re-factoring fixes; marker defaults; colormaps for heatmaps; added plot functions in figure_base

nifty/plotting/__init__.py

 from descriptors import *
 from plots import *
 from figures import *
+from colormap import *
\ No newline at end of file

nifty/plotting/colormap/__init__.py

+from colormap import Colormap
+import colormaps
\ No newline at end of file

nifty/plotting/colormap/colormap.py

+from nifty.plotting.plotly_wrapper import PlotlyWrapper
+
+
+class Colormap(PlotlyWrapper):
+    def __init__(self, name, red, green, blue):
+        self.name = name
+        self.red = red
+        self.green = green
+        self.blue = blue
+
+    def validate_map(self):
+        def validade(m):
+            #TODO: implement validation
+            pass
+
+    @staticmethod
+    def from_matplotlib_colormap_internal(name, mpl_cmap): # no discontinuities only
+        red = [(c[0], c[2]) for c in mpl_cmap['red']]
+        green = [(c[0], c[2]) for c in mpl_cmap['green']]
+        blue = [(c[0], c[2]) for c in mpl_cmap['blue']]
+        return Colormap(name, red, green, blue)
+
+    def to_plotly(self):
+        r, g, b = 0, 0, 0
+        converted = list()
+        prev_split, prev_r, prev_g, prev_b = 0., 0., 0., 0.
+
+        while prev_split < 1:
+            next_split = min(self.red[r][0], self.blue[b][0], self.green[g][0])
+
+            if next_split == self.red[r][0]:
+                red_val = self.red[r][1]
+                r += 1
+            else:
+                slope = (self.red[r][1]-prev_r) / (self.red[r][0] - prev_split)
+                y = prev_r - slope * prev_split
+                red_val = slope * next_split + y
+
+            if next_split == self.green[g][0]:
+                green_val = self.green[g][1]
+                g += 1
+            else:
+                slope = (self.green[g][1] - prev_g) / (self.green[g][0] - prev_split)
+                y = prev_g - slope * prev_split
+                green_val = slope * next_split + y
+
+            if next_split == self.blue[b][0]:
+                blue_val = self.blue[b][1]
+                b += 1
+            else:
+                slope = (self.blue[b][1] - prev_b) / (self.blue[b][0] - prev_split)
+                y = prev_r - slope * prev_split
+                blue_val = slope * next_split + y
+
+            prev_split, prev_r, prev_g, prev_b = next_split, red_val, green_val, blue_val
+            converted.append([next_split,
+                              'rgb(' +
+                              str(int(red_val*255)) + "," +
+                              str(int(green_val*255)) + "," +
+                              str(int(blue_val*255)) + ")"])
+
+        return converted
+
+
+
+
+

nifty/plotting/colormap/colormaps.py

+from nifty.plotting.colormap.colormap import Colormap
+
+
+def HighEnergyCmap():
+    """
+        Returns a color map often used in High Energy Astronomy.
+    """
+
+    red = [(0.0, 0.0),
+           (0.167, 0.0),
+           (0.333, 0.5),
+           (0.5, 1.0),
+           (0.667, 1.0),
+           (0.833, 1.0),
+           (1.0, 1.0)]
+
+    green = [(0.0, 0.0),
+             (0.167, 0.0),
+             (0.333, 0.0),
+             (0.5, 0.0),
+             (0.667, 0.5),
+             (0.833, 1.0),
+             (1.0, 1.0)]
+
+    blue = [(0.0, 0.0),
+            (0.167, 1.0),
+            (0.333, 0.5),
+            (0.5, 0.0),
+            (0.667, 0.0),
+            (0.833, 0.0),
+            (1.0, 1.0)]
+    return Colormap("High Energy", red, green, blue)
+
+
+def FaradayMapCmap():
+    """
+        Returns a color map used in reconstruction of the "Faraday Map".
+
+        References
+        ----------
+        .. [#] N. Opermann et. al.,
+            "An improved map of the Galactic Faraday sky",
+            Astronomy & Astrophysics, Volume 542, id.A93, 06/2012;
+            `arXiv:1111.6186 <http://www.arxiv.org/abs/1111.6186>`_
+    """
+    red = [(0.0, 0.35),
+           (0.1, 0.4),
+           (0.2, 0.25),
+           (0.41, 0.47),
+           (0.5, 0.8),
+           (0.56, 0.96),
+           (0.59, 1.0),
+           (0.74, 0.8),
+           (0.8, 0.8),
+           (0.9, 0.5),
+           (1.0, 0.4)]
+
+    green = [(0.0, 0.0),
+             (0.2, 0.0),
+             (0.362, 0.88),
+             (0.5, 1.0),
+             (0.638, 0.88),
+             (0.8, 0.25),
+             (0.9, 0.3),
+             (1.0, 0.2)]
+
+    blue = [(0.0, 0.35),
+            (0.1, 0.4),
+            (0.2, 0.8),
+            (0.26, 0.8),
+            (0.41, 1.0),
+            (0.44, 0.96),
+            (0.5, 0.8),
+            (0.59, 0.47),
+            (0.8, 0.0),
+            (1.0, 0.0)]
+
+    return Colormap("Faraday Map", red, green, blue)
+
+
+def FaradayUncertaintyCmap():
+    """
+        Returns a color map used for the "Faraday Map Uncertainty".
+
+        References
+        ----------
+        .. [#] N. Opermann et. al.,
+            "An improved map of the Galactic Faraday sky",
+            Astronomy & Astrophysics, Volume 542, id.A93, 06/2012;
+            `arXiv:1111.6186 <http://www.arxiv.org/abs/1111.6186>`_
+    """
+    red = [(0.0, 1.0),
+           (0.1, 0.8),
+           (0.2, 0.65),
+           (0.41, 0.6),
+           (0.5, 0.7),
+           (0.56, 0.96),
+           (0.59, 1.0),
+           (0.74, 0.8),
+           (0.8, 0.8),
+           (0.9, 0.5),
+           (1.0, 0.4)]
+
+    green = [(0.0, 0.9),
+             (0.2, 0.65),
+             (0.362, 0.95),
+             (0.5, 1.0),
+             (0.638, 0.88),
+             (0.8, 0.25),
+             (0.9, 0.3),
+             (1.0, 0.2)]
+
+    blue = [(0.0, 1.0),
+            (0.1, 0.8),
+            (0.2, 1.0),
+            (0.41, 1.0),
+            (0.44, 0.96),
+            (0.5, 0.7),
+            (0.59, 0.42),
+            (0.8, 0.0),
+            (1.0, 0.0)]
+
+    return Colormap("Faraday Uncertainty", red, green, blue)
+
+
+def PlusMinusCmap():
+    """
+        Returns a color map useful for a zero-centerd range of values.
+    """
+    red = [(0.0, 1.0),
+           (0.1, 0.96),
+           (0.2, 0.84),
+           (0.3, 0.64),
+           (0.4, 0.36),
+           (0.5, 0.0),
+           (0.6, 0.0),
+           (0.7, 0.0),
+           (0.8, 0.0),
+           (0.9, 0.0),
+           (1.0, 0.0)]
+
+    green = [(0.0, 0.5),
+             (0.1, 0.32),
+             (0.2, 0.18),
+             (0.3, 0.08),
+             (0.4, 0.02),
+             (0.5, 0.0),
+             (0.6, 0.02),
+             (0.7, 0.08),
+             (0.8, 0.18),
+             (0.9, 0.32),
+             (1.0, 0.5)]
+
+    blue = [(0.0, 0.0),
+            (0.1, 0.0),
+            (0.2, 0.0),
+            (0.3, 0.0),
+            (0.4, 0.0),
+            (0.5, 0.0),
+            (0.6, 0.36),
+            (0.7, 0.64),
+            (0.8, 0.84),
+            (0.9, 0.96),
+            (1.0, 1.0)]
+
+    return Colormap("Plus Minus", red, green, blue)
+
+
+def PlankCmap():
+    """
+        Returns a color map similar to the one used for the "Planck CMB Map".
+    """
+    red = [(0.0, 0.0),
+           (0.1, 0.0),
+           (0.2, 0.0),
+           (0.3, 0.0),
+           (0.4, 0.0),
+           (0.5, 1.0),
+           (0.6, 1.0),
+           (0.7, 1.0),
+           (0.8, 0.83),
+           (0.9, 0.67),
+           (1.0, 0.5)]
+
+    green = [(0.0, 0.0),
+             (0.1, 0.0),
+             (0.2, 0.0),
+             (0.3, 0.3),
+             (0.4, 0.7),
+             (0.5, 1.0),
+             (0.6, 0.7),
+             (0.7, 0.3),
+             (0.8, 0.0),
+             (0.9, 0.0),
+             (1.0, 0.0)]
+
+    blue = [(0.0, 0.5),
+            (0.1, 0.67),
+            (0.2, 0.83),
+            (0.3, 1.0),
+            (0.4, 1.0),
+            (0.5, 1.0),
+            (0.6, 0.0),
+            (0.7, 0.0),
+            (0.8, 0.0),
+            (0.9, 0.0),
+            (1.0, 0.0)]
+
+    return Colormap("Planck-like", red, green, blue)

nifty/plotting/figures/figure_2D.py

@@ -7,6 +7,7 @@ from nifty.plotting.plots import Heatmap, Mollweide
 class Figure2D(FigureFromPlot):
     def __init__(self, plots, title=None, width=None, height=None,
                  xaxis=None, yaxis=None):
+        super(Figure2D, self).__init__(plots, title, width, height)
 
         # TODO: add sanitization of plots input
         if isinstance(plots[0], Heatmap) and not width and not height:
@@ -45,7 +46,7 @@ class Figure2D(FigureFromPlot):
                                                 showticklabels=False
                                             )
         if self.yaxis:
-            plotly_object['layout']['yaxis'] = self.yaxis._to_plotly()
+            plotly_object['layout']['yaxis'] = self.yaxis.to_plotly()
         elif not self.yaxis:
             plotly_object['layout']['yaxis'] = dict(showline=False)
 

nifty/plotting/figures/figure_base.py

 # -*- coding: utf-8 -*-
 
+
+import os
+from PIL import Image
+
+import plotly.offline as ply_offline
+import plotly.plotly as ply
+
+
 from nifty.plotting.plotly_wrapper import PlotlyWrapper
 
 
@@ -8,3 +16,29 @@ class FigureBase(PlotlyWrapper):
         self.title = title
         self.width = width
         self.height = height
+
+    def plot(self, filename=None, interactive=False):
+        if not filename:
+            filename = os.path.abspath('/tmp/temp-plot.html')
+        if interactive:
+            try:
+                __IPYTHON__
+                ply_offline.init_notebook_mode(connected=True)
+                ply_offline.iplot(self.to_plotly(), filename=filename)
+            except NameError:
+                ply_offline.plot(self.to_plotly(), filename=filename)
+                raise Warning('IPython not active! Running without interactive mode.')
+        else:
+            ply_offline.plot(self.to_plotly(), filename=filename)
+
+    def plot_image(self, filename=None, show=False):
+        if not filename:
+            filename = os.path.abspath('temp-plot.jpeg')
+        ply_obj = self.to_plotly()
+        ply.image.save_as(ply_obj, filename=filename)
+        if show:
+            img = Image.open(filename)
+            img.show()
+
+
+

nifty/plotting/figures/multi_figure.py

 # -*- coding: utf-8 -*-
 
 import numpy as np
-
 from nifty import dependency_injector as gdi
-
 from figure_base import FigureBase
 from figure_3D import Figure3D
 
 plotly = gdi.get('plotly')
 
 
+# TODO: add nice height and width defaults for multifigure
 class MultiFigure(FigureBase):
-    def __init__(self, rows, columns, subfigures=None,
-                 title=None, width=None, height=None):
+    def __init__(self, rows, columns, title=None, width=None, height=None,
+                 subfigures=None):
         if 'plotly' not in gdi:
             raise ImportError("The module plotly is needed but not available.")
         super(MultiFigure, self).__init__(title, width, height)
@@ -31,42 +30,37 @@ class MultiFigure(FigureBase):
         self.subfigures[row, column] = figure
 
     def to_plotly(self):
-        sub_titles = self.subfigures.copy()
-        sub_titles = sub_titles.flatten
-        title_extractor = lambda z: z.title
-        sub_titles = np.vectorize(title_extractor)(sub_titles)
-
-        sub_specs = self.subfigures.copy_empty()
-        specs_setter = \
-            lambda z: {'is_3d': True} if isinstance(z, Figure3D) else {}
-        sub_specs = np.vectorize(specs_setter)(sub_specs)
+        title_extractor = lambda z: z.title if z else ""
+        sub_titles = tuple(np.vectorize(title_extractor)(self.subfigures.flatten()))
+
+        specs_setter = lambda z: {'is_3d': True} if isinstance(z, Figure3D) else {}
+        sub_specs = list(map(list, np.vectorize(specs_setter)(self.subfigures)))
+
         multi_figure_plotly_object = plotly.tools.make_subplots(
                                                    self.rows,
                                                    self.columns,
                                                    subplot_titles=sub_titles,
                                                    specs=sub_specs)
-
+        #TODO resolve bug with titles and 3D subplots
         for index, fig in np.ndenumerate(self.subfigures):
-            for plot in fig.plots:
-                multi_figure_plotly_object.append_trace(plot.to_plotly(),
-                                                        index[0]+1,
-                                                        index[1]+1)
+            if fig:
+                for plot in fig.plots:
+                    multi_figure_plotly_object.append_trace(plot.to_plotly(),
+                                                            index[0]+1,
+                                                            index[1]+1)
 
         multi_figure_plotly_object['layout'].update(height=self.height,
                                                     width=self.width,
                                                     title=self.title)
+
         return multi_figure_plotly_object
 
 
     @staticmethod
-    def from_figures_2cols(figures, title=None, width=None, height=None):
-        multi_figure = MultiFigure((len(figures)+1)/2, 2, title, width, height)
-
-        for i in range(0, len(figures), 2):
-            multi_figure.add_subfigure(figures[i], i/2, 0)
-
-        for i in range(1, len(figures), 2):
-            multi_figure.add_subfigure(figures[i], i/2, 1)
+    def from_figures_cols(figures, cols=2, title=None, width=None, height=None):
+        multi_figure = MultiFigure((len(figures) + cols -1)/cols , cols, title, width, height)
+        for i in range(len(figures)):
+            multi_figure.add_subfigure(figures[i], i/cols, i%cols)
 
         return multi_figure
 

nifty/plotting/plots/heatmaps/heatmap.py

 # -*- coding: utf-8 -*-
 
-from nifty.plotting.plots.plot import Plot
+from nifty.plotting.plotly_wrapper import PlotlyWrapper
 
 
-class Heatmap(Plot):
-    def __init__(self, data, label='', line=None, marker=None, webgl=False,
+class Heatmap(PlotlyWrapper):
+    def __init__(self, data, color_map=None, webgl=False,
                  smoothing=False):  # smoothing 'best', 'fast', False
-        super(Heatmap, self).__init__(label, line, marker)
         self.data = data
+        self.color_map = color_map
         self.webgl = webgl
         self.smoothing = smoothing
 
     def to_plotly(self):
-        plotly_object = super(Heatmap, self).to_plotly()
+        plotly_object = dict()
         plotly_object['z'] = self.data
+        plotly_object['showscale'] = False
+        if self.color_map:
+            plotly_object['colorscale'] = self.color_map.to_plotly()
+            plotly_object['colorbar'] = dict(title=self.color_map.name, x=0.42)
         if self.webgl:
             plotly_object['type'] = 'heatmapgl'
         else:

nifty/plotting/plots/heatmaps/mollweide.py

@@ -8,7 +8,7 @@ healpy = gdi.get('healpy')
 
 
 class Mollweide(Heatmap):
-    def __init__(self, data, label='', line=None, marker=None, webgl=False,
+    def __init__(self, data, color_map=None, webgl=False,
                  smoothing=False):  # smoothing 'best', 'fast', False
         if 'pylab' not in gdi:
             raise ImportError("The module pylab is needed but not available.")
@@ -16,8 +16,7 @@ class Mollweide(Heatmap):
             raise ImportError("The module healpy is needed but not available.")
 
         data = self._mollview(data)
-        super(Mollweide, self).__init__(data, label, line, marker, webgl,
-                                        smoothing)
+        super(Mollweide, self).__init__(data, color_map, webgl, smoothing)
 
     def _mollview(self, x, xsize=800):
         x = healpy.pixelfunc.ma_to_array(x)

nifty/plotting/plots/plot.py

@@ -2,13 +2,15 @@
 
 from abc import abstractmethod
 from nifty.plotting.plotly_wrapper import PlotlyWrapper
-
+from nifty.plotting.descriptors import Marker
 
 class Plot(PlotlyWrapper):
     def __init__(self, label, line, marker):
         self.label = label
         self.line = line
         self.marker = marker
+        if not self.line and not self.marker:
+            self.marker = Marker()
 
     @abstractmethod
     def to_plotly(self):
@@ -19,10 +21,10 @@ class Plot(PlotlyWrapper):
             ply_object['line'] = self.line.to_plotly()
             ply_object['marker'] = self.marker.to_plotly()
         elif self.line:
-            ply_object['mode'] = 'markers'
+            ply_object['mode'] = 'line'
             ply_object['line'] = self.line.to_plotly()
         elif self.marker:
-            ply_object['mode'] = 'line'
+            ply_object['mode'] = 'markers'
             ply_object['marker'] = self.marker.to_plotly()
 
         return ply_object