Merge branch 'plotclass' into 'NIFTy_5'

Plot class

See merge request ift/nifty-dev!94

demos/bernoulli_demo.py

@@ -79,8 +79,9 @@ if __name__ == '__main__':
 
     reconstruction = sky(H.position)
 
-    ift.plot(reconstruction, title='reconstruction')
-    ift.plot(GR.adjoint_times(data), title='data')
-    ift.plot(sky(mock_position), title='truth')
-    ift.plot_finish(nx=3, xsize=16, ysize=5, title="results",
-                    name="bernoulli.png")
+    plot = ift.Plot()
+    plot.add(reconstruction, title='reconstruction')
+    plot.add(GR.adjoint_times(data), title='data')
+    plot.add(sky(mock_position), title='truth')
+    plot.output(nx=3, xsize=16, ysize=5, title="results",
+                name="bernoulli.png")

demos/getting_started_1.py

@@ -103,18 +103,17 @@ if __name__ == '__main__':
 
     # PLOTTING
     rg = isinstance(position_space, ift.RGSpace)
+    plot = ift.Plot()
     if rg and len(position_space.shape) == 1:
-        ift.plot([HT(MOCK_SIGNAL), GR.adjoint(data), HT(m)],
+        plot.add([HT(MOCK_SIGNAL), GR.adjoint(data), HT(m)],
                  label=['Mock signal', 'Data', 'Reconstruction'],
                  alpha=[1, .3, 1])
-        ift.plot(mask_to_nan(mask, HT(m-MOCK_SIGNAL)), title='Residuals')
-        ift.plot_finish(nx=2, ny=1, xsize=10, ysize=4,
-                        title="getting_started_1")
+        plot.add(mask_to_nan(mask, HT(m-MOCK_SIGNAL)), title='Residuals')
+        plot.output(nx=2, ny=1, xsize=10, ysize=4, title="getting_started_1")
     else:
-        ift.plot(HT(MOCK_SIGNAL), title='Mock Signal')
-        ift.plot(mask_to_nan(mask, (GR(Mask)).adjoint(data)),
+        plot.add(HT(MOCK_SIGNAL), title='Mock Signal')
+        plot.add(mask_to_nan(mask, (GR(Mask)).adjoint(data)),
                  title='Data')
-        ift.plot(HT(m), title='Reconstruction')
-        ift.plot(mask_to_nan(mask, HT(m-MOCK_SIGNAL)), title='Residuals')
-        ift.plot_finish(nx=2, ny=2, xsize=10, ysize=10,
-                        title="getting_started_1")
+        plot.add(HT(m), title='Reconstruction')
+        plot.add(mask_to_nan(mask, HT(m-MOCK_SIGNAL)), title='Residuals')
+        plot.output(nx=2, ny=2, xsize=10, ysize=10, title="getting_started_1")

demos/getting_started_2.py

@@ -99,8 +99,9 @@ if __name__ == '__main__':
     # Plot results
     signal = sky(mock_position)
     reconst = sky(H.position)
-    ift.plot(signal, title='Signal')
-    ift.plot(GR.adjoint(data), title='Data')
-    ift.plot(reconst, title='Reconstruction')
-    ift.plot(reconst - signal, title='Residuals')
-    ift.plot_finish(name='getting_started_2.png', xsize=16, ysize=16)
+    plot = ift.Plot()
+    plot.add(signal, title='Signal')
+    plot.add(GR.adjoint(data), title='Data')
+    plot.add(reconst, title='Reconstruction')
+    plot.add(reconst - signal, title='Residuals')
+    plot.output(name='getting_started_2.png', xsize=16, ysize=16)

demos/getting_started_3.py

@@ -82,10 +82,11 @@ if __name__ == '__main__':
     INITIAL_POSITION = ift.from_random('normal', domain)
     position = INITIAL_POSITION
 
-    ift.plot(signal(MOCK_POSITION), title='Ground Truth')
-    ift.plot(R.adjoint_times(data), title='Data')
-    ift.plot([A(MOCK_POSITION)], title='Power Spectrum')
-    ift.plot_finish(ny=1, nx=3, xsize=24, ysize=6, name="setup.png")
+    plot = ift.Plot()
+    plot.add(signal(MOCK_POSITION), title='Ground Truth')
+    plot.add(R.adjoint_times(data), title='Data')
+    plot.add([A(MOCK_POSITION)], title='Power Spectrum')
+    plot.output(ny=1, nx=3, xsize=24, ysize=6, name="setup.png")
 
     # number of samples used to estimate the KL
     N_samples = 20
@@ -100,18 +101,20 @@ if __name__ == '__main__':
         KL, convergence = minimizer(KL)
         position = KL.position
 
-        ift.plot(signal(position), title="reconstruction")
-        ift.plot([A(position), A(MOCK_POSITION)], title="power")
-        ift.plot_finish(ny=1, ysize=6, xsize=16, name="loop.png")
+        plot = ift.Plot()
+        plot.add(signal(position), title="reconstruction")
+        plot.add([A(position), A(MOCK_POSITION)], title="power")
+        plot.output(ny=1, ysize=6, xsize=16, name="loop.png")
 
+    plot = ift.Plot()
     sc = ift.StatCalculator()
     for sample in samples:
-        sc.add(signal(sample + position))
-    ift.plot(sc.mean, title="Posterior Mean")
-    ift.plot(ift.sqrt(sc.var), title="Posterior Standard Deviation")
+        sc.add(signal(sample+position))
+    plot.add(sc.mean, title="Posterior Mean")
+    plot.add(ift.sqrt(sc.var), title="Posterior Standard Deviation")
 
-    powers = [A(s + position) for s in samples]
-    ift.plot(
-        [A(position), A(MOCK_POSITION)] + powers,
+    powers = [A(s+position) for s in samples]
+    plot.add(
+        [A(position), A(MOCK_POSITION)]+powers,
         title="Sampled Posterior Power Spectrum")
-    ift.plot_finish(ny=1, nx=3, xsize=24, ysize=6, name="results.png")
+    plot.output(ny=1, nx=3, xsize=24, ysize=6, name="results.png")

demos/plot_test.py

@@ -20,21 +20,24 @@ def plot_test():
 
     # Start various plotting tests
 
-    ift.plot(field_rg1_1, title='Single plot')
-    ift.plot_finish()
-
-    ift.plot(field_rg2, title='2d rg')
-    ift.plot([field_rg1_1, field_rg1_2], title='list 1d rg', label=['1', '2'])
-    ift.plot(field_rg1_2, title='1d rg, xmin, ymin', xmin=0.5, ymin=0.,
+    plot = ift.Plot()
+    plot.add(field_rg1_1, title='Single plot')
+    plot.output()
+
+    plot = ift.Plot()
+    plot.add(field_rg2, title='2d rg')
+    plot.add([field_rg1_1, field_rg1_2], title='list 1d rg', label=['1', '2'])
+    plot.add(field_rg1_2, title='1d rg, xmin, ymin', xmin=0.5, ymin=0.,
              xlabel='xmin=0.5', ylabel='ymin=0')
-    ift.plot_finish(title='Three plots')
-
-    ift.plot(field_hp, title='HP planck-color', colormap='Planck-like')
-    ift.plot(field_rg1_2, title='1d rg')
-    ift.plot(field_ps)
-    ift.plot(field_gl, title='GL')
-    ift.plot(field_rg2, title='2d rg')
-    ift.plot_finish(nx=2, ny=3, title='Five plots')
+    plot.output(title='Three plots')
+
+    plot = ift.Plot()
+    plot.add(field_hp, title='HP planck-color', colormap='Planck-like')
+    plot.add(field_rg1_2, title='1d rg')
+    plot.add(field_ps)
+    plot.add(field_gl, title='GL')
+    plot.add(field_rg2, title='2d rg')
+    plot.output(nx=2, ny=3, title='Five plots')
 
 
 if __name__ == '__main__':

nifty5/__init__.py

@@ -69,7 +69,7 @@ from .minimization.line_energy import LineEnergy
 from .minimization.energy_adapter import EnergyAdapter
 
 from .sugar import *
-from .plotting.plot import plot, plot_finish
+from .plotting.plot import Plot
 
 from .library.amplitude_model import AmplitudeModel
 from .library.inverse_gamma_model import InverseGammaModel

nifty5/plotting/plot.py

@@ -262,82 +262,81 @@ def _plot(f, ax, **kwargs):
     raise ValueError("Field type not(yet) supported")
 
 
-_plots = []
-_kwargs = []
-
-
-def plot(f, **kwargs):
-    """Add a figure to the current list of plots.
-
-    Notes
-    -----
-    After doing one or more calls `plot()`, one also needs to call
-    `plot_finish()` to output the result.
-
-    Parameters
-    ----------
-    f: Field, or list of Field objects
-        If `f` is a single Field, it must live over a single `RGSpace`,
-        `PowerSpace`, `HPSpace`, `GLSPace`.
-        If it is a list, all list members must be Fields living over the same
-        one-dimensional `RGSpace` or `PowerSpace`.
-    title: string
-        title of the plot
-    xlabel: string
-        label for the x axis
-    ylabel: string
-        label for the y axis
-    [xyz]min, [xyz]max: float
-        limits for the values to plot
-    colormap: string
-        color map to use for the plot (if it is a 2D plot)
-    linewidth: float or list of floats
-        line width
-    label: string of list of strings
-        annotation string
-    alpha: float or list of floats
-        transparency value
-    """
-    _plots.append(f)
-    _kwargs.append(kwargs)
-
-
-def plot_finish(**kwargs):
-    """Plot the accumulated list of figures.
-
-    Parameters
-    ----------
-    title: string
-        title of the full plot
-    nx, ny: integer (default: square root of the numer of plots, rounded up)
-        number of subplots to use in x- and y-direction
-    xsize, ysize: float (default: 6)
-        dimensions of the full plot in inches
-    name: string (default: "")
-        if left empty, the plot will be shown on the screen,
-        otherwise it will be written to a file with the given name.
-        Supported extensions: .png and .pdf
-    """
-    global _plots, _kwargs
-    import matplotlib.pyplot as plt
-    nplot = len(_plots)
-    fig = plt.figure()
-    if "title" in kwargs:
-        plt.suptitle(kwargs.pop("title"))
-    nx = kwargs.pop("nx", int(np.ceil(np.sqrt(nplot))))
-    ny = kwargs.pop("ny", int(np.ceil(np.sqrt(nplot))))
-    if nx*ny < nplot:
-        raise ValueError(
-            'Figure dimensions not sufficient for number of plots. '
-            'Available plot slots: {}, number of plots: {}'
-            .format(nx*ny, nplot))
-    xsize = kwargs.pop("xsize", 6)
-    ysize = kwargs.pop("ysize", 6)
-    fig.set_size_inches(xsize, ysize)
-    for i in range(nplot):
-        ax = fig.add_subplot(ny, nx, i+1)
-        _plot(_plots[i], ax, **_kwargs[i])
-    fig.tight_layout()
-    _makeplot(kwargs.pop("name", None))
-    _plots = []
-    _kwargs = []
+class Plot(object):
+    def __init__(self):
+        self._plots = []
+        self._kwargs = []
+
+
+    def add(self, f, **kwargs):
+        """Add a figure to the current list of plots.
+
+        Notes
+        -----
+        After doing one or more calls `plot()`, one also needs to call
+        `plot_finish()` to output the result.
+
+        Parameters
+        ----------
+        f: Field, or list of Field objects
+            If `f` is a single Field, it must live over a single `RGSpace`,
+            `PowerSpace`, `HPSpace`, `GLSPace`.
+            If it is a list, all list members must be Fields living over the
+            same one-dimensional `RGSpace` or `PowerSpace`.
+        title: string
+            title of the plot
+        xlabel: string
+            label for the x axis
+        ylabel: string
+            label for the y axis
+        [xyz]min, [xyz]max: float
+            limits for the values to plot
+        colormap: string
+            color map to use for the plot (if it is a 2D plot)
+        linewidth: float or list of floats
+            line width
+        label: string of list of strings
+            annotation string
+        alpha: float or list of floats
+            transparency value
+        """
+        self._plots.append(f)
+        self._kwargs.append(kwargs)
+
+
+    def output(self, **kwargs):
+        """Plot the accumulated list of figures.
+
+        Parameters
+        ----------
+        title: string
+            title of the full plot
+        nx, ny: integer (default: square root of the numer of plots, rounded up)
+            number of subplots to use in x- and y-direction
+        xsize, ysize: float (default: 6)
+            dimensions of the full plot in inches
+        name: string (default: "")
+            if left empty, the plot will be shown on the screen,
+            otherwise it will be written to a file with the given name.
+            Supported extensions: .png and .pdf
+        """
+        import matplotlib.pyplot as plt
+        nplot = len(self._plots)
+        fig = plt.figure()
+        if "title" in kwargs:
+            plt.suptitle(kwargs.pop("title"))
+        nx = kwargs.pop("nx", int(np.ceil(np.sqrt(nplot))))
+        ny = kwargs.pop("ny", int(np.ceil(np.sqrt(nplot))))
+        if nx*ny < nplot:
+            raise ValueError(
+                'Figure dimensions not sufficient for number of plots. '
+                'Available plot slots: {}, number of plots: {}'
+                .format(nx*ny, nplot))
+        xsize = kwargs.pop("xsize", 6)
+        ysize = kwargs.pop("ysize", 6)
+        fig.set_size_inches(xsize, ysize)
+        for i in range(nplot):
+            ax = fig.add_subplot(ny, nx, i+1)
+            _plot(self._plots[i], ax, **self._kwargs[i])
+        fig.tight_layout()
+        _makeplot(kwargs.pop("name", None))