def la_draw(new: tuple, points: tuple, triplets: tuple, anaDiff: tuple, cl: str, plt=plt):
FOLDER = os.path.join(settings.BASE_DIR, 'static/img/lazy/')
NB_TRIPLET_DISPLAYED = 4
plt.xlim(0, 1)
plt.ylim(0, 1)
fig = plt.gcf()
removeFiles(FOLDER)
# IMAGE 1 #
# Training set
plt.scatter(
[point[0] for point in points],
[point[1] for point in points],
c=[point[2] for point in points],
s=POINTS_SIZE,
linewidths=0
)
plt.scatter(new[0], new[1], c="#000000", s=POINTS_SIZE, linewidths=0)
pylab.savefig(FOLDER + '0/0')
def kmeans_draw(new, points, neighbors, nneighbors, cl):
FOLDER = os.path.join(settings.BASE_DIR, 'static/img/kmeans/')
removeFiles(FOLDER)
# Clear the figure
plt.clf()
plt.xlim(0, 1)
plt.ylim(0, 1)
plt.scatter(
[point[0] for point in points],
[point[1] for point in points],
c=[point[2] for point in points],
s=POINTS_SIZE,
linewidths=0,
)
pylab.savefig(FOLDER +"0/" + '1', bbox_inches='tight')
plt.scatter(new[0], new[1], c="#000000", s=POINTS_SIZE, linewidths=0)
pylab.savefig(FOLDER +"1/"+ '2', bbox_inches='tight')
plt.scatter(new[0], new[1], c=cl, s=POINTS_SIZE, linewidths=0)
pylab.savefig(FOLDER +"4/" '5', bbox_inches='tight')
plt.scatter(new[0], new[1], c="#000000", s=POINTS_SIZE, linewidths=0)
i=0
for d in nneighbors:
plt.plot([new[0], points[d[0]][0]], [new[1], points[d[0]][1]], c="#878787", alpha=.3)
pylab.savefig(FOLDER+'3/' + str(i), bbox_inches='tight')
i+=1
plt.scatter(new[0], new[1], c="#000000")
i=0
for d in neighbors:
plt.plot([new[0], points[d[0]][0]], [new[1], points[d[0]][1]], c="#878787", alpha=.3)
pylab.savefig(FOLDER +"2/" +str(i), bbox_inches='tight')
i+=1
def f_draw(new: tuple, points: tuple, triplets: tuple, anaDiff: tuple, cl: str, plt=plt):
FOLDER = os.path.join(settings.BASE_DIR, 'static/img/fadana/')
NB_TRIPLET_DISPLAYED = 4
plt.xlim(0, 1)
plt.ylim(0, 1)
fig = plt.gcf()
removeFiles(FOLDER)
# IMAGE 1 #
# Training set
plt.scatter(
[point[0] for point in points],
[point[1] for point in points],
c=[point[2] for point in points],
s=POINTS_SIZE,
linewidths=0
)
plt.scatter(new[0], new[1], c="#000000", s=POINTS_SIZE, linewidths=0)
pylab.savefig(FOLDER + '0/0')
# IMAGE 2 #
# Triplets
tripletsDisplayed = [choice(triplets) for i in range(NB_TRIPLET_DISPLAYED)]
# Highlights triplets
label = ['A', 'B', 'C']
for i, t in enumerate(tripletsDisplayed):
patchs = [fig.gca().add_artist(plt.Circle((points[t[i+1]][0], points[t[i+1]][1]), radius=0.02, color='#FF0000')) for i in range(3)]
texts = [pylab.text(points[t[i+1]][0], points[t[i+1]][1], label[i]) for i in range(3)]
pylab.savefig(FOLDER + '1/' + str(i))
# Clear circles and texts
for i in range(3):
patchs[i].remove()
texts[i].remove()
# IMAGE 3 #
# computes analogical difference
print("On trouve les meilleurs triplets en résolvant le calcul de différence analogique")
print(tripletsDisplayed[0])
# txt = pylab.text(.5, 1.05, 'Find best triplets solving analogical difference')
a = points[tripletsDisplayed[0][1]]
b = points[tripletsDisplayed[0][2]]
c = points[tripletsDisplayed[0][3]]
patchs = [fig.gca().add_artist(plt.Circle((points[tripletsDisplayed[0][i+1]][0],
points[tripletsDisplayed[0][i+1]][1]),
radius=0.02,
color='#FF0000')) for i in range(3)]
pylab.savefig(FOLDER + '2/0')
# txt.remove()
# remove patches
for p in patchs:
p.remove()
# IMAGE 4 #
annot = []
for i, p in enumerate([a, b, c]):
# Fancy annotation describing the x and y values and the place in the equation of the point
annot.append(plt.annotate(label[i] + '\nx = '+ str(round(p[0], 3)) + '\ny = ' + str(round(p[1], 3)),
xy=(p[0], p[1]), xytext=(-20,20),
textcoords='offset points', ha='center', va='bottom',
bbox=dict(boxstyle='round,pad=0.2', fc='yellow', alpha=0.3),
arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0.5',
color='red')))
# print("On calcul la difference analogique de chaque composante (valeurs normalisées)")
# txt = pylab.text(.6, 1.05, 'A - B, on each attribut')
adx1 = a[0] - b[0] # A - B
ady1 = a[1] - b[1]
txt1 = pylab.text(.095, 1.08, "Ax - Bx = " + str(adx1))
txt2 = pylab.text(.095, 1.02, "Ay - By = " + str(ady1))
pylab.savefig(FOLDER + '3/0')
# Analogical difference C and D
# txt.remove()
txt1.remove()
txt2.remove()
# txt = pylab.text(.6, 1.05, 'C - D, on each attribut')
adx2 = c[0] - new[0] # C - D
ady2 = c[1] - new[1]
txt1 = pylab.text(.095, 1.08, "Cx - Dx = " + str(adx2))
txt2 = pylab.text(.095, 1.02, "Cy - Dy = " + str(ady2))
pylab.savefig(FOLDER + '4/0')
# txt.remove()
txt1.remove()
txt2.remove()
# remove annoations
for a in annot:
a.remove()
# Real analogical difference
# pylab.text('AD = 1 - | (a - B) - (C - D) |, on each attribute, then sum everything to get the final analogical difference')
adx = 1 - abs(adx1 - adx2) # AD = 1 - | (A - B) - (C - D) |
# print("AD(Ax, Bx) = 1 - | (Ax - Bx) - (Cx - Dx) | = " + str(adx))
ady = 1 - abs(ady1 - ady2)
# print("AD(Ay, By) = 1 - | (Ay - By) - (Cy - Dy) | = " + str(ady))
ad = adx + ady
# print("AD(A, B, C, D) Finale = " + str(ad))
txt = pylab.text(.5, 1.05, "AD(A, B, C, D) Finale = " + str(ad))
pylab.savefig(FOLDER + '5/0')
txt.remove()
# IMAGE 5 #
for i, closest in enumerate(anaDiff):
tplt = triplets[closest[0]]
# Circles to highlight the current points of the equation
w, x, y = points[tplt[1]], points[tplt[2]], points[tplt[3]]
annot1 = plt.annotate(s='A', xy=(w[0], w[1]))
annot2 = plt.annotate(s='B', xy=(x[0], x[1]))
annot3 = plt.annotate(s='C', xy=(y[0], y[1]))
textEquation = pylab.text(.5, 1.05, str(w[-1]) + " : " + str(x[-1]) + " :: " + str(y[-1]) + " : x")
pylab.savefig(FOLDER + '6/0')
# Clear the circles & txt
for annot in [annot1, annot2, annot3]:
annot.remove()
textEquation.remove()
# IMAGE 6 #
if(cl != None):
plt.scatter(new[0], new[1], c=cl, s=POINTS_SIZE, linewidths=0)
else:
pylab.text(.095, 1.05, "Aucune equation analogique n'a pu être résolue")
pylab.savefig(FOLDER + '7/0')
def pb_draw(new, points, c, couples, classe, plt=plt):
FOLDER = os.path.join(settings.BASE_DIR, 'static/img/pairBased/')
NB_COUPLES_DISPLAYED = 4
removeFiles(FOLDER) # remove previous files
# IMAGE 1 #
_reset(plt, points, c)
pylab.savefig(FOLDER + '0/' + '0')
# IMAGE 2 #
plt.scatter(new[0], new[1], c="#000000", s=POINTS_SIZE, linewidths=0)
pylab.savefig(FOLDER + '1/' + '0')
# IMAGE 3 #
plt.plot([new[0], c[0][0]], [new[1], c[0][1]], c="#878787", alpha=.3)
pylab.text(0.5, 1.05, 'Nearest neighbor, dist='+str(round(c[1], 4)), fontsize=12)
pylab.savefig(FOLDER + '2/' + '0')
# IMAGE 4 #
# Clear and redraw the points, axes, ...
plt.clf()
_reset(plt, points, c)
plt.scatter(new[0], new[1], c="#000000", s=POINTS_SIZE, linewidths=0)
# Select random couples to display
displayedCouples = [choice(couples) for i in range(NB_COUPLES_DISPLAYED)]
for c in [choice(couples) for i in range(NB_COUPLES_DISPLAYED)]:
plt.plot([c[0][0], c[1][0]], [c[0][1], c[1][1]], c="#878787", alpha=.3) # Draw the line between the two points
midx, midy = (c[0][0] + c[1][0]) / 2, (c[0][1] + c[1][1]) / 2 # Where the text is placed
annot = plt.annotate(str(round(c[2], 3)), xy=(midx, midy), xytext=(-15,15),
textcoords='offset points', ha='center', va='bottom',
arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0.5'))
# pylab.text(midx, midy, str(round(c[2], 3))) # Display the distance between the two points
pylab.savefig(FOLDER + '3/' + '0')
annot.remove()
# IMAGE 5 #
if(classe is None):
print("Can't classify")
print("Solving analogical equation, first solved => class given to the new point")
# Clear and redraw the points, axes, ...
plt.clf()
_reset(plt, points, c)
plt.scatter(new[0], new[1], c="#000000", s=POINTS_SIZE, linewidths=0)
# pylab.text(0.5, 1.05, 'Couples creation + distance computation', fontsize=12)
for i, closest in enumerate(couples):
# Circles to highlight the current points of the equation
w, x, y = closest[0], closest[1], c[0]
annot1 = plt.annotate(s='A', xy=(w[0], w[1]))
annot2 = plt.annotate(s='B', xy=(x[0], x[1]))
annot3 = plt.annotate(s='C', xy=(y[0], y[1]))
textEquation = pylab.text(.5, 1.05, str(w[-1]) + " : " + str(x[-1]) + " :: " + str(y[-1]) + " : x")
pylab.savefig(FOLDER + '4/' + str(i))
# Clear the circles & txt
for annot in [annot1, annot2, annot3]:
annot.remove()
textEquation.remove()
# IMAGE 6 #
_reset(plt, points, c)
plt.scatter(new[0], new[1], c=classe, s=POINTS_SIZE, linewidths=0)
pylab.savefig(FOLDER + '5/0')
