def draw():
lineList = SimulatedAnnealingTSP.lineList
linecollections = collections.LineCollection(lineList)
fig = plt.gcf()
fig.clf()
fig.patch.set_facecolor("w")
DPI = fig.get_dpi()
fig.set_size_inches(800.0 / float(DPI), 600.0 / float(DPI))
plt.axis('off')
ax = fig.add_subplot(111)
ax.add_collection(linecollections, autolim=True)
for x in SimulatedAnnealingTSP.pointList:
ax.scatter(x[0], x[1], s=10, c="#ff0000", alpha=0.8)
totalLength = SimulatedAnnealingTSP.getTotalLength()
desp_patch = mpatches.Patch(
color='red',
label="temperature:%f,length=%f" %
(SimulatedAnnealingTSP.temperature, totalLength))
# draw_Barnsley(ax)
ax.legend(handles=[desp_patch])
ax.axis("equal")
ax.set_axis_off()
ax.set_xlim(ax.dataLim.xmin, ax.dataLim.xmax)
ax.invert_yaxis()
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.get_renderer()._renderer)
fig.clf()
def draw():
lineList = []
lineList.append(((10, 20), (110, 20)))
lineList.append(((10, 40), (110, 40)))
lineList.append(((10, 60), (110, 60)))
lineList.append(((10, 80), (110, 80)))
lineList.append(((10, 100), (110, 100)))
lineList.append(((10, 120), (110, 120)))
lineList.append(((10, 140), (110, 140)))
lineList.append(((10, 160), (110, 160)))
lineList.append(((10, 180), (110, 180)))
lineList.append(((10, 200), (110, 200)))
linecollections = collections.LineCollection(lineList)
fig = plt.gcf()
fig.clf()
fig.patch.set_facecolor("w")
DPI = fig.get_dpi()
fig.set_size_inches(800.0 / float(DPI), 600.0 / float(DPI))
plt.axis('off')
ax = fig.add_subplot(111)
ax.add_collection(linecollections, autolim=True)
ypos = 20
for x in Pendulum.posList:
xpos = 60 + x
ax.scatter(xpos, ypos, s=700, c=nm.random.rand(), alpha=0.5)
ypos += 20
ax.axis("equal")
ax.set_axis_off()
ax.set_xlim(ax.dataLim.xmin, ax.dataLim.xmax)
ax.invert_yaxis()
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.get_renderer()._renderer)
fig.clf()
def draw():
fig = plt.gcf()
fig.clf()
fig.patch.set_facecolor("w")
DPI = fig.get_dpi()
fig.set_size_inches(700.0 / float(DPI), 600.0 / float(DPI))
plt.axis('off')
ax = fig.add_subplot(121)
ax.scatter(100, BouncingBall.pos + 3, s=700, c='#0000ff', alpha=0.8)
ax2 = fig.add_subplot(122)
if BouncingBall.drawParam == 'x':
ax2.set_ylim(-10, 70)
ax2.plot(BouncingBall.timeList, BouncingBall.posList)
ax2.set_xlabel("t(s)")
ax2.set_ylabel("pos(m)")
else:
ax2.plot(BouncingBall.timeList, BouncingBall.vList)
ax2.set_xlabel("t(s)")
ax2.set_ylabel("v(m/s)")
ax2.set_xlim(ax2.dataLim.xmin, ax2.dataLim.xmax)
ax.axis("equal")
#ax.set_axis_off()
ax.set_xlim(ax.dataLim.xmin, ax.dataLim.xmax)
ax.set_ylim(0, 80)
#ax.invert_yaxis()
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.get_renderer()._renderer)
fig.clf()
def drawFibu():
r = nm.arange(2.501, 3.8, 0.001)
s = nm.random.random_sample(r.shape)
x = ChaosModel.calc_stable_x(s, r)
points = []
for i in range(len(x)):
for j in range(len(x[i])):
points.append((r[j], x[i][j]))
(x1, y1) = zip(*points)
fig = plt.gcf()
plt.clf()
plt.axis('off')
DPI = fig.get_dpi()
fig.set_size_inches(1200.0 / float(DPI), 800.0 / float(DPI))
#fig = plt.figure()
plt.scatter(x1, y1, marker='.', lw=0, color="r", s=1)
#print dir(fig.canvas.get_renderer())
#print fig.canvas.get_renderer()
#print fig.canvas.get_renderer().height
#print dir(fig._cachedRenderer)
#print fig.canvas.get_renderer().get_content_extents()
#print fig.canvas.get_renderer()
#print fig.canvas.renderer._renderer
#fig.savefig('fibu.png', dpi=fig.dpi)
plt.axis('on')
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.renderer._renderer)
fig.clf()
def draw():
fig = plt.gcf()
#SIZE = lena.shape[0]
#注意:此参数会极大影响计算过程的内存消耗，对于小内存机器可以会让计算进程因内存不够而出错，请自行调节计算
#x_min, x_max = -2.5, 1
#y_min, y_max = -1.2, 1.2
#x,y = nm.meshgrid(nm.linspace(x_min,x_max,2*Julia.SIZE),nm.linspace(y_min,y_max,Julia.SIZE));
#c = x + 1j*y
#z = c.copy()
#fractal = nm.zeros(z.shape,dtype=nm.uint8)+Julia.MAX_COLOR
#for n in range(Julia.ITERATIONS):
# mask = nm.abs(z) <=10
# z[mask] = z[mask]**2+c[mask]
# fractal[(fractal==Julia.MAX_COLOR) & (~mask)] = (Julia.MAX_COLOR-1)*n/ITERATIONS
# Display the fractal
DPI = fig.get_dpi()
fig.set_size_inches(1500.0 / float(DPI), 800.0 / float(DPI))
#print Julia.fractal
im = plt.imshow(Julia.fractal, cmap=plt.get_cmap('flag'))
#plt.title('Mandelbrot')
plt.axis('off')
im.figure.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(
im.figure.canvas.get_renderer()._renderer)
fig.clf()
def Buffon_draw(data):
fig = pl.gcf()
fig.patch.set_facecolor("w")
DPI = fig.get_dpi()
fig.set_size_inches(1200.0 / float(DPI), 800.0 / float(DPI))
#for i in xrange(6):
# ax = fig.add_subplot(241+i)
# draw(ax, rules[i])
#ax = fig.add_subplot(247)
#draw_Barnsley(ax)
#fig.add_subplot(247)
pl.axis('off')
ax = fig.add_subplot(121)
draw(ax)
ax2 = fig.add_subplot(122)
ax2.plot(Buffon.numNeedleList, Buffon.piEstimationValList)
ax2.set_axis_on()
desp_patch = mpatches.Patch(
color='red',
label="n needls:%d,pi=%f" %
(Buffon.numNeedle, Buffon.piEstimationValList[-1]))
#draw_Barnsley(ax)
ax2.legend(handles=[desp_patch])
fig.subplots_adjust(left=0, right=1, bottom=0, top=1, wspace=0, hspace=0)
#pl.show()
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.get_renderer()._renderer)
fig.clf()
def draw():
fig = plt.gcf()
fig.clf()
fig.patch.set_facecolor("w")
DPI = fig.get_dpi()
fig.set_size_inches(800.0/float(DPI),600.0/float(DPI))
#plt.axis('off')
ax = fig.add_subplot(111)
a, b, m, n = 1, 0.8, 1, 0.5
X, Y = meshgrid(arange(-0.1, 4, .3), arange(-0.1, 4, .3))
U = a * X - b * X * Y
V = -m * Y + n * X * Y
Q = ax.quiver(U, V)
l, r, b, t = axis()
dx, dy = r - l, t - b
ax.scatter(PredatorPrey.x, PredatorPrey.y, s=10, c="#ff0000", alpha=0.8)
desp_patch = mpatches.Patch(color='red',
label="x:%f,y=%f" % (PredatorPrey.x,PredatorPrey.y))
# draw_Barnsley(ax)
ax.legend(handles=[desp_patch])
ax.axis("equal")
#ax.set_axis_off()
ax.set_xlim(ax.dataLim.xmin, ax.dataLim.xmax)
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.get_renderer()._renderer)
fig.clf()
def LSystem_draw_Barnsley(data):
params = data['params']
paramsMatrix = numpy.asarray(params)
slim = data['slim']
fig = pl.gcf()
fig.patch.set_facecolor("w")
DPI = fig.get_dpi()
if slim:
fig.set_size_inches(300.0 / float(DPI), 600.0 / float(DPI))
else:
fig.set_size_inches(1000.0/float(DPI),600.0/float(DPI))
#for i in xrange(6):
# ax = fig.add_subplot(241+i)
# draw(ax, rules[i])
#ax = fig.add_subplot(247)
#draw_Barnsley(ax)
#fig.add_subplot(247)
pl.axis('off')
ax = fig.add_subplot(111)
#draw(ax,rules[rule])
draw_Barnsley(ax,paramsMatrix)
fig.subplots_adjust(left=0,right=1,bottom=0,top=1,wspace=0,hspace=0)
#pl.show()
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.get_renderer()._renderer)
fig.clf()
def draw():
lineList = GeneticTSP.lineList
linecollections = collections.LineCollection(lineList)
fig = plt.gcf()
fig.clf()
fig.patch.set_facecolor("w")
gs = gridspec.GridSpec(1, 2, width_ratios=[2, 4])
DPI = fig.get_dpi()
fig.set_size_inches(GeneticTSP.width / float(DPI),
GeneticTSP.height / float(DPI))
plt.axis('off')
plt.tight_layout(pad=0)
#ax = fig.add_subplot(111)
ax1 = plt.subplot(gs[0])
top5AgentList = []
for i in range(5):
citySeq = GeneticTSP.agentList[i].citySequence
citySeqFix = []
zeroIndex = citySeq.index(0)
for _ in range(GeneticTSP.numPoints):
citySeqFix.append(citySeq[zeroIndex])
zeroIndex = (zeroIndex + 1) % GeneticTSP.numPoints
top5AgentList.append(citySeqFix)
top5AgentArray = nm.array(top5AgentList)
top5AgentArray = nm.transpose(top5AgentArray)
table = ax1.table(cellText=top5AgentArray,
cellLoc='center',
bbox=[0, 0, 1, 1])
table.set_fontsize(18)
if GeneticTSP.top5AgentArray is None:
GeneticTSP.top5AgentArray = top5AgentArray
else:
for key, c in table.get_celld().iteritems():
if GeneticTSP.top5AgentArray[key] != top5AgentArray[key]:
c.set(facecolor='#00ff00')
if key[0] == 0:
c.set(facecolor='#ff0000')
GeneticTSP.top5AgentArray = top5AgentArray
ax1.set_axis_off()
ax = plt.subplot(gs[1])
ax.add_collection(linecollections, autolim=True)
for x in GeneticTSP.pointList:
ax.scatter(x[0], x[1], s=10, c="#ff0000", alpha=0.8)
totalLength = GeneticTSP.getTotalLength()
desp_patch = mpatches.Patch(color='red',
label="generation:%d,length=%f" %
(GeneticTSP.generation, totalLength))
# draw_Barnsley(ax)
ax.legend(handles=[desp_patch])
ax.axis("equal")
ax.set_axis_off()
ax.set_xlim(ax.dataLim.xmin, ax.dataLim.xmax)
ax.invert_yaxis()
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.get_renderer()._renderer)
fig.clf()
def drawLogisticPopulationModel(r, x1start, x2start, iter_count, lines=1):
def calculate_trajectory(seed, r, count):
result = []
x = seed
f = lambda r, x: r * x * (1 - x)
for i in range(0, count):
x = f(r, x)
result.append(x)
return result
if lines == 1:
x = range(0, iter_count)
y1 = calculate_trajectory(0.2, r, iter_count)
fig = plt.gcf()
fig.set_size_inches(18.5, 10.5)
labelText = "seed=" + str(x1start) + ",r=" + str(
r) + ",steps=" + str(iter_count)
plot1 = plt.plot(x, y1, color="r", label=labelText)
plt.xlabel("steps")
plt.ylabel("iterated value")
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(
fig.canvas.get_renderer()._renderer)
fig.clf()
elif lines == 2:
x = range(0, iter_count)
y1 = calculate_trajectory(x1start, r, iter_count)
y2 = calculate_trajectory(x2start, r, iter_count)
fig = plt.gcf()
fig.set_size_inches(18.5, 10.5)
label1Text = "seed=" + str(x1start) + ",r=" + str(
r) + ",steps=" + str(iter_count)
label2Text = "seed=" + str(x2start) + ",r=" + str(
r) + ",steps=" + str(iter_count)
plot1 = plt.plot(x, y1, color="r", label=label1Text)
plot2 = plt.plot(x, y2, color="b", label=label2Text)
plt.xlabel("steps")
plt.ylabel("iterated value")
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(
fig.canvas.get_renderer()._renderer)
fig.clf()
else:
print 'illegal param'
def draw():
fig = plt.gcf()
fig.clf()
griddata = 1-GameOfLife.gridData
plt.grid(which='none', axis='none', linestyle='-', color='r')
im = plt.imshow(griddata, cmap=plt.cm.gray, interpolation='nearest',vmin=0,vmax=1)
#matplotlib.pyplot.axis('off')
DPI = fig.get_dpi()
fig.set_size_inches(1000.0 / float(DPI), 468.0 / float(DPI))
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(im.figure.canvas.get_renderer()._renderer)
fig.clf()
def draw():
fig = plt.gcf()
fig.clf()
fig.subplots_adjust(top=0.8, bottom=0.05, left=0.01, right=0.99)
gs = gridspec.GridSpec(1, 2, width_ratios=[4, 1])
x = nm.arange(0, 10, 0.2)
y = nm.sin(x)
ax0 = plt.subplot(gs[0])
ax1 = plt.subplot(gs[1])
griddata = SpatialGame.gridData
print griddata[(0, 0)]
plt.grid(which='none', axis='none', linestyle='-', color='r')
im = ax0.imshow(griddata,
cmap=plt.cm.get_cmap('indexed'),
interpolation="nearest",
vmin=0,
vmax=4)
ax1.scatter(20, 20, s=700, c='#0000ff', alpha=1.0)
ax1.annotate('CC',
xy=(20, 20),
xycoords='data',
xytext=(20, 20),
textcoords='offset points',
arrowprops=dict(arrowstyle="->"))
ax1.scatter(20, 40, s=700, c='#ff0000', alpha=1.0)
ax1.annotate('DD',
xy=(20, 40),
xycoords='data',
xytext=(20, 40),
textcoords='offset points',
arrowprops=dict(arrowstyle="->"))
ax1.scatter(20, 60, s=700, c='#00ff00', alpha=1.0)
ax1.annotate('DC',
xy=(20, 60),
xycoords='data',
xytext=(20, 60),
textcoords='offset points',
arrowprops=dict(arrowstyle="->"))
ax1.scatter(20, 80, s=700, c='#ffff00', alpha=1.0)
ax1.annotate('CD',
xy=(20, 80),
xycoords='data',
xytext=(20, 80),
textcoords='offset points',
arrowprops=dict(arrowstyle="->"))
matplotlib.pyplot.axis('off')
DPI = fig.get_dpi()
fig.set_size_inches(1200.0 / float(DPI), 1000.0 / float(DPI))
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(
im.figure.canvas.get_renderer()._renderer)
fig.clf()
def draw(self):
# set point-of-view: specified by (altitude degrees, azimuth degrees)
self.ax.view_init(30, 0.3 * self.steps)
for line, pt, xi in zip(self.lines, self.pts, self.x_t):
x, y, z = xi[:self.steps].T
line.set_data(x, y)
line.set_3d_properties(z)
pt.set_data(x[-1:], y[-1:])
pt.set_3d_properties(z[-1:])
self.fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(self.fig.canvas.get_renderer()._renderer)
def LSystem_draw_Barnsley(data):
rule = data['rule']
fig = pl.gcf()
fig.patch.set_facecolor("w")
DPI = fig.get_dpi()
fig.set_size_inches(1200.0 / float(DPI), 800.0 / float(DPI))
#for i in xrange(6):
# ax = fig.add_subplot(241+i)
# draw(ax, rules[i])
#ax = fig.add_subplot(247)
#draw_Barnsley(ax)
#fig.add_subplot(247)
pl.axis('off')
ax = fig.add_subplot(111)
draw(ax, rules[rule])
#draw_Barnsley(ax)
fig.subplots_adjust(left=0, right=1, bottom=0, top=1, wspace=0, hspace=0)
#pl.show()
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.get_renderer()._renderer)
fig.clf()
def draw(self):
# Set up figure & 3D axis for animation
self.fig = plt.gcf()
self.fig.patch.set_facecolor("w")
DPI = self.fig.get_dpi()
self.fig.set_size_inches(1200.0 / float(DPI), 1200.0 / float(DPI))
self.ax = self.fig.add_axes([0, 0, 1, 1], projection='3d')
self.ax.axis('off')
self.ax.axis("equal")
self.ax.set_axis_off()
# choose a different color for each trajectory
self.colors = plt.cm.jet(np.linspace(0, 1, self.N_trajectories))
# set up lines and points
self.lines = sum(
[self.ax.plot([], [], [], '-', c=c) for c in self.colors], [])
self.pts = sum(
[self.ax.plot([], [], [], 'o', c=c) for c in self.colors], [])
# prepare the axes limits
self.ax.set_xlim((-30, 30))
self.ax.set_ylim((-35, 35))
self.ax.set_zlim((0, 60))
# set point-of-view: specified by (altitude degrees, azimuth degrees)
self.ax.view_init(30, 0.3 * self.steps)
for line, pt, xi in zip(self.lines, self.pts, self.x_t):
x, y, z = xi[:self.steps].T
line.set_data(x, y)
line.set_3d_properties(z)
pt.set_data(x[-1:], y[-1:])
pt.set_3d_properties(z[-1:])
self.fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(
self.fig.canvas.get_renderer()._renderer)
self.fig.clf()
def draw():
lineList = AntColonyTSP.lineList
linecollections = collections.LineCollection(lineList,
linewidths=1,
colors="#FF0000")
fig = plt.gcf()
fig.clf()
fig.patch.set_facecolor("w")
DPI = fig.get_dpi()
fig.set_size_inches(AntColonyTSP.width / float(DPI),
AntColonyTSP.height / float(DPI))
plt.axis('off')
plt.tight_layout(pad=0)
ax = fig.add_subplot(111)
#pheromoneList = AntColonyTSP.getPheromoneDensityLineList()
res = AntColonyTSP.getPheromoneDensityLineList()
p_lineList = res['lineList']
p_colorList = res['colorList']
#for l in pheromoneList:
# ax.add_line(l)
p_collection = collections.LineCollection(p_lineList,
colors=p_colorList)
ax.add_collection(p_collection, autolim=True)
ax.add_collection(linecollections, autolim=True)
for x in AntColonyTSP.pointList:
ax.scatter(x[0], x[1], s=30, c="#FF00FF", alpha=1.0)
totalLength = AntColonyTSP.getTotalLength()
desp_patch = mpatches.Patch(color='red',
label="length=%f" % (totalLength))
# draw_Barnsley(ax)
ax.legend(handles=[desp_patch])
ax.axis("equal")
ax.set_axis_off()
ax.set_xlim(ax.dataLim.xmin, ax.dataLim.xmax)
ax.invert_yaxis()
fig.canvas.draw()
_pybridge.PyRendererAggBufferRGBA(fig.canvas.get_renderer()._renderer)
fig.clf()
