Python Drawing Animation Sample __python

Suit, first look at the Python matpotlib official website http://matplotlib.org/examples/index.html on the completion of what the example, after all, their own research API too time-consuming

1,

Import NumPy as NP
import Matplotlib.pyplot as Plt
import matplotlib.animation as animation


def Data_gen (t=0 ):
    cnt = 0
    while CNT < 1000:
        cnt = 1
        t + + 0.1
        yield T, Np.sin (2*np.pi*t) * NP.EXP (-T/10.)


DEF init ():
    Ax.set_ylim ( -1.1, 1.1)
    Ax.set_xlim (0,)
    del xdata[:]
    del ydata[:]
    line.set_ Data (XData, Ydata) return line
    ,

fig, ax = plt.subplots () line
, = Ax.plot ([], [], lw=2)
Ax.grid () C18/>xdata, Ydata = [], []


def Run (data):
    # Update the data
    t, y = data
    xdata.append (t)
    Ydata.ap Pend (y)
    xmin, xmax = Ax.get_xlim ()

    if T >= xmax:
        ax.set_xlim (xmin, 2*xmax)
        Ax.figure.canvas.draw ()
    line.set_data (XData, Ydata) return line

    ,

ani = animation. Funcanimation (Fig, run, Data_gen, Blit=false, interval=10,
                              repeat=false, Init_func=init)
plt.show ()

2,

Import NumPy as NP
import Matplotlib.pyplot as Plt
import matplotlib.animation as animation

fig = plt.figure (


def f (x, y): Return
    np.sin (x) + Np.cos (y)

x = Np.linspace (0, 2 * np.pi,)
y = np.linspace (0, 2 * np.p Reshape ( -1, 1)

im = Plt.imshow (f (x, y), animated=true)


def updatefig (*args):
    global x, y
    x + + NP . Pi/15.
    Y + + np.pi/20.
    Im.set_array (f (x, y)) return
    IM,

ani = animation. Funcanimation (Fig, Updatefig, interval=50, blit=true)
plt.show ()

3,

Import NumPy as NP import Matplotlib.pyplot as PLT import matplotlib.animation as animation def update_line (num, data, L INE): Line.set_data (data[.,: num]) return line, FIG1 = plt.figure () data = Np.random.rand (2,) l, = Plt.plot ([], [], ' R ') Plt.xlim (0, 1) plt.ylim (0, 1) plt.xlabel (' x ') plt.title (' test ') Line_ani = animation. Funcanimation (FIG1, Update_line, fargs= (data, L), interval=50, Blit=true) # to Sav  E The animation, use the Command:line_ani.save (' lines.mp4 ') Fig2 = Plt.figure () x = Np.arange ( -9,) y = Np.arange (-9, Reshape ( -1, 1) base = Np.hypot (x, y) IMS = [] for add in Np.arange: Ims.append (Plt.pcolor (x, Y, base + Add, Norm=plt. Normalize (0)) Im_ani = animation. Artistanimation (FIG2, IMS, INTERVAL=50, repeat_delay=3000, Blit=true) # to save this SE Cond animation with some metadata, use the following command: # im_ani.save (' Im.mp4 ', metadata={' artist ': ' Guido '}) PLT.show () 

4,

Import NumPy as NP import Matplotlib.pyplot as PLT import matplotlib.patches as patches import Matplotlib.path as Path IM Port matplotlib.animation as animation fig, ax = plt.subplots () # Histogram our data with numpy data = NP.RANDOM.RANDN (1 N, bins = np.histogram (data, M) # Get the corners of the rectangles for the histogram left = Np.array (Bins[:-1]) r ight = Np.array (bins[1:]) bottom = Np.zeros (len) top = bottom + N nrects = Len (left) # This comes the tricky part- -We have to set up the vertex and path # codes arrays using MoveTo, LineTo and Closepoly To, 3 for the LINETO, 1 for the # closepoly; The vert for the Closepoly are ignored but we still need # it to keep the codes aligned with the vertices = nverts ( 1 + 3 + 1) verts = Np.zeros ((nverts, 2)) codes = Np.ones (nverts, int) * path. Path.lineto Codes[0::5] = path. Path.moveto Codes[4::5] = path. Path.closepoly verts[0::5, 0] = left verts[0::5, 1] = bottom Verts[1::5, 0] = left VErts[1::5, 1] = top Verts[2::5, 0] = right verts[2::5, 1] = top Verts[3::5, 0] = right verts[3::5, 1] = bottom Barpath = Path. Path (verts, codes) Patch = patches. Pathpatch (Barpath, facecolor= ' green ', edgecolor= ' yellow ', alpha=0.5) ax.add_patch (patch) Ax.set_xlim (left[0), right[ -1]) Ax.set_ylim (Bottom.min (), Top.max ()) def animate (i): # Simulate new data coming in data = NP.RANDOM.RANDN (1 N, bins = np.histogram (data,) top = bottom + N verts[1::5, 1] = top Verts[2::5, 1] = top Retu RN [Patch,] ani = animation. Funcanimation (Fig, animate, Repeat=false, Blit=true) plt.show ()

5, the animation to save video files, first installed sudo apt-get install FFmpeg

Import NumPy as NP import matplotlib matplotlib.use ("Agg") import Matplotlib.pyplot as PLT import matplotlib.animation as  Animation def update_line (num, data, line): Line.set_data (data[..., num]) return line, # Set up formatting for


The movie files Writer = animation.writers[' ffmpeg '] Writer = Writer (fps=15, metadata=dict (artist= ' Me '), bitrate=1800) FIG1 = plt.figure () data = Np.random.rand (2) L, = Plt.plot ([], [], ' R ') Plt.xlim (0, 1) plt.ylim (0, 1) plt.xlabel (' x ' ) plt.title (' test ') Line_ani = animation. Funcanimation (FIG1, Update_line, fargs= (data, L), interval=50, blit=true) ffwriter = Animation. Ffmpegwriter () line_ani.save (' Basic_animation.mp4 ', writer = Ffwriter, fps=30, extra_args=['-vcodec ', ' libx264 ']) # 
Line_ani.save (' Lines.mp4 ', writer=writer) Fig2 = Plt.figure () x = Np.arange ( -9,) y = Np.arange ( -9, ten). Reshape (-1, 1) Base = Np.hypot (x, y) IMS = [] for add in Np.arange: Ims.append (Plt.pcolor (x, y, base + adD, Norm=plt. Normalize (0)) Im_ani = animation. Artistanimation (FIG2, IMS, INTERVAL=50, repeat_delay=3000, Blit=true) #im_ani. Save (' im.
 MP4 ', Writer=writer)