def format_figure(fig: plt.Figure,
title: str = None,
x_label: str = None,
y_label: str = None,
title_y_position: float = 0.93):
fig.set_figwidth(12)
fig.set_figheight(8)
fig.set_facecolor("white")
if title is not None:
fig.suptitle(title,
y=title_y_position,
verticalalignment='top',
fontsize=24)
axes = fig.axes
for ax in axes:
ax.spines['top'].set_color('white')
ax.spines['right'].set_color('white')
ax.set_facecolor("white")
ax.xaxis.grid(which="both", linewidth=0.5)
ax.yaxis.grid(which="both", linewidth=0.5)
ax.xaxis.label.set_fontsize(18)
ax.yaxis.label.set_fontsize(18)
ax.title.set_fontsize(20)
if x_label is not None:
fig.text(0.5, 0.04, x_label, ha='center', fontdict={'size': 18})
if y_label is not None:
fig.text(0.04,
0.5,
y_label,
va='center',
rotation='vertical',
fontdict={'size': 18})
def __mouseRealseEvent(self, e: MouseEvent, fig: Figure, ax: Axes):
""" 鼠标点击画布时显示点击位置 """
# 当鼠标左键的点击位置是ax并且当前工具栏模式不是缩放或者移动时，打印点击位置并显示
if e.inaxes is ax and e.button == MouseButton.LEFT and \
plt.get_current_fig_manager().toolbar.mode not in {'zoom rect', 'pan/zoom'}:
# 移除上一个点击的点
self.__removePoint(ax, 'clicked point')
# 绘制当前点击的点
ax.plot(e.x, e.y, 'g*', label='clicked point')
fig.suptitle(f'Clicked Pos : {(e.x, e.y)}')
fig.canvas.draw()
print(f'Clicked Pos : {(e.x, e.y)}')
class Example(Frame):
def __init__(self, parent):
Frame.__init__(self, parent)
self.hsv_color = colorsys.rgb_to_hsv(0.0, 0.0, 1.0)
self.hex_color = '#0000ff'
self.color_list = ["red","blue","green","orange","purple"]
self.parent = parent
print "Loading model..."
self.lux = Lux()
fp = open(curdir+"/gauss_model.pkl"); self.gm = pickle.load(fp); fp.close()
fp = open(curdir+"/memoized_binomial_data.pkl"); self.curve_data = pickle.load(fp); fp.close()
fp = open(curdir+"/sampling_normalizer.pkl"); self.normalizer = pickle.load(fp); fp.close()
print "Creating UI"
self.initUI()
self.update_output()
self.replot()
def update_output(self):
(h, s, v) = self.hsv_color
self.hsv_var.set("Hue: \t %2.1f \nSat:\t %2.1f \nValue:\t %2.1f" % (h*360,s*100,v*100))
items = self.lux.full_posterior((h * 360, s * 100, v * 100))
self.current_post = items
desc = [ '{:<25} ({:.3f})\n'.format(items[i][0], items[i][1]) for i in range(25) ]
self.display.config(state=NORMAL)
self.display.delete(0, END)
for i in range(25): self.display.insert(END, '{:<20} ({:.3f})'.format(items[i][0], items[i][1]))
self.display.select_set(0, 0)
def plot_lux_model(self, params,ax1,label,support,dim):
cur_color='black'
mu1,sh1,sc1,mu2,sh2,sc2 = params
left_stach=gam_dist(sh1,scale=sc1); lbounds=left_stach.interval(0.99)
right_stach=gam_dist(sh2,scale=sc2); rbounds=right_stach.interval(0.99)
lx=np.linspace(mu1,-180); rx=np.linspace(mu2,360)
s=3;
ax1.plot(rx, [right_stach.sf(abs(y-mu2)) for y in rx],linewidth=s,c=cur_color);
ax1.plot([1.01*mu1,0.99*mu2], [1.,1.], linewidth=s,c=cur_color)
return ax1.plot(lx,[left_stach.sf(abs(y-mu1)) for y in lx],c=cur_color, linewidth=s);
def plot_gm_model(self, params, ax, label, support):
s=3
x = np.linspace(support[0],support[1],360)
return ax.plot(x,norm.pdf(x,params[0],params[1]),c='red', linewidth=s), norm.pdf([params[0]],params[0],[params[1]])[0]
def initUI(self):
self.parent.title("Interactive LUX visualization")
self.pack(fill=BOTH, expand=1)
self.color_frame = Frame(self, border=1)
self.color_frame.pack(side=LEFT)
probe_title_var = StringVar(); probe_title_label = Label(self.color_frame, textvariable=probe_title_var, justify=CENTER, font = "Helvetica 16 bold italic")
probe_title_var.set("Color Probe X"); probe_title_label.pack(side=TOP)
self.hsv_var = StringVar()
self.hsv_label = Label(self.color_frame, textvariable=self.hsv_var,justify=LEFT)
h,s,v = self.hsv_color
self.hsv_var.set("Hue: %2.1f \nSaturation: %2.1f \nValue: %2.1f" % (h*360,s*100,v*100))
self.hsv_label.pack(side=TOP)
self.frame = Frame(self.color_frame, border=1,
relief=SUNKEN, width=200, height=200)
self.frame.pack(side=TOP)
self.frame.config(bg=self.hex_color)
self.frame.bind("<Button-1>",self.onChoose)
self.btn = Button(self.color_frame, text="Select Color",
command=self.onChoose)
self.btn.pack(side=TOP)
posterior_title_var = StringVar(); posterior_title_label = Label(self.color_frame, textvariable=posterior_title_var, justify=CENTER, font = "Helvetica 16 bold italic")
posterior_title_var.set("\n\nLUX's Posterior"); posterior_title_label.pack(side=TOP)
Label(self.color_frame, text="Double click to show details \n(Wait time dependent on computer)").pack(side=TOP)
my_font = tkFont.Font(family="Courier", size=10)
self.display = Listbox(self.color_frame, border=1,
relief=SUNKEN, width=30, height=25, font=my_font)
self.display.pack(side=TOP,fill=Y,expand=1)
self.display.bind("<Double-Button-1>",self.onSelect)
self.display_btn = Button(self.color_frame, text="Show details", command=self.onSelect)
self.display_btn.pack(side=TOP)
self.update_output()
self.fig = Figure(figsize=(10,4), dpi=100)
self.canvas = FigureCanvasTkAgg(self.fig, master=self)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=LEFT, fill=BOTH, expand=1)
self.canvas._tkcanvas.pack(side='top', fill='both', expand=1)
def replot(self):
def gb(x,i,t):
#t is max value, i in number of bins, x is the thing to be binned
if x==t:
return i-1
elif x==0.0:
return 0
return int(floor(float(x)*i/t))
hsv_title = []
j=self.display.curselection()[0]
name = self.current_post[j][0]
mult = lambda x: reduce(operator.mul, x)
g_labels = []; lux_labels=[]; all_g_params=[]
for i in range(3):
def align_yaxis(ax1, v1, ax2, v2):
"""adjust ax2 ylimit so that v2 in ax2 is aligned to v1 in ax1"""
_, y1 = ax1.transData.transform((0, v1))
_, y2 = ax2.transData.transform((0, v2))
inv = ax2.transData.inverted()
_, dy = inv.transform((0, 0)) - inv.transform((0, y1-y2))
miny, maxy = ax2.get_ylim()
ax2.set_ylim(miny, maxy+dy)
subplot = self.fig.add_subplot(4,1,i+1)
dim_label = ["H", "S","V"][i]
subplot.set_ylabel(r"$P(k^{true}_{%s}|x)$" % ["H", "S","V"][i] )
curve_data = self.curve_data[name][i]
scale = lambda x,a=0.3,b=0.9: (b-a)*(x)+a
p_x = lambda x: self.normalizer[i][gb(x,len(self.normalizer[i]),[360,100,100][i])]
max_p_x = max(self.normalizer[i])
#1 is white, 0 is black. so we want highly probable thigns to be black..
if self.lux.get_adj(self.current_post[j][0]):
support = [[-180,180], [0,100],[0,100]][i]
pp = lambda x,i: x-360 if i==0 and x>180 else x
hacky_solution = [360,100,100][i]
w = 1.5 if i==0 else 1
conv = lambda x: x*support[1]/len(curve_data)
bar_colors = ["%s" % (scale(1-p_x(conv(x))/max_p_x)) for x in range(len(curve_data))]
bar1 = subplot.bar([pp(atan2(sin((x*hacky_solution/len(curve_data))*pi/180),cos((x*hacky_solution/len(curve_data))*pi/180))*180/pi,i) for x in range(len(curve_data))],[x/max(curve_data) for x in curve_data], label="%s data" % j,ec="black",width=w,linewidth=0,color=bar_colors)
else:
support = [[0,360], [0,100],[0,100]][i]
w = 1.5 if i==0 else 1
conv = lambda x: x*support[1]/len(curve_data)
bar_colors = ["%s" % (scale(1-p_x(conv(x))/max_p_x)) for x in range(len(curve_data))]
bar1 = subplot.bar([x*support[1]/len(curve_data) for x in range(len(curve_data))],[x/max(curve_data) for x in curve_data], label="%s data" % name[0],ec="black",width=w,linewidth=0,color=bar_colors)
pp = lambda x,*args: x
point = pp(self.hsv_color[i]*[360,100,100][i],i)
hsv_title.append(point)
probeplot = subplot.plot([point,point], [0,1],linewidth=3,c='blue',label="Probe")
#for j in range(5):
lux_plot = self.plot_lux_model(self.lux.get_params(self.current_post[j][0])[i], subplot, self.current_post[j][0],support, i)
subplot2 = subplot.twinx()
gm_plot,gm_height = self.plot_gm_model([pp(g_param,i) for g_param in self.gm[self.current_post[j][0]][0][i]], subplot2, self.current_post[j][0], support)
extra = Rectangle((0, 0), 1, 1, fc="w", fill=False, edgecolor='none', linewidth=0)
subplot.legend([extra], [["Hue", "Saturation", "Value"][i]],loc=2,frameon=False)
if i==0: legend_set=lux_plot+[extra,extra,extra]+gm_plot+[extra,extra,extra]
lux_params = self.lux.get_params(self.current_post[j][0])[i]
g_params = [pp(g_param,i) for g_param in self.gm[self.current_post[j][0]][0][i]]
all_g_params.append(g_params)
g_labels.append(r"$\mu^{%s}=$%2.2f, $\sigma^{%s}$=%2.2f" % (dim_label, g_params[0],dim_label,g_params[1]))
#lux_labels.append(r"$\mu^{L,%s}=$%2.2f, $E[\tau^{L,%s}]$=%2.2f, $\alpha^{L,%s}$=%2.2f, $\beta^{L,%s}$=%2.2f, $\mu^{U,%s}=$%2.2f, $E[\tau^{L,%s}]$=%2.2f, $\alpha^{U,%s}$=%2.2f, $\beta^{U,%s}$=%2.2f" % (dim_label, lux_params[0],dim_label, (lux_params[0]-lux_params[1]*lux_params[2]),dim_label,lux_params[1],dim_label, lux_params[2],dim_label,lux_params[3],dim_label,(lux_params[3]+lux_params[4]*lux_params[5]),dim_label, lux_params[4],dim_label,lux_params[5]))
lux_labels.append(r"$\mu^{L,%s}=$%2.2f, $\alpha^{L,%s}$=%2.2f, $\beta^{L,%s}$=%2.2f, $\mu^{U,%s}=$%2.2f, $\alpha^{U,%s}$=%2.2f, $\beta^{U,%s}$=%2.2f" % (dim_label, lux_params[0],dim_label, lux_params[1],dim_label, lux_params[2],dim_label,lux_params[3],dim_label,lux_params[4],dim_label,lux_params[5]))
subplot.set_xlim(support[0],support[1])
subplot.set_ylim(0,1.05)
subplot2.set_xlim(support[0],support[1])
subplot2.set_ylabel(r"$P(x|Gaussian_{%s})$" % ["H", "S","V"][i])
align_yaxis(subplot, 1., subplot2, gm_height)
leg_loc =(0.9,0.2)
datum = [x*[360,100,100][i] for i,x in enumerate(self.hsv_color)]; phi_value = self.lux.get_phi(datum,self.current_post[j][0])
#gauss_value = mult([norm.pdf(datum[i],all_g_params[i][0],all_g_params[i][1]) for i in range(3)])
leg=self.fig.legend(probeplot+legend_set, ["Probe X"]+ [r"$\mathbf{\phi}_{%s}(X)=\mathbf{%2.5f}$; $\mathbf{\alpha}=\mathbf{%2.4f}$" % (self.current_post[j][0],phi_value,self.lux.get_avail(self.current_post[j][0]))]+lux_labels+
[r"$Normal^{Hue}_{%s}$; $prior(%s)=%2.4f$" % (self.current_post[j][0],self.current_post[j][0], self.gm[self.current_post[j][0]][2])]+[g_labels[0]+"; "+g_labels[1]+"; "+g_labels[2]]
, loc=8, handletextpad=4,labelspacing=0.1)
self.fig.suptitle("%s" % name, size=30)
print "done replotting"
def onChoose(self, *args):
try:
((red,green,blue), hx) = tkColorChooser.askcolor()
except:
print "I think you hit cancel"
return
self.hex_color = hx
self.hsv_color = colorsys.rgb_to_hsv(red/255.0, green/255.0, blue/255.0)
self.frame.config(bg=hx)
self.update_output()
self.fig.clear()
self.replot()
self.canvas.draw()
def onSelect(self, *args):
self.fig.clear()
self.replot()
self.canvas.draw()
class Example(Frame):
def __init__(self, parent):
Frame.__init__(self, parent)
self.hsv_color = colorsys.rgb_to_hsv(0.0, 0.0, 1.0)
self.hex_color = '#0000ff'
self.color_list = ["red","blue","green","orange","purple"]
self.parent = parent
print "Getting Model"
self.lux = lux.LUX("lux.xml")
print "Creating UI"
self.initUI()
self.update_output()
def update_output(self):
(h, s, v) = self.hsv_color
items = self.lux.full_posterior((h * 360, s * 100, v * 100))
self.current_post = items
desc = [ '{} ({:.3f})\n'.format(items[i][0], items[i][1]) for i in range(25) ]
self.display.config(state=NORMAL)
self.display.delete(1.0, END)
self.display.insert(END, ''.join(desc))
self.display.config(state=DISABLED)
def make_plotter(self, params,ax1,label,cur_color,support):
mu1,sh1,sc1,mu2,sh2,sc2 = params
left_stach=gam_dist(sh1,scale=sc1); lbounds=left_stach.interval(0.99)
right_stach=gam_dist(sh2,scale=sc2); rbounds=right_stach.interval(0.99)
lx=np.linspace(mu1,-180); rx=np.linspace(mu2,360)
s=3; #cur_color='black'
ax1.plot(rx, [1-right_stach.cdf(abs(y-mu2)) for y in rx],linewidth=s,c=cur_color);
ax1.plot([1.01*mu1,0.99*mu2], [1,1], linewidth=s,c=cur_color)
return ax1.plot(lx,[1-left_stach.cdf(abs(y-mu1)) for y in lx],c=cur_color, label=r"$\phi^{Hue}_{%s}$" % label,linewidth=s);
def initUI(self):
self.parent.title("Interactive LUX visualization")
self.pack(fill=BOTH, expand=1)
self.color_frame = Frame(self, border=1)
self.color_frame.pack(side=LEFT)
self.frame = Frame(self.color_frame, border=1,
relief=SUNKEN, width=100, height=100)
#self.frame.place(x=160, y=30)
self.frame.pack(side=TOP)
self.frame.config(bg=self.hex_color)
self.btn = Button(self.color_frame, text="Select Color",
command=self.onChoose)
self.btn.pack(side=TOP)
#self.btn.place(x=30, y=30)
self.display = Text(self, border=1,
relief=SUNKEN, width=30, height=5)
#self.display.place(x=280, y=30)
self.display.pack(side=LEFT,fill=Y,expand=1)
self.update_output()
self.fig = Figure(figsize=(10,4), dpi=100)
self.replot()
self.canvas = FigureCanvasTkAgg(self.fig, master=self)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=LEFT, fill=BOTH, expand=1)
self.canvas._tkcanvas.pack(side='top', fill='both', expand=1)
def replot(self):
hsv_title = []
for i in range(3):
if self.lux.get_adj(self.current_post[0][0]):
support = [[-180,180], [0,100],[0,100]][i]
pp = lambda x,i: x-360 if i==0 and x>180 else x
else:
support = [[0,360], [0,100],[0,100]][i]
pp = lambda x,*args: x
subplot = self.fig.add_subplot(3,1,i+1)
subplot.set_xlim(support[0],support[1])
subplot.set_ylabel("%s" % ["Hue", "Saturation","Value"][i])
point = pp(self.hsv_color[i]*[360,100,100][i],i)
hsv_title.append(point)
probeplot = subplot.plot([point,point], [0,1],linewidth=3,c='black',label="Probe")
legend_set = []
for j in range(5):
test = self.make_plotter(self.lux.get_params(self.current_post[j][0])[i], subplot, self.current_post[j][0],self.color_list[j],support)
if type(test)==type([]): legend_set+=test
else: legend_set.append(test)
self.fig.legend(legend_set, [r"$\phi_{%s}$; $\alpha=%2.4f$" % (x[0],self.lux.get_avail(x[0])) for x in self.current_post[:5]], loc=1)
self.fig.suptitle("HSV (%2.2f,%2.2f,%2.2f) top 5 Phi curves" % (hsv_title[0],hsv_title[1],hsv_title[2]))
def onChoose(self):
((red,green,blue), hx) = tkColorChooser.askcolor()
self.hex_color = hx
self.hsv_color = colorsys.rgb_to_hsv(red/255.0, green/255.0, blue/255.0)
self.frame.config(bg=hx)
self.update_output()
self.fig.clear()
self.replot()
self.canvas.draw()
def set_figure_properties(fig: plt.Figure, **kwargs) -> None:
"""
Ease the configuration of a :class:`matplotlib.figure.Figure`.
Parameters
----------
fig : matplotlib.figure.Figure
The figure.
Keyword arguments
-----------------
fontsize : int
Font size to use for the plot titles, and axes ticks and labels.
Defaults to 12.
tight_layout : bool
`True` to fit the whole subplots into the figure area,
`False` otherwise. Defaults to `True`.
tight_layout_rect : Sequence[float]
A rectangle (left, bottom, right, top) in the normalized figure
coordinate that the whole subplots area (including labels) will
fit into. Defaults to (0, 0, 1, 1).
suptitle : str
The figure title. Defaults to an empty string.
xlabel : str
TODO
ylabel : str
TODO
figlegend_on : bool
TODO
figlegend_ax : int
TODO
figlegend_loc : `str` or `Tuple[float, float]`
TODO
figlegend_framealpha : float
TODO
figlegend_ncol : int
TODO
subplots_adjust_hspace : float
TODO
subplots_adjust_vspace : float
TODO
"""
fontsize = kwargs.get("fontsize", 12)
tight_layout = kwargs.get("tight_layout", True)
tight_layout_rect = kwargs.get("tight_layout_rect", (0, 0, 1, 1))
suptitle = kwargs.get("suptitle", "")
x_label = kwargs.get("x_label", "")
x_labelpad = kwargs.get("x_labelpad", 20)
y_label = kwargs.get("y_label", "")
y_labelpad = kwargs.get("y_labelpad", 20)
figlegend_on = kwargs.get("figlegend_on", False)
figlegend_ax = kwargs.get("figlegend_ax", 0)
figlegend_loc = kwargs.get("figlegend_loc", "lower center")
figlegend_framealpha = kwargs.get("figlegend_framealpha", 1.0)
figlegend_ncol = kwargs.get("figlegend_ncol", 1)
wspace = kwargs.get("subplots_adjust_wspace", None)
hspace = kwargs.get("subplots_adjust_hspace", None)
rcParams["font.size"] = fontsize
if suptitle is not None and suptitle != "":
fig.suptitle(suptitle, fontsize=fontsize + 1)
if x_label != "" or y_label != "":
ax = fig.add_subplot(111)
ax.set_frame_on(False)
ax.set_xticks([])
ax.set_xticklabels([], visible=False)
ax.set_yticks([])
ax.set_yticklabels([], visible=False)
if x_label != "":
ax.set_xlabel(x_label, labelpad=x_labelpad)
if y_label != "":
ax.set_ylabel(y_label, labelpad=y_labelpad)
if tight_layout:
fig.tight_layout(rect=tight_layout_rect)
if figlegend_on:
handles, labels = fig.get_axes()[figlegend_ax].get_legend_handles_labels()
fig.legend(
handles,
labels,
loc=figlegend_loc,
framealpha=figlegend_framealpha,
ncol=figlegend_ncol,
)
if wspace is not None:
fig.subplots_adjust(wspace=wspace)
if hspace is not None:
fig.subplots_adjust(hspace=hspace)
def plot_joint_parameter_posteriors(fig: plt.Figure,
parameter_names: [str],
accepted_parameters: [[float]],
predicted_vals: [float],
priors: ["stats.Distribution"],
weights=None) -> plt.Figure:
if (len(parameter_names) != 2): parameter_names = ["", ""]
for p in accepted_parameters:
if (len(p) != 2):
raise Exception("All `accepted_parameters` must be 2d exactly.")
if (len(priors) != 2):
raise Exception("Exactly 2 `priors` must be provided.")
weights = weights if (weights) else [
1 / len(accepted_parameters) for _ in range(len(accepted_parameters))
]
acc_params_x = [p[0] for p in accepted_parameters]
acc_params_y = [p[1] for p in accepted_parameters]
fig = plt.figure()
gs = GridSpec(4, 4)
ax_scatter = fig.add_subplot(gs[1:4, 0:3])
ax_hist_x = fig.add_subplot(gs[0, 0:3])
ax_hist_y = fig.add_subplot(gs[1:4, 3])
# plot scatter
sns.kdeplot(acc_params_x,
acc_params_y,
cmap="Blues",
shade=True,
weights=weights,
ax=ax_scatter)
# plot accepted data
ax_hist_x.hist(acc_params_x, density=True)
ax_hist_y.hist(acc_params_y, orientation='horizontal', density=True)
# plot priors used
hist_x_xs = np.linspace(min(acc_params_x + [priors[0].ppf(.01)]),
max(acc_params_x + [priors[0].ppf(.99)]), 100)
ax_hist_x.plot(hist_x_xs,
priors[0].pdf(hist_x_xs),
"k-",
lw=2,
label='Prior')
hist_y_xs = np.linspace(min(acc_params_y + [priors[1].ppf(.01)]),
max(acc_params_y + [priors[1].ppf(.99)]), 100)
ax_hist_y.plot(priors[1].pdf(hist_y_xs),
hist_y_xs,
"k-",
lw=2,
label='Prior')
# plot smooth posterior (ie KDE)
density_x = stats.kde.gaussian_kde(acc_params_x, weights=weights)
ax_hist_x.plot(hist_x_xs,
density_x(hist_x_xs),
"--",
lw=2,
c="orange",
label="Posterior KDE")
density_y = stats.kde.gaussian_kde(acc_params_y, weights=weights)
ax_hist_y.plot(density_y(hist_y_xs),
hist_y_xs,
"--",
lw=2,
c="orange",
label="Posterior KDE")
# plot posterior mean
ax_hist_x.vlines(predicted_vals[0],
ymin=0,
ymax=ax_hist_x.get_ylim()[1],
colors="orange")
ax_hist_y.hlines(predicted_vals[1],
xmin=0,
xmax=ax_hist_y.get_xlim()[1],
colors="orange")
# make legend
f = lambda m, l, c: ax_scatter.plot([], [], marker=m, color=c, ls=l)[0]
handles = [
f(None, "-", "black"),
f(None, "-", "orange"),
f(None, "--", "orange"),
f("s", "", "#1f77b4")
]
# ax_scatter.legend(handles=handles,labels=["Prior","Posterior Mean","Posterior KDE","Accepted"],fontsize=18)
ax_scatter.set_xlim((hist_x_xs[0], hist_x_xs[-1]))
ax_scatter.set_ylim((hist_y_xs[0], hist_y_xs[-1]))
ax_scatter.set_xlabel(parameter_names[0])
ax_scatter.set_ylabel(parameter_names[1])
ax_scatter.margins(0)
ax_hist_x.margins(0)
ax_hist_y.margins(0)
title_ending = "" if "" in parameter_names else " for {} & {}".format(
parameter_names[0], parameter_names[1])
fig.suptitle("Joint and Marginal Posteriors{}.".format(title_ending))
return fig
