matplotlib动画需要大量的时间来运行

Question

我正在使用Animation.funcanimation进行相当简单的matplotlib动画，并且运行时间很长。在11秒长的视频中，每帧约0.81和220帧的180帧。我已经结合了标准的性能改进，即在动画循环中没有创建艺术家对象并返回所有更新的艺术家对象，以便可以完成闪光，但都没有对性能产生重大影响。我已经计时了newFrame函数的内容，并且运行约为0.6ms。我的代码在下面。

还有其他建议如何加快它或并行化？

编辑：看来性能问题与子图主要有关。减少子图的数量会大大减少执行时间。并不是一个很好的解决方案，但值得注意的

编辑2：评论axsArray [a，b] .minorticks_on（）将性能翻倍至〜0.4 s每一帧。这使得性能更符合我基于Matplotlib动画的先前经验的期望，尽管对于简单的情节来说仍然非常慢。

#!/usr/bin/env python3

from timeit import default_timer

import matplotlib
import matplotlib.animation as animation
import matplotlib.pyplot as plt
import numpy as np
import os
import sys

matplotlib.use("Agg")

plt.close('all')
start = default_timer()


# ==============================================================================
def main():
    # ==========================================================================
    # Settings
    # ==========================================================================
    # Check for CLI arguments
    if len(sys.argv) == 2:
        cliFPS = int(sys.argv[1])
    elif len(sys.argv) > 2:
        raise TypeError(f"Too many ({len(sys.argv)}) command line arguments given")

    # Data settings
    loadPath = ''
    yPos     = 16  # y position of the x line to load
    zPos     = 16  # z position of the x line to load

    # Plot Settings
    supTitleText  = "Time Evolution of Initial Conditions"
    densityColor  = 'blue'                      # color of the density plot
    velocityColor = 'purple'                    # color of the velocity plots
    magneticColor = 'tab:orange'                # color of the magnetic field plots
    pressureColor = 'green'                     # color of the pressure plot
    ieColor       = 'red'                       # color of the specific internal energy plot
    linestyle     = '-'                         # The line style
    linewidth     = 0.5                         # How wide to make the lines
    marker        = "."                         # Marker kind for points
    markersize    = 3                           # Size of the marker
    figSizeScale  = 2.                          # Scaling factor for the figure size
    figHeight     = 4.8 * figSizeScale          # height of the plot in inches, default is 4.8
    figWidth      = 7.0 * figSizeScale          # width of the plot in inches, default is 6.4
    padPercent    = 0.05                        # How many percent larger the limits should be than the data

    # Video Settings
    OutFile       = "mvp.mp4"                   # Output filename
    Duration      = 10.                         # How long the video is in seconds
    dpi           = 150                         # Dots per inch
    index         = 0                           # Initialize index
    initIndex     = 0                           # Index for init frames
    fps           = cliFPS if ("cliFPS" in locals()) else 20  # Framerate
    FrameTime     = (1./fps) * 1000             # Frametime in milliseconds
    totFrames     = int(fps * Duration)         # Total number of frames (floor)
    # ==========================================================================
    # End settings
    # ==========================================================================

    # Load data
    (densityData, velocityXData, velocityYData, velocityZData, pressureData,
     ieData, magneticXData, magneticYData, magneticZData, positions,
     timeStepNum, dims, physicalSize) = loadData(loadPath, yPos, zPos)

    # Compute which time steps to plot
    if timeStepNum.size >= totFrames:
        floatSamples    = np.arange(0, timeStepNum.size, timeStepNum.size/totFrames)
        timeStepSamples = np.asarray(np.floor(floatSamples), dtype="int")
    else:  # if the number of simulation steps is less than the total number of frames
        totFrames = timeStepNum.size
        fps       = np.ceil(totFrames/Duration)
        FrameTime = (1./fps) * 1000
        timeStepSamples = np.arange(0, timeStepNum.size, 1, dtype="int")

    # Insert the initial second of the initial conditions
    timeStepSamples = np.insert(timeStepSamples, 0, [0]*fps)

    # Get the plot limits
    densityLowLim, densityHighLim     = computeLimit(densityData, padPercent)
    ieLowLim, ieHighLim               = computeLimit(ieData, padPercent)
    pressureLowLim, pressureHighLim   = computeLimit(pressureData, padPercent)
    velocityXLowLim, velocityXHighLim = computeLimit(velocityXData, padPercent)
    velocityYLowLim, velocityYHighLim = computeLimit(velocityYData, padPercent)
    velocityZLowLim, velocityZHighLim = computeLimit(velocityXData, padPercent)
    magneticXLowLim, magneticXHighLim = computeLimit(magneticXData, padPercent)
    magneticYLowLim, magneticYHighLim = computeLimit(magneticYData, padPercent)
    magneticZLowLim, magneticZHighLim = computeLimit(magneticZData, padPercent)

    # Set up plots
    # Create 9 subplots
    fig, subPlot = plt.subplots(3, 3, figsize = (figWidth, figHeight))

    # Super Title
    titleText = fig.suptitle(supTitleText)

    # Shared x-label
    subPlot[2,0].set_xlabel("Position")
    subPlot[2,1].set_xlabel("Position")
    subPlot[2,2].set_xlabel("Position")

    # Set values for the subplots
    densityPlot,   subPlot = setupSubPlots('Density',         densityLowLim,   densityHighLim,   positions, densityData,   linestyle, linewidth, marker, markersize, densityColor,  subPlot)
    pressurePlot,  subPlot = setupSubPlots('Pressure',        pressureLowLim,  pressureHighLim,  positions, pressureData,  linestyle, linewidth, marker, markersize, pressureColor, subPlot)
    iePlot,        subPlot = setupSubPlots('Internal Energy', ieLowLim,        ieHighLim,        positions, ieData,        linestyle, linewidth, marker, markersize, ieColor,       subPlot)
    velocityXPlot, subPlot = setupSubPlots('$V_x$',           velocityXLowLim, velocityXHighLim, positions, velocityXData, linestyle, linewidth, marker, markersize, velocityColor, subPlot)
    velocityYPlot, subPlot = setupSubPlots('$V_y$',           velocityYLowLim, velocityYHighLim, positions, velocityYData, linestyle, linewidth, marker, markersize, velocityColor, subPlot)
    velocityZPlot, subPlot = setupSubPlots('$V_z$',           velocityZLowLim, velocityZHighLim, positions, velocityZData, linestyle, linewidth, marker, markersize, velocityColor, subPlot)
    magneticXPlot, subPlot = setupSubPlots('$B_x$',           magneticXLowLim, magneticXHighLim, positions, magneticXData, linestyle, linewidth, marker, markersize, magneticColor, subPlot)
    magneticYPlot, subPlot = setupSubPlots('$B_y$',           magneticYLowLim, magneticZHighLim, positions, magneticYData, linestyle, linewidth, marker, markersize, magneticColor, subPlot)
    magneticZPlot, subPlot = setupSubPlots('$B_z$',           magneticZLowLim, magneticZHighLim, positions, magneticZData, linestyle, linewidth, marker, markersize, magneticColor, subPlot)

    # Layout
    plt.tight_layout()
    fig.subplots_adjust(top=0.88)

    # Generate animation
    simulation = animation.FuncAnimation(fig,
                                         newFrame,
                                         fargs = (fig, supTitleText, densityPlot, pressurePlot, iePlot,
                                                  velocityXPlot, velocityYPlot, velocityZPlot,
                                                  magneticXPlot, magneticYPlot, magneticZPlot,
                                                  densityData, pressureData, ieData,
                                                  velocityXData, velocityYData, velocityZData,
                                                  magneticXData, magneticYData, magneticZData,
                                                  timeStepSamples, titleText),
                                         blit = True,
                                         frames = timeStepSamples,
                                         interval = FrameTime,
                                         repeat = False)

    FFwriter = animation.FFMpegWriter(bitrate=1000,
                                      fps=fps,
                                      codec='libx264',
                                      extra_args=['-crf','28','-preset','ultrafast','-pix_fmt','yuv420p'])
    simulation.save(filename=OutFile, writer = FFwriter)
    # simulation.save(filename=OutFile, fps=fps, dpi=dpi)
    print(f"\n\nAnimation complete. Framerate: {fps} fps, Total Number of Frames: {timeStepSamples.size}")
# ==============================================================================

# ==============================================================================
def loadData(path, yPos, zPos):

    numFiles = 870
    dims = [32, 32, 32]
    physicalSize = [1,1,1]

    np.random.random((numFiles, dims[0]))

    # Allocate Arrays
    densityData        = np.random.random((numFiles, dims[0]))
    velocityXData      = np.random.random((numFiles, dims[0]))
    velocityYData      = np.random.random((numFiles, dims[0]))
    velocityZData      = np.random.random((numFiles, dims[0]))
    pressureData       = np.random.random((numFiles, dims[0]))
    ieData             = np.random.random((numFiles, dims[0]))
    magneticXData      = np.random.random((numFiles, dims[0]))
    magneticYData      = np.random.random((numFiles, dims[0]))
    magneticZData      = np.random.random((numFiles, dims[0]))
    timeStepNum        = np.arange(0, numFiles, 1)
    positions          = np.linspace(0., 1, dims[0])

    return (densityData, velocityXData, velocityYData, velocityZData,
            pressureData, ieData, magneticXData, magneticYData, magneticZData,
            positions, timeStepNum, dims, physicalSize)
# ==============================================================================

# ==============================================================================
def setupSubPlots(fieldName, lowLim, highLim, positions, data, linestyle, linewidth, marker, markersize, color, axsArray):
    # Get the subplot coordinates to set
    if fieldName == 'Density':
        a, b = (0,0)
    elif fieldName == 'Pressure':
        a, b = (0,1)
    elif fieldName == 'Internal Energy':
        a, b = (0,2)
    elif fieldName == '$V_x$':
        a, b = (1,0)
    elif fieldName == '$V_y$':
        a, b = (1,1)
    elif fieldName == '$V_z$':
        a, b = (1,2)
    elif fieldName == '$B_x$':
        a, b = (2,0)
    elif fieldName == '$B_y$':
        a, b = (2,1)
    elif fieldName == '$B_z$':
        a, b = (2,2)
    else:
        raise ValueError('setSubPlots received invalid fieldName')

    # Set plot parameters
    axsArray[a,b].set_ylim(lowLim, highLim)
    axsArray[a,b].set_ylabel(fieldName)
    axsArray[a,b].minorticks_on()
    axsArray[a,b].grid(which = "both")

    # Set initial values
    returnPlot, = axsArray[a,b].plot(positions,
                                     data[0,:],
                                     linestyle  = linestyle,
                                     linewidth  = linewidth,
                                     marker     = marker,
                                     markersize = markersize,
                                     color      = color,
                                     label      = fieldName,
                                     animated   = True)

    return returnPlot, axsArray
# ==============================================================================

# ==============================================================================
def computeLimit(dataSet, padPercent):
    pad = np.max(np.abs([dataSet.min(), dataSet.max()])) * padPercent
    if pad == 0:
        # if the dataset doesn't exist or is zero return reasonable limits
        return -1, 1
    else:
        lowLim  = dataSet.min() - pad
        highLim = dataSet.max() + pad
        return lowLim, highLim
# ==============================================================================

# ==============================================================================
def newFrame(idx, fig, supTitleText, densityPlot, pressurePlot, iePlot,
             velocityXPlot, velocityYPlot, velocityZPlot,
             magneticXPlot, magneticYPlot, magneticZPlot,
             densityData, pressureData, ieData,
             velocityXData, velocityYData, velocityZData,
             magneticXData, magneticYData, magneticZData,
             timeStepSamples, titleText):
    titleText.set_text(f"{supTitleText} \n Time Step: {idx}")

    densityPlot  .set_ydata(densityData[idx,:])
    pressurePlot .set_ydata(pressureData[idx,:])
    iePlot       .set_ydata(ieData[idx,:])

    velocityXPlot.set_ydata(velocityXData[idx,:])
    velocityYPlot.set_ydata(velocityYData[idx,:])
    velocityZPlot.set_ydata(velocityZData[idx,:])

    magneticXPlot.set_ydata(magneticXData[idx,:])
    magneticYPlot.set_ydata(magneticYData[idx,:])
    magneticZPlot.set_ydata(magneticZData[idx,:])

    # Report progress
    if not hasattr(newFrame, "counter"):
        newFrame.counter = -1  # Accounts for first call which is performed before the animation starts
        print()

    if newFrame.counter >= 0:
        print(f'Animation is {100*(newFrame.counter/timeStepSamples.shape[0]):.1f}% complete', end='\r')

    newFrame.counter += 1

    # The return is required to make blit work
    return (titleText, densityPlot, pressurePlot, iePlot,
            velocityXPlot, velocityYPlot, velocityZPlot,
            magneticXPlot, magneticYPlot, magneticZPlot)
# ==============================================================================

main()

print(f'Time to execute: {round(default_timer()-start,2)} seconds')