Python pylab.ioff方法代码示例

# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import ioff [as 别名]
def generate_png_chess_dp_vertex(self):
    """Produces pictures of the dominant product vertex a chessboard convention"""
    import matplotlib.pylab as plt
    plt.ioff()
    dab2v = self.get_dp_vertex_doubly_sparse()
    for i, ab in enumerate(dab2v): 
        fname = "chess-v-{:06d}.png".format(i)
        print('Matrix No.#{}, Size: {}, Type: {}'.format(i+1, ab.shape, type(ab)), fname)
        if type(ab) != 'numpy.ndarray': ab = ab.toarray()
        fig = plt.figure()
        ax = fig.add_subplot(1,1,1)
        ax.set_aspect('equal')
        plt.imshow(ab, interpolation='nearest', cmap=plt.cm.ocean)
        plt.colorbar()
        plt.savefig(fname)
        plt.close(fig) 

# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import ioff [as 别名]
def plotallfuncs(allfuncs=allfuncs):
    from matplotlib import pylab as pl
    pl.ioff()
    nnt = NNTester(npoints=1000)
    lpt = LinearTester(npoints=1000)
    for func in allfuncs:
        print(func.title)
        nnt.plot(func, interp=False, plotter='imshow')
        pl.savefig('%s-ref-img.png' % func.func_name)
        nnt.plot(func, interp=True, plotter='imshow')
        pl.savefig('%s-nn-img.png' % func.func_name)
        lpt.plot(func, interp=True, plotter='imshow')
        pl.savefig('%s-lin-img.png' % func.func_name)
        nnt.plot(func, interp=False, plotter='contour')
        pl.savefig('%s-ref-con.png' % func.func_name)
        nnt.plot(func, interp=True, plotter='contour')
        pl.savefig('%s-nn-con.png' % func.func_name)
        lpt.plot(func, interp=True, plotter='contour')
        pl.savefig('%s-lin-con.png' % func.func_name)
    pl.ion() 

# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import ioff [as 别名]
def plotallfuncs(allfuncs=allfuncs):
    from matplotlib import pylab as pl
    pl.ioff()
    nnt = NNTester(npoints=1000)
    lpt = LinearTester(npoints=1000)
    for func in allfuncs:
        print(func.title)
        nnt.plot(func, interp=False, plotter='imshow')
        pl.savefig('%s-ref-img.png' % func.__name__)
        nnt.plot(func, interp=True, plotter='imshow')
        pl.savefig('%s-nn-img.png' % func.__name__)
        lpt.plot(func, interp=True, plotter='imshow')
        pl.savefig('%s-lin-img.png' % func.__name__)
        nnt.plot(func, interp=False, plotter='contour')
        pl.savefig('%s-ref-con.png' % func.__name__)
        nnt.plot(func, interp=True, plotter='contour')
        pl.savefig('%s-nn-con.png' % func.__name__)
        lpt.plot(func, interp=True, plotter='contour')
        pl.savefig('%s-lin-con.png' % func.__name__)
    pl.ion() 

# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import ioff [as 别名]
def generate_png_spy_dp_vertex(self):
    """Produces pictures of the dominant product vertex in a common black-and-white way"""
    import matplotlib.pyplot as plt
    plt.ioff()
    dab2v = self.get_dp_vertex_doubly_sparse()
    for i,ab2v in enumerate(dab2v): 
      plt.spy(ab2v.toarray())
      fname = "spy-v-{:06d}.png".format(i)
      print(fname)
      plt.savefig(fname, bbox_inches='tight')
      plt.close()
    return 0 

# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import ioff [as 别名]
def convert_one_audio_file_to_specgram(local_audio_file, converted_local_png_file):
    '''
    Convert a local audio file into a png format with spectrogram.

    Parameters
    ----------
    local_audio_file : string
        Local location to the audio file to be converted.

    converted_local_png_file : string
        Local location to store the converted audio file

    Returns
    -------
    None

    Raises
    ------
    DLPyError
        If anything goes wrong, it complains and prints the appropriate message.

    '''

    try:
        import soundfile as sf
        import matplotlib.pylab as plt
    except (ModuleNotFoundError, ImportError):
        raise DLPyError('cannot import soundfile')

    data, sampling_rate = sf.read(local_audio_file)

    fig, ax = plt.subplots(1)
    fig.subplots_adjust(left=0, right=1, bottom=0, top=1)
    ax.axis('off')
    ax.specgram(x=data, Fs=sampling_rate)
    ax.axis('off')
    fig.savefig(converted_local_png_file, dpi=300, frameon='false')
    # this is the key to avoid mem leaking in notebook
    plt.ioff()
    plt.close(fig) 

# 需要导入模块: from matplotlib import pylab [as 别名]
# 或者: from matplotlib.pylab import ioff [as 别名]
def plot(self, func, interp=True, plotter='imshow'):
        import matplotlib as mpl
        from matplotlib import pylab as pl
        if interp:
            lpi = self.interpolator(func)
            z = lpi[self.yrange[0]:self.yrange[1]:complex(0, self.nrange),
                    self.xrange[0]:self.xrange[1]:complex(0, self.nrange)]
        else:
            y, x = np.mgrid[
                self.yrange[0]:self.yrange[1]:complex(0, self.nrange),
                self.xrange[0]:self.xrange[1]:complex(0, self.nrange)]
            z = func(x, y)

        z = np.where(np.isinf(z), 0.0, z)

        extent = (self.xrange[0], self.xrange[1],
            self.yrange[0], self.yrange[1])
        pl.ioff()
        pl.clf()
        pl.hot()  # Some like it hot
        if plotter == 'imshow':
            pl.imshow(np.nan_to_num(z), interpolation='nearest', extent=extent,
                      origin='lower')
        elif plotter == 'contour':
            Y, X = np.ogrid[
                self.yrange[0]:self.yrange[1]:complex(0, self.nrange),
                self.xrange[0]:self.xrange[1]:complex(0, self.nrange)]
            pl.contour(np.ravel(X), np.ravel(Y), z, 20)
        x = self.x
        y = self.y
        lc = mpl.collections.LineCollection(
            np.array([((x[i], y[i]), (x[j], y[j]))
                      for i, j in self.tri.edge_db]),
            colors=[(0, 0, 0, 0.2)])
        ax = pl.gca()
        ax.add_collection(lc)

        if interp:
            title = '%s Interpolant' % self.name
        else:
            title = 'Reference'
        if hasattr(func, 'title'):
            pl.title('%s: %s' % (func.title, title))
        else:
            pl.title(title)

        pl.show()
        pl.ion()