如何在python matplotlib中的3D图上映射Z轴

我有一个要以3D绘制的数据集。这是我要适应的工作演示：

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline 

L = 2
n = 5
x = np.linspace(-L, L, n)
y = x.copy()
X, Y = np.meshgrid(x, y)
Z = np.exp(-(X**2 + Y**2))

print("X",X)
print("Y",Y)
print("Z",Z)
print("X Y", (X,Y))

 
fig = plt.figure('3D surface')
ax = fig.add_subplot(111, projection='3d')
ax.plot_wireframe(X, Y, Z)
ax.set_xticks([-2, -1, 0, 1, 2])
ax.set_yticks([-2, -1, 0, 1, 2])
ax.set_zticks([0, 0.5, 1])
fig.tight_layout()

plt.show()

这将产生一个简单的（ish）3d图形

我不明白的一件事是如何Z = np.exp(-(X**2 + Y**2))提出数组的数组。

无论如何，我的数据是（X，Y）与要绘制的每个值的坐标的字典。因此，它应该执行这样的任务Z[0][0] = data[(30,7)]，Z[0][1] = data[(30,8)]依此类推。我也有_x, _y, _z专栏。但是我在理解如何Z从数据集中映射时遇到了麻烦。我玩了几个小时没有运气。即使以零作为数据运行，它也不喜欢形状。如何从此数据集构造Z以便正确呈现？

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline 

data = {(30, 7): 2.899760589371981, (30, 8): 4.3702838372222175, (30, 9): 257.85906533277785, (30, 10): 156.9642451913889, (30, 11): 117.79734351666666, (30, 12): 87.12845625999996, (30, 13): 94.1963482875, (30, 14): 144.57304811222224, (30, 15): 223.74991824888886, (29, 7): 2.9388598647343014, (29, 8): 183.23979641944442, (29, 9): 183.87488728833333, (29, 10): 119.85781460916668, (29, 11): 133.86661589138888, (29, 12): 109.66159447583333, (29, 13): 3.6515377230555557, (29, 14): 176.69359495694445, (29, 15): 218.97532622376457, (28, 7): 2.99624667961165, (28, 8): 152.36525726868572, (28, 9): 254.6567875744445, (28, 10): 310.34455074499994, (28, 11): 3.6265693675, (28, 12): 295.7473858616667, (28, 13): 354.81396648555545, (28, 14): 330.7759454947221, (28, 15): 515.8284059156024, (27, 7): 3.4832570676328496, (27, 8): 494.6530009130556, (27, 9): 558.9684737969444, (27, 10): 628.1385504569445, (27, 11): 429.3385649711112, (27, 12): 305.40794006611105, (27, 13): 398.37097107749986, (27, 14): 444.77040126472224, (27, 15): 595.9394107845642, (26, 7): 0.0, (26, 8): 0.0, (26, 9): 0.0, (26, 10): 0.0, (26, 11): 0.0, (26, 12): 0.0, (26, 13): 0.0, (26, 14): 0.0, (26, 15): 0.0, (23, 7): 2.7060749759615375, (23, 8): 533.8678920588889, (23, 9): 482.0098852449999, (23, 10): 284.4878292747223, (23, 11): 231.53837660861112, (23, 12): 205.2212722930555, (23, 13): 299.9973697577778, (23, 14): 325.5393605852778, (23, 15): 382.63983945363685, (22, 7): 2.83702641826923, (22, 8): 524.1154506774999, (22, 9): 346.5053747252778, (22, 10): 222.7439437819444, (22, 11): 251.81164356472226, (22, 12): 232.7076795425, (22, 13): 288.4576297033334, (22, 14): 362.3498162430556, (22, 15): 520.0129735083241, (21, 7): 2.7541651057692302, (21, 8): 211.71934589441514, (21, 9): 348.59216153305556, (21, 10): 330.0827526966666, (21, 11): 260.69524474055555, (21, 12): 320.93003513888885, (21, 13): 369.6799363852778, (21, 14): 3.6481402877777773, (21, 15): 1.8889219255968905, (20, 7): 2.7879265990338156, (20, 8): 497.38878044777783, (20, 9): 578.3888874361112, (20, 10): 519.4063311825, (20, 11): 379.19423817277783, (20, 12): 355.4565675847222, (20, 13): 315.1411549133333, (20, 14): 534.9071456774999, (20, 15): 497.936075809101, (19, 7): 2.944537333333333, (19, 8): 644.4201197541665, (19, 9): 527.9697446508333, (19, 10): 410.7373982661112, (19, 11): 3.7668233774999997, (19, 12): 302.8033477325001, (19, 13): 112.06049545249999, (19, 14): 174.2037114966666, (19, 15): 387.2604299555802, (16, 7): 2.8616058750000004, (16, 8): 538.8488919238888, (16, 9): 376.52284052694444, (16, 10): 300.7281810838889, (16, 11): 3.7158952178382885, (16, 12): 294.77077434194445, (16, 13): 556.5988753430554, (16, 14): 1228.526131274722, (16, 15): 2.231257877290394, (15, 7): 3.01720390821256, (15, 8): 979.4515585080555, (15, 9): 1564.1824778733335, (15, 10): 1018.206215281111, (15, 11): 541.9170581094446, (15, 12): 336.1475581652777, (15, 13): 764.1392879230556, (15, 14): 4.015594756111109, (15, 15): 509.6690150694059, (14, 7): 2.8746716811594197, (14, 8): 818.7880467329813, (14, 9): 3.8322007208333337, (14, 10): 731.1910409155555, (14, 11): 596.6873250883333, (14, 12): 412.8375621772222, (14, 13): 520.7571591841667, (14, 14): 591.1471487788889, (14, 15): 475.0035797801222, (13, 7): 2.9789540289855068, (13, 8): 639.7969894552778, (13, 9): 637.3779882011111, (13, 10): 506.29437398361114, (13, 11): 353.42218859972223, (13, 12): 305.01100706444447, (13, 13): 340.25735466222227, (13, 14): 3.8758763275000008, (13, 15): 543.8317377257081, (12, 7): 2.906306302884616, (12, 8): 542.9521286569444, (12, 9): 463.0875075130556, (12, 10): 379.6890530136111, (12, 11): 286.1033081977778, (12, 12): 178.39918646277772, (12, 13): 170.33147364083334, (12, 14): 365.98617212138885, (12, 15): 405.7444252476402, (9, 7): 2.928884572115384, (9, 8): 720.7984582758332, (9, 9): 3.8483128874999992, (9, 10): 341.41119732944446, (9, 11): 270.2110689561111, (9, 12): 247.2861200113889, (9, 13): 3.6537818458333327, (9, 14): 306.4674261755556, (9, 15): 2.074388856746252, (8, 7): 2.8890238550724634, (8, 8): 528.4556908091666, (8, 9): 547.9114031425, (8, 10): 500.7944513597222, (8, 11): 3.8512908269444446, (8, 12): 218.3805275261111, (8, 13): 333.57671157, (8, 14): 569.8214435466666, (8, 15): 192.89880216601884, (7, 7): 2.858327285024154, (7, 8): 4.12684743635353, (7, 9): 443.1686869602776, (7, 10): 240.09031229000004, (7, 11): 371.5734720022222, (7, 12): 218.1925328358334, (7, 13): 368.90455026333336, (7, 14): 361.331266850278, (7, 15): 514.2903071515823, (6, 7): 2.8794815652173913, (6, 8): 607.3809963869444, (6, 9): 431.1556074402779, (6, 10): 356.52103546333336, (6, 11): 446.5897162197221, (6, 12): 496.7547147022222, (6, 13): 806.7499224338891, (6, 14): 3.336047919399667, (6, 15): 1.7095653892282068, (5, 7): 2.923072471153846, (5, 8): 637.6159190302777, (5, 9): 419.02678446083337, (5, 10): 448.8138195866668, (5, 11): 419.91707975833333, (5, 12): 428.1129128058334, (5, 13): 413.6354027394445, (5, 14): 548.7387238566666, (5, 15): 469.7728208978345, (2, 7): 2.8789869371980683, (2, 8): 437.0934774280554, (2, 9): 343.60157044583343, (2, 10): 351.74249603000004, (2, 11): 203.51295713194446, (2, 12): 251.80848501055553, (2, 13): 321.7246431113889, (2, 14): 230.65422133611108, (2, 15): 573.934631541921}

_x = np.array([k[0] for k in data.keys()])
_y = np.array([k[1] for k in data.keys()])
_z = np.array([v for v in data.values()])

X,Y = np.meshgrid(_x,_y)

sizeY = max(_y) - min(_y)
sizeX = max(_x) - min(_x)

print('data size', len(data), "sizeX", sizeX, "sizeY", sizeY, " * ", sizeX * sizeY)
print('X',X)
print('Y',Y)

Z = np.zeros(sizeX * sizeY)
Z.shape = (sizeX, sizeY)
print('Z', Z)


fig = plt.figure('3D surface')
ax = fig.add_subplot(111, projection='3d')
ax.plot_wireframe(X, Y, Z)
plt.show()