141 clear=True):
142
143 global fig
144 if not fig:
145 fig = plt.figure()
146 newFig = True
147 else:
148 newFig = False
149 if clear:
150 fig.clf()
151
152 axes = fig.add_axes((0.1, 0.1, 0.85, 0.80))
153
154 xmin = sorted(mag)[int(0.05*len(mag))]
155 xmax = sorted(mag)[int(0.95*len(mag))]
156
157 axes.set_xlim(-17.5, -13)
158 axes.set_xlim(xmin - 0.1*(xmax - xmin), xmax + 0.1*(xmax - xmin))
159 axes.set_ylim(0, 10)
160
161 colors = ["r", "g", "b", "c", "m", "k", ]
162 for k, mean in enumerate(centers):
163 if k == 0:
164 axes.plot(axes.get_xlim(), (mean, mean,), "k%s" % ltype)
165
166 ll = (clusterId == k)
167 axes.plot(mag[ll], width[ll], marker, markersize=markersize, markeredgewidth=markeredgewidth,
168 color=colors[k%len(colors)])
169
170 ll = (clusterId == -1)
171 axes.plot(mag[ll], width[ll], marker, markersize=markersize, markeredgewidth=markeredgewidth,
172 color='k')
173
174 if newFig:
175 axes.set_xlabel("model")
176 axes.set_ylabel(r"$\sqrt{I_{xx} + I_{yy}}$")
177
178 return fig
179