Question

我有一个创建类似2D直方图网格的函数。因此，我可以选择是否将这个新情节放在预先存在的数字上，我会执行以下操作：

def make_hist2d(x, y, current_fig=False, layout=(1,1,1),*args):

    if current_fig: 

        fig = _plt.gcf()
        ax  = fig.add_subplot(*layout)  # layout=(nrows, ncols, nplot)

    else:

        fig, ax = _plt.subplots()    


    H, x, y = np.histogram2d(...)

    # manipulate the histogram, e.g. column normalize.

    XX, YY = _np.meshgrid(xedges, yedges)
    Image  = ax.pcolormesh(XX, YY, Hplot.T, norm=norm, **pcmesh_kwargs)
    ax.autoscale(tight=True)

    grid_kargs = {'orientation': 'vertical'}
    cax, kw    = _mpl.colorbar.make_axes_gridspec(ax, **grid_kargs)
    cbar       = fig.colorbar(Image, cax=cax)
    cbar.set_label(cbar_title)

    return fig, ax, cbar



def hist2d_grid(data_dict, key_pairs, layout, *args):  # ``*args`` are things like xlog, ylog, xlabel, etc. 
                                                       # that are common to all subplots in the figure.

    fig, ax = _plt.subplots()    

    nplots = range(len(key_pairs) + 1)    # key_pairs = ((k1a, k1b), (k2a, k2b), ..., (kna, knb))

    ax_list = []

    for pair, i in zip(key_pairs, nplots):

        fig, ax, cbar = make_hist2d(data[k1a], data[k1b]

        ax_list.append(ax)

    return fig, ax_list

然后我打电话给：

hgrid = hist2d_grid(...)

但是，如果我想向grid添加一个新图形，我不知道获得子图布局的好方法。例如，是否有类似的东西：

layout = fig.get_layout()

那会给我一些像(nrows, ncols, n_subplots)？

的东西

我可以用以下的方式做到这一点：

n_plot = len(ax_list) / 2  # Each subplot generates a plot and a color bar.
n_rows = np.floor(np.sqrt(n_ax))
n_cols = np.ceil(np.sqrt(n_ax))

但是我必须处理像(2,4)子图数组这样的特殊情况，我会得到n_rows = 2和n_cols = 3，这意味着我会将(2,3,8)传递给ax.add_subplot() <div id="waterfall"> <div class="fall" id="water1">Defaulter’s Initial Margin</div> <div class="fall" id="water2">Defaulter’s Guaranty Fund Contribution</div> <div class="fall" id="water3">Clearing House Contribution $20 Million</div> <div class="fall" id="water4">Guaranty Fund<br>Total Value XX Million</div> <div class="fall" id="water5">Unfunded contributions - assessment <div class="text-box" id="text-box-2">text text text text text text text text text text text text text text text text text text text</div> </div> <div class="fall" id="water6">Service Continuity Phase <div class="text-box" id="text-box-1">text text text text text text text text text text text text text text text text text text text</div> </div> <div class="fall" id="water7">Service Closure</div> </div>，显然不起作用，因为8＆gt; 3 * 2

Answer 1

由;WITH Parents AS ( Select SP1.SupplierId , SP1.ParentId from SupplierLinks SP1 where SP1.SupplierId = @SupplierId Union All Select SP2.SupplierId , SP2.ParentId From SupplierLinks SP2 Inner Join Parents C on C.ParentId = SP2.SupplierId ) Decalare @ParentId int Select @ParentId = P.SupplierId From Parents as P Where parentid = 0 or ParentId is null ;WITH Children AS ( Select SP1 .SupplierId , SP1 .ParentId from SupplierLinks SP1 where SupplierId = @ParentId Union All Select SP2.SupplierId , SP2.ParentId From SupplierLinks SP2 Inner Join Children C on C.SupplierId = SP2.parentid )返回的ax是一个numpy轴数，然后fig, ax = plt.subplots(4,2)将为您提供所需的布局信息，例如。

ax.shape

您还可以通过循环图形对象的子项

来获取各个轴的位置

 nrows, ncols = ax.shape
 n_subplots = nrows*ncols

并且可能从最终元素[[f.colNum, f.rowNum] for f in fig.get_children()[1:]]获得大小

如果需要，您还可以使用gridspec更明确地了解子图的位置。使用gridspec，您可以设置gridspec对象并传递给子图，

fig.get_children()[-1]

要获得可以使用的布局，

import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(2, 2)
ax = plt.subplot(gs[0, 0])

matplotlib：获取子图布局？

1 个答案: