correct comp update
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@ -1,22 +1,16 @@
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"""Specialised plots for functions defined in blmfuncs.py.
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fixme:
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-- Im normalsing all color mapping input vectors to [0,1]. This will
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destroy informative numerical values in colorbar (but we
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are not showing these anyway). A better fix would be to let the
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colorbar listen to the scalarmappable instance and corect itself, but
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I did not get that to work ...
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fixme2:
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-- If scatterplot is not inited with a colorvector there will be no
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colorbar, but when adding colors the colorbar shoud be created.
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"""
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from fluents import plots
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from scipy import dot,sum,diag,arange,log,mean,newaxis,sqrt
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from matplotlib import cm
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import pylab as PB
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import gtk
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from matplotlib import cm
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import gtk
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import fluents
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from fluents import plots
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import scipy
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from scipy import dot,sum,diag,arange,log,mean,newaxis,sqrt
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class BlmScatterPlot(plots.ScatterPlot):
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"""Scatter plot used for scores and loadings in bilinear models."""
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@ -31,6 +25,7 @@ class BlmScatterPlot(plots.ScatterPlot):
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self._absi = absi
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self._ordi = ordi
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self._colorbar = None
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self._cmap = cm.jet
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dataset_1 = model.as_dataset(part_name)
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id_dim = dataset_1.get_dim_name(0)
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sel_dim = dataset_1.get_dim_name(1)
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@ -43,10 +38,45 @@ class BlmScatterPlot(plots.ScatterPlot):
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plots.ScatterPlot.__init__(self, dataset_1, dataset_1, id_dim, sel_dim, id_1, id_2 ,c=col ,s=40 , name=title)
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self.sc.set_cmap(self._cmap)
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self.add_pc_spin_buttons(self._T.shape[1], absi, ordi)
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self._key_press = self.canvas.mpl_connect(
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'key_press_event', self._on_key_press)
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def _update_color_from_dataset(self, data):
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"""Overriding scatter for testing of colormaps.
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"""
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is_category = False
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array = data.asarray()
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#only support for 2d-arrays:
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try:
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m, n = array.shape
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except:
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raise ValueError, "No support for more than 2 dimensions."
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# is dataset a vector or matrix?
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if not n==1:
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# we have a category dataset
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if isinstance(data, fluents.dataset.CategoryDataset):
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is_category = True
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map_vec = scipy.dot(array, scipy.diag(scipy.arange(n))).sum(1)
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else:
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map_vec = array.sum(1)
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else:
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map_vec = array.ravel()
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# update facecolors
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self.sc.set_array(map_vec)
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self.sc.set_clim(map_vec.min(), map_vec.max())
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if is_category:
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cmap = cm.Paired
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else:
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cmap = cm.jet
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self.sc.set_cmap(cmap)
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self.sc.update_scalarmappable() #sets facecolors from array
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self.canvas.draw()
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def _on_key_press(self, event):
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if event.key=='c':
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self.toggle_colorbar()
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@ -68,7 +98,7 @@ class BlmScatterPlot(plots.ScatterPlot):
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if self._colorbar==None:
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if self.sc._A!=None: # we need colormapping
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# get axes original position
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self._ax_last_pos = self.ax.get_position()
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self._ax_last_pos = self.axes.get_position()
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self._colorbar = self.fig.colorbar(self.sc)
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self._colorbar.draw_all()
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self.canvas.draw()
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@ -80,18 +110,18 @@ class BlmScatterPlot(plots.ScatterPlot):
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self.sc.observers = [obs for obs in self.sc.observers if obs !=self._colorbar]
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self._colorbar = None
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self.sc.colorbar = None
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self.ax.set_position(self._ax_last_pos)
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self.axes.set_position(self._ax_last_pos)
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self.canvas.draw()
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def add_pc_spin_buttons(self, amax, absi, ordi):
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sb_a = gtk.SpinButton(climb_rate=1)
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sb_a.set_range(1, amax)
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sb_a.set_value(absi)
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sb_a.set_value(absi+1)
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sb_a.set_increments(1, 5)
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sb_a.connect('value_changed', self.set_absicca)
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sb_o = gtk.SpinButton(climb_rate=1)
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sb_o.set_range(1, amax)
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sb_o.set_value(ordi)
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sb_o.set_value(ordi+1)
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sb_o.set_increments(1, 5)
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sb_o.connect('value_changed', self.set_ordinate)
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hbox = gtk.HBox()
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@ -115,12 +145,12 @@ class BlmScatterPlot(plots.ScatterPlot):
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self.xaxis_data = xy[:,0]
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self.yaxis_data = xy[:,1]
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self.sc._offsets = xy
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if self.use_blit==True:
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self.canvas.restore_region(self._clean_bck)
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self.ax.draw_artist(self.sc)
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self.canvas.blit()
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else:
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self.canvas.draw_idle()
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self.selection_collection._offsets = xy
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self.canvas.draw_idle()
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pad = abs(self.xaxis_data.min()-self.xaxis_data.max())*0.05
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new_lims = (self.xaxis_data.min()+pad, self.xaxis_data.max()+pad)
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self.axes.set_xlim(new_lims, emit=True)
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self.canvas.draw_idle()
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def set_ordinate(self, sb):
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self._ordi = sb.get_value_as_int() - 1
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@ -128,12 +158,11 @@ class BlmScatterPlot(plots.ScatterPlot):
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self.xaxis_data = xy[:,0]
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self.yaxis_data = xy[:,1]
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self.sc._offsets = xy
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if self.use_blit==True:
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self.canvas.restore_region(self._clean_bck)
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self.ax.draw_artist(self.sc)
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self.canvas.blit()
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else:
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self.canvas.draw_idle()
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self.selection_collection._offsets = xy
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pad = abs(self.yaxis_data.min()-self.yaxis_data.max())*0.05
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new_lims = (self.yaxis_data.min()+pad, self.yaxis_data.max()+pad)
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self.axes.set_ylim(new_lims, emit=True)
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self.canvas.draw_idle()
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def show_labels(self, index=None):
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if self._text_labels == None:
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@ -141,7 +170,7 @@ class BlmScatterPlot(plots.ScatterPlot):
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y = self.yaxis_data
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self._text_labels = {}
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for name, n in self.dataset_1[self.current_dim].items():
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txt = self.ax.text(x[n],y[n], name)
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txt = self.axes.text(x[n],y[n], name)
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txt.set_visible(False)
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self._text_labels[n] = txt
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if index!=None:
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@ -156,6 +185,7 @@ class BlmScatterPlot(plots.ScatterPlot):
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txt.set_visible(False)
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self.canvas.draw()
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class PcaScorePlot(BlmScatterPlot):
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def __init__(self, model, absi=0, ordi=1):
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title = "Pca scores (%s)" %model._dataset['X'].get_name()
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@ -213,7 +243,7 @@ class PlsQvalScatter(plots.ScatterPlot):
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id_2, = dataset_2.get_identifiers(sel_dim_2, [0])
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if model.model.has_key('w_tsq'):
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col = model.model['w_tsq'].ravel()
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col = normalise(col)
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#col = normalise(col)
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else:
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col = 'g'
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plots.ScatterPlot.__init__(self, dataset_1, dataset_2,
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@ -232,13 +262,13 @@ class PredictionErrorPlot(plots.Plot):
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plots.Plot.__init__(self, name)
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self._frozen = True
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self.current_dim = 'johndoe'
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self.ax = self.fig.add_subplot(111)
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self.axes = self.fig.add_subplot(111)
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# draw
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sep = model.model['sep']
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aopt = model.model['aopt']
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bx_plot_lines = self.ax.boxplot(sqrt(sep))
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aopt_marker = self.ax.axvline(aopt, linewidth=10,
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bx_plot_lines = self.axes.boxplot(sqrt(sep))
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aopt_marker = self.axes.axvline(aopt, linewidth=10,
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color='r',zorder=0,
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alpha=.5)
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