我们从Python开源项目中，提取了以下11个代码示例，用于说明如何使用matplotlib.animation.FFMpegWriter()。
def animate(self, compute_step, iterations, train_data_update_freq=20, test_data_update_freq=100, one_test_at_start=True, more_tests_at_start=False, save_movie=False): def animate_step(i): if (i == iterations // train_data_update_freq): #last iteration compute_step(iterations, True, True) else: for k in range(train_data_update_freq): n = i * train_data_update_freq + k request_data_update = (n % train_data_update_freq == 0) request_test_data_update = (n % test_data_update_freq == 0) and (n > 0 or one_test_at_start) if more_tests_at_start and n < test_data_update_freq: request_test_data_update = request_data_update compute_step(n, request_test_data_update, request_data_update) # makes the UI a little more responsive plt.pause(0.001) if not self.is_paused(): return self._mpl_update_func() self._animation = animation.FuncAnimation(self._mpl_figure, animate_step, int(iterations // train_data_update_freq + 1), init_func=self._mlp_init_func, interval=16, repeat=False, blit=False) if save_movie: mywriter = animation.FFMpegWriter(fps=24, codec='libx264', extra_args=['-pix_fmt', 'yuv420p', '-profile:v', 'high', '-tune', 'animation', '-crf', '18']) self._animation.save("./tensorflowvisu_video.mp4", writer=mywriter) else: plt.show(block=True)
def __init__(self, var_xarray, Nsteps, vmin, vmax, animationname): # Global definitions self.var = var_xarray self.Nsteps = Nsteps self.vmin = vmin self.vmax = vmax # Figure and axes self.fig = plt.figure() # self.ax = self.fig.axes() # Animation definitio anim = animation.FuncAnimation(self.fig, self.update, xrange(Nsteps), interval=1, blit=False) # Writer FFMpeg needed for mp4 film mywriter = animation.FFMpegWriter(bitrate=500) anim.save(animationname, writer=mywriter, fps=1, extra_args=['-vcodec', 'libx264'], dpi=300) # No init_plot needed
def train(self, training_agent, total_episode, save_movie=False): def animate_func(step): #self.step = step if step > total_episode: print("Finish training ") #plt.close() else: training_agent(episode=step, visual=self) plt.pause(1.001) # makes the UI a little more responsive if not self.ispause: return self._update() self.am = animation.FuncAnimation(self._fig, animate_func, total_episode, init_func=self._init, interval=16, repeat=False, blit=False) if save_movie: mywriter = animation.FFMpegWriter(fps=24, codec='libx264', extra_args=['-pix_fmt', 'yuv420p', '-profile:v', 'high', '-tune', 'animation', '-crf', '18']) self.am.save("./video.mp4", writer=mywriter) else: plt.show(block=True)
def plot_anim(self, movesets, **kwargs): pass # DOESNT WORK SINE THE LENGTH OF A MOVESET IS VARIABLE # setup = self.plot_moveset(movesets[0], show=False, export=True, export_plots=True, plot=True) # fig = setup['fig'] # ax = setup['ax'] # plots = setup['plots'] # # def update(i): # label = 'Generation {}'.format(i) # path, bumps = self.plot_moveset(movesets[i], export_data=True) # path_xs, path_ys = Labyrinth._transform_array_into_xy(path) # bumps_xs, bumps_ys = Labyrinth._transform_array_into_xy(bumps) # # plots[0].set_offsets(bumps_xs, bumps_ys) # # plots[1].set_offsets(path[0]) # # plots[2].set_offsets((path_xs[-1], path_ys[-1])) # for i, j in enumerate(range(len(path)-2, -1, -1), 3): # plots[i].set_positions([path_xs[i], path_ys[i]], [path_xs[i + 1], path_ys[i + 1]]) # # plots[len(plots)-1] # return plots # # mywriter = animation.FFMpegWriter() # ani = animation.FuncAnimation(fig, update, frames=np.arange(0, len(movesets)), interval=200) # ani.save('asd.mp4', writer=mywriter)
def writevideo(self): #print animation.writers.list() #matplotlib.rcParams['animation.ffmpeg_args'] = ['-report', '/tmp/ffmpeg.log'] #FFMpegWriter = animation.writers['ffmpeg'] metadata = dict(title='Github Data Projects', artist='0x0FFF', comment='Evolution of open source data projects') writer = FFMpegWriter(fps=30, bitrate=8000, metadata=metadata ) i = 0 #self.iters = 200 with writer.saving(self.fig, "/projects/personal/writer_test.mp4", 120): while i < self.iters: self.update_animation(i) writer.grab_frame() i += 1 return
def visualize(self, num=100, save=False): """ Visualizes given Sorting Algorithm :param num: Number of points that has to be chosen for visualization :param save: Boolean indicating whether to save animation in 'output' directory """ plt.title(self.sorter.name + " Visualization") plt.xlabel("Array Index") plt.ylabel("Element") data = np.arange(num) ran.shuffle(data) self.sorter.sort(data, visualization=True) self.hist_arr = self.sorter.hist_array self.scatter = plt.scatter(np.arange(self.hist_arr.shape[1]), self.hist_arr[0]) # plt.scatter(x-array,y-array) self.animation = animation.FuncAnimation(self.fig, self.__update, frames=self.hist_arr.shape[0], repeat=False, blit=False, interval=1) if save: import os import errno path = "output" try: os.makedirs(path) except OSError as exc: if exc.errno == errno.EEXIST and os.path.isdir(path): pass else: raise path = os.path.join('output', self.sorter.name + ".mp4") p1 = Process( target=lambda: self.animation.save(path, writer=animation.FFMpegWriter(fps=100))) p1.start() plt.show()
def __init__(self, var_xarray, Nsteps, vmin, vmax, animationname): # Global definitions self.var = var_xarray self.Nsteps = Nsteps self.vmin = vmin self.vmax = vmax # Figure and axes self.fig = plt.figure(figsize=(8,3)) self.ax=plt.axes(projection=ccrs.PlateCarree()) self.ax.set_extent([-90, 15, 25, 70],ccrs.PlateCarree()) self.plt_hdl = self.var[0, ...].plot.pcolormesh('nav_lon','nav_lat',ax=self.ax, vmin=self.vmin, vmax=self.vmax, transform=ccrs.PlateCarree()) plt.title(self.var[0, ...].coords['time_centered'].values, size=10) # to modify the title #self.ax.title.set_size(10) lon_tcks = range(-80,20,20) lat_tcks = range(30,70,10) self.ax.set_xticks(lon_tcks, crs=ccrs.PlateCarree()) self.ax.set_yticks(lat_tcks, crs=ccrs.PlateCarree()) self.ax.coastlines(resolution='50m') # Currently can be one of “110m”, “50m”, and “10m” self.ax.gridlines() # Animation definitio anim = animation.FuncAnimation(self.fig, self.update, xrange(Nsteps), interval=1, blit=False) # Writer FFMpeg needed for mp4 film mywriter = animation.FFMpegWriter(bitrate=500) anim.save(animationname, writer=mywriter, fps=1, extra_args=['-vcodec', 'libx264'], dpi=300) #anim.save(animationname, writer=mywriter, fps=1, extra_args=['-vcodec', 'libx264']) # No init_plot needed
def dfAnimate( df, movieName = None, nShaddow = 0, xRatio= 1.0, rate = 1 , xlim = None , ylim = None , xlabel = "x(m)" , ylabel = "Elevation(m)") : """ Animate a dataFrame where time is the index, and columns are the "spatial" position """ from matplotlib import animation print ("Making animation file : " , movieName) global pause pause = False def onClick(event): global pause pause ^= True nShaddow = max(1,nShaddow) fig, ax = plt.subplots() fig.canvas.mpl_connect('button_press_event', onClick ) ls = [] for i in range(nShaddow) : if i == 0 : color = "black" else : color = "blue" ltemp, = ax.plot( [], [], lw=1 , alpha = 1-i*1./nShaddow , color = color) ls.append(ltemp) xVal = df.columns ax.grid(True) if xlim : ax.set_xlim( xlim ) else : ax.set_xlim( min(xVal) , max(xVal) ) if ylim : ax.set_ylim( ylim ) else : ax.set_ylim( df.min().min() , df.max().max() ) ax.set_xlabel(xlabel) ax.set_ylabel(ylabel) def run(itime): ax.set_title("{}s".format(df.index[itime*rate]) ) for s in range(nShaddow): if not pause : if itime > s : ls[s].set_data( xVal , df.iloc[ rate*(itime - s) , : ] ) return ls ani = animation.FuncAnimation( fig , run, range(len(df)), blit=True, interval=30, repeat=False) if movieName is None : plt.show() else : mywriter = animation.FFMpegWriter(fps = 25 , codec="libx264") ani.save( movieName +'.mp4' , writer=mywriter)
def makeAnimation(filename , movieName = None, nShaddow = 20, xRatio= 1.0, version = "foamStar" , rate = 1) : """ Make a 2D animation of the wave field. """ print "Making animation file : " , movieName nShaddow = max(1,nShaddow) data = pd.read_csv(filename, comment = "#" , header=None , delim_whitespace=True, dtype = float).as_matrix() if version == "foamStar" : with open(filename , "r") as f : f.readline() ; f.readline() ; xVal = [float(x) for x in f.readline().split()[2:]] #Remove x = 0.0 if 0.0 in xVal : i = xVal.index(0.0) xVal.pop(i) data = np.delete(data, i+1 , axis = 1) xVal = np.array(xVal) xVal /= xRatio else : xVal = np.linspace(0,1 , len(data[1,:]) -1 ) fig, ax = plt.subplots() ls = [] for i in range(nShaddow) : if i == 0 : color = "black" else : color = "blue" ltemp, = ax.plot([], [], lw=1 , alpha = 1-i*1./nShaddow , color = color) ls.append(ltemp) ax.grid(True) ax.set_xlim( min(xVal) , max(xVal) ) ax.set_ylim( -1.5 , +1.5 ) ax.set_xlabel("x") ax.set_ylabel("Elevation(m)") def run(itime): ax.set_title("{}s".format(data[itime*rate,0]) ) for s in range(nShaddow): if itime > s : ls[s].set_data( xVal , data[ rate*(itime - s),1:] ) return ls ani = animation.FuncAnimation( fig , run, range(len(data)), blit=True, interval=30, repeat=False) if movieName is None : plt.show() else : mywriter = animation.FFMpegWriter(fps = 25 , codec="libx264") ani.save( movieName +'.mp4',writer=mywriter)
