Python matplotlib.pylab.ion() Examples

The following are 9 code examples of matplotlib.pylab.ion(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module matplotlib.pylab , or try the search function .
Example #1
Source File: testfuncs.py    From Computable with MIT License 6 votes vote down vote up 
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()
Example #2
Source File: testfuncs.py    From matplotlib-4-abaqus with MIT License 6 votes vote down vote up 
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()
Example #3
Source File: testfuncs.py    From neural-network-animation with MIT License 6 votes vote down vote up 
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()
Example #4
Source File: testfuncs.py    From ImageFusion with MIT License 6 votes vote down vote up 
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()
Example #5
Source File: demo_ui.py    From spriteworld with Apache License 2.0 6 votes vote down vote up 
def __init__(self):
    self.rewards = 10 * [np.nan]
    self.rewards_bounds = [-10, 10]
    self.last_success = None

    plt.ion()
    self._fig = plt.figure(
        figsize=(9, 12), num='Spriteworld', facecolor='white')
    gs = gridspec.GridSpec(2, 1, height_ratios=[3, 1])
    self._ax_image = plt.subplot(gs[0])
    self._ax_image.axis('off')

    self._ax_scalar = plt.subplot(gs[1])
    self._ax_scalar.spines['right'].set_visible(False)
    self._ax_scalar.spines['top'].set_visible(False)
    self._ax_scalar.xaxis.set_ticks_position('bottom')
    self._ax_scalar.yaxis.set_ticks_position('left')
    self._setup_callbacks()
Example #6
Source File: testfuncs.py    From Computable with MIT License 4 votes vote down vote up 
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()
Example #7
Source File: testfuncs.py    From matplotlib-4-abaqus with MIT License 4 votes vote down vote up 
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()
Example #8
Source File: testfuncs.py    From neural-network-animation with MIT License 4 votes vote down vote up 
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()
Example #9
Source File: testfuncs.py    From ImageFusion with MIT License 4 votes vote down vote up 
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()