Python matplotlib.cm.Set1() Examples
The following are 2 code examples for showing how to use matplotlib.cm.Set1(). These examples are extracted from open source projects. 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.
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def scatter_plot( self, **kwds ): ''' Generates a scatter plot using the first 2 princpal components as axes. **Keywords**: - *vectors* = True if original axes should be plotted as vectors in this space. Default is False. - *path* = a path to save this figure to - *dpi* = the dpi of the saved figure - *width* = the width (in inches) of the saved figure - *height* = the height (in inches) of the saved figure ''' #get 2d subspace ss = self.get_subspace(n=2) #calculate colours import matplotlib.cm as cm scale = 255 / (max(self.groups) + 1) c = cm.Set1(self.groups*scale,alpha=1) #plot scatterplot fig,ax = plt.subplots() ss.plot('PC1','PC2',kind='scatter',c=c,ax=ax) #plot vectors if (kwds.has_key('vectors')): if kwds['vectors'] == True: #calculate initial vectors (ie. identity matrix) axes=np.identity(len(self.data.columns)) #project axes=self.project(axes,2) #plot for i,a in enumerate(axes): x = [0,a] y = [0,a] ax.plot(x,y,label=self.data.columns[i]) ax.legend() #private functions
def plot_cells(cells, dx=1.0, **kwargs): """ Plot the spatial receptive fields for multiple cells. Parameters ---------- cells : list of array_like A list of spatiotemporal receptive fields, each of which is a spatiotemporal array. dx : float, optional The spatial sampling rate of the STA, setting the scale of the x- and y-axes. ax : matplotlib Axes object, optional The axes onto which the ellipse should be plotted. Defaults to a new figure. Returns ------ fig : matplotlib.figure.Figure The figure onto which the ellipses are plotted. ax : matplotlib.axes.Axes The axes onto which the ellipses are plotted. """ _ = kwargs.pop('fig') ax = kwargs.pop('ax') colors = cm.Set1(np.random.rand(len(cells),)) # for each cell for color, sta in zip(colors, cells): # get the spatial profile try: spatial_profile = ft.decompose(sta) except np.linalg.LinAlgError: continue # plot ellipse try: ellipse(spatial_profile, fc=color, ec=color, lw=2, dx=dx, alpha=0.3, ax=ax) except RuntimeError: pass