我们从Python开源项目中，提取了以下9个代码示例，用于说明如何使用matplotlib.pyplot.GridSpec()。
def draw(self, X, y, **kwargs): """ Sets up the layout for the joint plot draw calls ``draw_joint`` and ``draw_xy`` to render the visualizations. """ fig = plt.figure(figsize=(self.size, self.size)) gs = plt.GridSpec(self.ratio + 1, self.ratio + 1) #Set up the 3 axes objects joint_ax = fig.add_subplot(gs[1:, :-1]) x_ax = fig.add_subplot(gs[0, :-1], sharex=joint_ax) y_ax = fig.add_subplot(gs[1:, -1], sharey=joint_ax) fig.tight_layout() fig.subplots_adjust(hspace=self.space, wspace=self.space) self.fig = fig self.joint_ax = joint_ax self.x_ax = x_ax self.y_ax = y_ax self.draw_joint(X, y, **kwargs) self.draw_xy(X, y, **kwargs)
def setup_figure(): f = plt.figure(figsize=(6, 2.15)) brain_gs = plt.GridSpec(2, 2, .03, .18, .52, .99, .05, .05) brain_axes = [f.add_subplot(gs) for gs in brain_gs] brain_axes = np.reshape(brain_axes, (2, 2)) hist_gs = plt.GridSpec(2, 1, .53, .20, .65, .975) hist_axes = [f.add_subplot(gs) for gs in hist_gs] cmap_gs = plt.GridSpec(1, 2, .05, .07, .50, .14, .05, .05) cmap_axes = [f.add_subplot(gs) for gs in cmap_gs] clust_gs = plt.GridSpec(1, 1, .75, .20, .98, .98) clust_ax = f.add_subplot(clust_gs[0]) f.text(.003, .92, "A", size=12) f.text(.68, .92, "B", size=12) return f, brain_axes, hist_axes, cmap_axes, clust_ax
def setupGrid(passRows, passCols): plugins.plotting.plotGrid = plot.GridSpec(passRows, passCols) # Change current grid location
def setup_figure(): f = plt.figure(figsize=(7, 2.8)) brain_gs = plt.GridSpec(3, 4, .13, .13, .87, .99, .05, .05) brain_axes = [f.add_subplot(gs) for gs in brain_gs] brain_axes = np.vstack(np.array_split(brain_axes, 6)) hist_gs = plt.GridSpec(3, 2, .01, .15, .99, .99, 7, .08) hist_axes = [f.add_subplot(gs) for gs in hist_gs] cbar_ax = f.add_axes([.35, .07, .3, .04]) return f, brain_axes, hist_axes, cbar_ax
def setup_figure(): f = plt.figure(figsize=(7, 4.65)) dots_grid = plt.GridSpec(2, 7, .08, .45, .98, .94, .15, .15) dots_axes = [f.add_subplot(spec) for spec in dots_grid] sticks_grid = plt.GridSpec(1, 6, .12, .09, .92, .34, .15, .1) sticks_axes = [f.add_subplot(spec) for spec in sticks_grid] return f, dots_axes, sticks_axes
def setup_figure(): f = plt.figure(figsize=(7, 6)) dots_grid = plt.GridSpec(2, 7, .1, .56, .98, .94, .1, .15) dots_axes = [f.add_subplot(spec) for spec in dots_grid] sticks_grid = plt.GridSpec(1, 6, .18, .31, .92, .48, .1, .1) sticks_axes = [f.add_subplot(spec) for spec in sticks_grid] rest_grid = plt.GridSpec(1, 6, .18, .07, .92, .24, .1, .1) rest_axes = [f.add_subplot(spec) for spec in rest_grid] return f, dots_axes, sticks_axes, rest_axes
def setup_figure(): f = plt.figure(figsize=(7, 6.56)) brain_gs = plt.GridSpec(7, 4, .13, .10, .87, .99, .05, .05) brain_axes = [f.add_subplot(gs) for gs in brain_gs] brain_axes = np.vstack(np.array_split(brain_axes, 14)) hist_gs = plt.GridSpec(7, 2, .01, .11, .99, .99, 7, .08) hist_axes = [f.add_subplot(gs) for gs in hist_gs] cbar_ax = f.add_axes([.35, .06, .3, .02]) return f, brain_axes, hist_axes, cbar_ax
def setup_figure(): f = plt.figure(figsize=(7, 4.5)) dots_grid = plt.GridSpec(2, 7, .02, .51, .98, .94, 0, 0) dots_axes = [f.add_subplot(spec) for spec in dots_grid] sticks_grid = plt.GridSpec(1, 6, .09, .26, .91, .47, 0, 0) sticks_axes = [f.add_subplot(spec) for spec in sticks_grid] rest_grid = plt.GridSpec(1, 6, .09, .01, .91, .22, 0, 0) rest_axes = [f.add_subplot(spec) for spec in rest_grid] return f, dots_axes, sticks_axes, rest_axes
def diagnostics(self, tmin=None, tmax=None, show=True): innovations = self.ml.innovations(tmin, tmax) fig = self._get_figure() gs = plt.GridSpec(2, 3, wspace=0.2) plt.subplot(gs[0, :2]) plt.title('Autocorrelation') # plt.axhline(0.2, '--') r = ps.stats.acf(innovations) plt.stem(r) plt.subplot(gs[1, :2]) plt.title('Partial Autocorrelation') # plt.axhline(0.2, '--') # plt.stem(self.ml.stats.pacf()) plt.subplot(gs[0, 2]) innovations.hist(bins=20) plt.subplot(gs[1, 2]) probplot(innovations, plot=plt) if show: plt.show() return fig.axes
