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()