從 scipy interpolate/griddata 檢索數據點

Question

我使用 Scipy 的 Griddata 使用繪制的點（顯示為空）填充此網格化數據。 有沒有辦法根據 (x,y) 坐標獲取插值 (z)？ 這是繪圖的代碼，x、y、z 值都是系列。

    xi = np.linspace(min(lats),max(lats),360)
    yi = np.linspace(min(lons),max(lons),360)
    # grid the data.
    zi = griddata((lats, lons), nuits, (xi[None,:], yi[:,None]), method='cubic')
    # contour the gridded data.
    plt.contourf(xi,yi,zi,15,cmap=cMap)
    plt.colorbar()
    # plot data points.
    #plt.scatter(lats,lons,c=nuits,marker='o',s=26,cmap=cMap)
    plt.scatter(lats,lons,facecolors='none', edgecolors='k',s=26)
    plt.show()

Answer 1

這會起作用：

xi_coords = {value: index for index, value in enumerate(xi)}
yi_coords = {value: index for index, value in enumerate(yi)}
xic = <your coordinate>
yic = <your coordinate>
zi[xi_coords[xic], yi_coords[yic]]

Answer 2

您可以通過以下方式從 (xi,yi) 坐標中獲取內插的 zi 坐標：

# (xi,yi) coords to get the interpolated zi coords
# where len(xic) = len(yic)  
xic = <your coordinate>
yic = <your coordinate>

# sort these coordinates in an increasing order
s_xic = np.sort(xic)
s_yic = np.sort(yic)

# indices belonging to xic, yic, that would sort the array
ind_s_xic = np.argsort(xic)
ind_s_yic = np.argsort(yic)

 
dict_xic = dict(zip(ind_s_xic, np.array(range(len(xic))))
dict_yic = dict(zip(ind_s_yic, np.array(range(len(yic))))


xi,yi = np.meshgrid(s_xic, s_yic)

# zi_grid has dimensions ( len(yic), len(xic) )
zi_grid = griddata((lats, lons), nuits, (xi, yi), method='cubic')

# zic is the interpolated z-coordinate data with an arrangement order,
# corresponding to the x and y-coordinate data in xic and yic
zic =  [ zi_grid[dict_yic[i], dict_xic[i]] for i in range(len(xic)) ]

訪問How does one use numpy's Meshgrid function with a random interval rather than a equally spaced one? 了解 meshgrid 的工作原理。

Meshgrid 可以從您的不均勻間隔的 (xi,yi) 坐標創建，之后，griddata 可以使用您的 meshgrid 從基於點 = (lats, lons)，值 = nuits 創建的插值表面插入 z 坐標。