=2, head_width=0.2, head_length=0.15)
# Poor man's x-tick
def _reprInformation(bn, evs=None, size=None, cmap=_INFOcmap, asString=False):
"""
repr a bn annotated with results from inference : Information and mutual information
Parameters
----------
bn: pyAgrum.BayesNet
the model
evs: Dict[str|int,str|int|List[float]]
the observations
size: int|str
size of the rendered graph
cmap: matplotlib.colours.Colormap
the cmap
asString: bool
returns the string or display the HTML
Returns
-------
str|None
return the HTML string or directly display it.
"""
if size is None:
size = gum.config["notebook", "default_graph_size"]
if evs is None:
evs = {}
gr, mi, ma = getInformationGraph(bn, evs, size, cmap, withMinMax=True)
# dynamic member makes pylink unhappy
# pylint: disable=no-member
gsvg = IPython.display.SVG(gr.create_svg(encoding="utf-8"))
width = int(gsvg.data.split("width=")[1].split('"')[1].split("pt")
[0]) / mpl.pyplot.rcParams['figure.dpi'] # pixel in inches
if width < 5:
width = 5
fig = mpl.figure.Figure(figsize=(width, 1))
fig.patch.set_alpha(0)
canvas = fc(fig)
ax1 = fig.add_axes([0.05, 0.80, 0.9, 0.15])
norm = mpl.colors.Normalize(vmin=mi, vmax=ma)
cb1 = mpl.colorbar.ColorbarBase(ax1,
cmap=cmap,
norm=norm,
orientation='horizontal')
cb1.set_label('Entropy')
cb1.ax.text(mi,
-2,
f"{mi:.4f}",
ha='left',
va='top',
color=gumcols.proba2bgcolor(0.01, cmap))
cb1.ax.text(ma,
-2,
f"{ma:.4f}",
ha='right',
va='top',
color=gumcols.proba2bgcolor(0.99, cmap))
png = IPython.core.pylabtools.print_figure(
canvas.figure, "png") # from IPython.core.pylabtools
png_legend = f"<img style='vertical-align:middle' src='data:image/png;base64,{encodebytes(png).decode('ascii')}'>"
sss = f"<div align='center'>{gsvg.data}<br/>{png_legend}</div>"
if asString:
return sss
return IPython.display.display(IPython.display.HTML(sss))
def xkcd_plot (x,ys,jiggleScale=5,xmin=0,xmax=-1,ymin=0,ymax=-1,ylim_min=1e-5,ylim_max=10,xticks=[[4.75,4.75]],plotname="xkcd.png",useLabels=False,
the_labs=None):
xticks = []
for xt in x:
# print 'tick locations' ,xt
xticks.append([xt,xt])
nx = np.linspace(x[0], x[-1], num=257, endpoint=True)
#xmin = 0# x[0] - x[0] * .1
#xmax = x[-1] + x[-1] * .1
maxofys = np.max(ys)
ylim_max = maxofys*1.1
# Add the jiggles
scale = jiggleScale
yn = []
newscale = 0;
for y in ys:
newscale = np.max([newscale,scale*np.max(y)])
scale = newscale
for y in ys:
yy = np.interp(nx,x,y)
if not useLabels:
yy += rand_func() * scale
yn.append(yy)
ys = yn
x = nx
# Set up a figure
fig = Figure()
canvas = fc(fig)
# Plot the data
ax = fig.add_subplot(1, 1, 1)
colors = ['c','r','g','b','y']
verticaloffset = .003
plts = []
for i in range(len(ys)):
# lay down a white line first to create overlap effect
# ax.plot(x[xmin:xmax], ys[i][ymin:ymax], 'white', lw=7)
pzzz, = ax.plot(x[xmin:xmax], ys[i][ymin:ymax]+verticaloffset, colors[i%len(colors)], lw=2)
plts.append(pzzz)
ax.set_xlim(x[0]*.9,x[-1]*1.2)
# Poor man's x-axis. There's probably a better way of doing this.
# xaxis = nx
xaxis = [ylim_min] * 257
if not useLabels:
xaxis += rand_func() * scale/2.5-(ylim_max-ylim_min)*.02
# print "axis endpoints", x[0], x[-1], xaxis[0], xaxis[-1]
xxaxis = ((x[0:-1]-x[0]-2)*1.1+(x[0]+1.5)*1.1)
if useLabels:
ax.legend(plts, the_labs,loc='upper left')
ax.set_ylim(np.min(xaxis)*4, ylim_max*1.1)
# Poor man's x-ticks
# for x in xticks:
# yaxis = [-0.001, 0.001]
# ax.plot(x, yaxis, 'k', lw=1.5)
# ax.set_yscale('log')
# ax.set_xscale('log')
# XKCD font. This won't work on your machine. Install the font
# and change the path to the place where you installed it.
#prop = fm.FontProperties(fname='/Users/damon/Library/Fonts/Humor-Sans.ttf')
# ax.text(4.5, -0.5, 'PEAK', size=11)
# Turn off decoration
if not useLabels:
ax.plot(xxaxis, xaxis[0:-1], 'k', lw=2)
ax.arrow(xxaxis[-1], xaxis[-2], 0.1, 0, fc='k', width=(ylim_max-ylim_min)*.001,head_width= (ylim_max-ylim_min)*.03, head_length=.2)
ax.set_xticks([])
ax.set_yticks([])
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_frame_on(False)
return fig
# Turn off all clipping
def noclip(ax):
"Turn off all clipping in axes ax; call immediately before drawing"
ax.set_clip_on(False)
artists = []
artists.extend(ax.collections)
artists.extend(ax.patches)
artists.extend(ax.lines)
artists.extend(ax.texts)
artists.extend(ax.artists)
for a in artists:
a.set_clip_on(False)
noclip(ax)
# Save
fig.savefig(plotname)
