Python曲面绘制

我有以下表格数据（请看图片） 我想用python绘制一个曲面图。使用matplotlib中的曲面打印

import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import numpy as np

fig = plt.figure()
ax = fig.gca(projection='3d')
X=[2,3,5,8,20,30,50,80,100,150,175,200,250,300]
Y=[2,3,4,5,10,15,20,30,40,50,80,100,125,150,175,200]
Y,X=np.meshgrid(Y,X)
Z=np.array([
[0.2885307,0.269452,0.259193,0.2548041,0.2731868,0.4801551,0.7992361,1.7577641,3.2611327,5.428839,19.647976,37.59729,78.0871,152.21466,268.14572,0],
[0.2677955,0.2538363,0.2380033,0.2306999,0.4779794,0.9251045,1.5448972,3.508644,6.4968576,11.252151,0,0,0,0,0,0],
[0.2432982,0.2283371,0.2514196,0.3392502,0,0,0,0,0,0,0,0,0,0,0,0],
[0.2342575,0.3158406,0.4770729, 0.6795485,2.353042, 5.260077,9.78172,25.87004,59.52568, 0,0,0,0,0,0,0],
[0.6735384, 1.3873291,2.346506, 3.5654,0,0,0,0,0,0,0,0,0,0,0,0],
[1.3584715, 2.9405127,5.096819,8.155857,0,0,0,0,0,0,0,0,0,0,0,0],
[3.558062,8.216592,15.768077,27.386694,0,0,0,0,0,0,0,0,0,0,0,0],
[9.537899,25.202589,58.20041,0,0,0,0,0,0,0,0,0,0,0,0,0],
[16.083374,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[54.936775,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[89.185974,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]])

my_col = cm.jet(Z/np.amax(Z))
surf = ax.plot_surface(X, Y, Z,cmap=cm.coolwarm,linewidth=0, antialiased=False)
ax.set_zlim(0, 300)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))
fig.colorbar(surf, shrink=0.5, aspect=5)
plt.show()

我得到了这样一个情节

这是正确的，但不是很有吸引力或直观。我怎样才能使可视化更平滑和清晰？请注意，我的数据中有许多空白。我应该为空格使用“zero”还是“nan”（不是数字）？对于相同的数据，excel显示了更好的图形。

---

为了使python绘图更具视觉吸引力，我非常感谢您的输入。

matplotlib和excel绘图之间的区别在于matplotlib是以线性比例绘制的，而excel是对数的（或者看起来像对数轴但实际上不是对数轴的东西，请参见下文）。因此，在matplotlib中，坡度看起来非常陡峭，但在excel中，坡度被原木显著拉伸

不幸的是，matplotlib还没有在3D中运行良好的日志轴。我不知道这是为什么，但这是一个严重的缺点。如果在进行绘图之前获取X和Y数据的

log10

，则可以看到类似于Excel的绘图。您还可以进一步DIY您自己的日志轴，但我刚刚使用tick格式化程序对其进行了简化

编辑：
回到这个问题后，我意识到Excel绘图实际上并没有显示对数轴，而只是绘制

X

和

Y

沿轴等间距给出的值，即使这些值没有明确的数学级数

需要注意的是，这并不是数据的良好表示，因为它给人的印象是它是对数的（对于提供的特定数据），但实际上不是，尽管需要非常仔细的检查才能看到它。在这里，相邻数字之间的间隔甚至不是单调的

所以我不鼓励这种表示法，但为了重现Excel绘图，我建议制作等距数据，但用不同的数字标记（仅此一句就足以阻止这种方法）。但以下是代码和方法：

---

如果要显示为

X

和

Y

指定的特定数字，一种解决方案是使用对数轴进行绘制（因为数字的间隔非常近似于对数），然后通过轴上的线专门绘制数字，或者，不要用这些数字代替通常的规则间隔数字。（但要将它们绘制为轴值，和以固定的间隔将它们隔开，这是一个问题。）

生成前一个绘图的代码在哪里？嗨，很抱歉。我现在加上了，没关系。。。我认为错误在于数据。你的情节和《期待》很相似。你确定所有这些零都存在于数据中吗？我不完全理解你的评论。所有这些零都在那里。我的意思是，这些数据在表格中我知道我的表格有很多空白。我正试图从这些数据中画出一个像样的图表。例如，我可以删除最后3行。但在绘图、着色风格等方面有好的选择吗？谢谢你的回答，我有点怀疑。是否可以显示X轴和Y轴上的所有值，而不是仅显示10和100？@SandeepParamenshwara：是的，这是可能的，但很难找到一个通用的解决方案。matplotlib需要做的是在3D中记录轴。（在那之前，如果你需要一个特定绘图的答案，根据我已经发布的内容尝试一些东西可能是合理的，如果你有问题，回来问一个新问题，并提供一些细节，例如，你是否需要：适用于所有范围、出版物质量位置、刻度的良好整数值等等。也许有人会这么做是的，但这是一个太大的问题，不能只添加到这个问题和答案上。）@SandeepParameshwara：我又看了一遍，在阅读你最初发布的情节时犯了一个错误。我认为，这个错误正好说明了为什么这些图不应该以您的问题中的方式呈现，并且真正的

log10

是正确的方法，但我还是想纠正这个错误，所以我已经发布了它。

import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter, FuncFormatter
from mpl_toolkits.mplot3d import axes3d
import numpy as np

def format_log(x, pos=None):
    x1 = 10**x
    s = "%.3f" % x1
    return s[:-4] if s[-3:]=="000" else " "

fig = plt.figure()
ax = fig.gca(projection='3d')
X=[2,3,5,8,20,30,50,80,100,150,175,200,250,300]
Y=[2,3,4,5,10,15,20,30,40,50,80,100,125,150,175,200]
X = np.log10(np.array(X))
Y = np.log10(np.array(Y))
Y,X=np.meshgrid(Y,X)
Z=np.array([
[0.2885307,0.269452,0.259193,0.2548041,0.2731868,0.4801551,0.7992361,1.7577641,3.2611327,5.428839,19.647976,37.59729,78.0871,152.21466,268.14572,0],
[0.2677955,0.2538363,0.2380033,0.2306999,0.4779794,0.9251045,1.5448972,3.508644,6.4968576,11.252151,0,0,0,0,0,0],
[0.2432982,0.2283371,0.2514196,0.3392502,0,0,0,0,0,0,0,0,0,0,0,0],
[0.2342575,0.3158406,0.4770729, 0.6795485,2.353042, 5.260077,9.78172,25.87004,59.52568, 0,0,0,0,0,0,0],
[0.6735384, 1.3873291,2.346506, 3.5654,0,0,0,0,0,0,0,0,0,0,0,0],
[1.3584715, 2.9405127,5.096819,8.155857,0,0,0,0,0,0,0,0,0,0,0,0],
[3.558062,8.216592,15.768077,27.386694,0,0,0,0,0,0,0,0,0,0,0,0],
[9.537899,25.202589,58.20041,0,0,0,0,0,0,0,0,0,0,0,0,0],
[16.083374,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[54.936775,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[89.185974,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]])
my_col = cm.jet(Z/np.amax(Z))
surf = ax.plot_surface(X, Y, Z,cmap=cm.coolwarm)
ax.set_zlim(0, 300)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))
ax.xaxis.set_major_formatter(FuncFormatter(format_log))
ax.yaxis.set_major_formatter(FuncFormatter(format_log))
fig.colorbar(surf, shrink=0.5, aspect=5)
plt.show()

fig = plt.figure()
ax = fig.gca(projection='3d')
x=[2,3,5,8,20,30,50,80,100,150,175,200,250,300]
y=[2,3,4,5,10,15,20,30,40,50,80,100,125,150,175,200]

Y,X=np.meshgrid(range(len(y)),range(len(x)))
Z=np.array([
[0.2885307,0.269452,0.259193,0.2548041,0.2731868,0.4801551,0.7992361,1.7577641,3.2611327,5.428839,19.647976,37.59729,78.0871,152.21466,268.14572,0],
[0.2677955,0.2538363,0.2380033,0.2306999,0.4779794,0.9251045,1.5448972,3.508644,6.4968576,11.252151,0,0,0,0,0,0],
[0.2432982,0.2283371,0.2514196,0.3392502,0,0,0,0,0,0,0,0,0,0,0,0],
[0.2342575,0.3158406,0.4770729, 0.6795485,2.353042, 5.260077,9.78172,25.87004,59.52568, 0,0,0,0,0,0,0],
[0.6735384, 1.3873291,2.346506, 3.5654,0,0,0,0,0,0,0,0,0,0,0,0],
[1.3584715, 2.9405127,5.096819,8.155857,0,0,0,0,0,0,0,0,0,0,0,0],
[3.558062,8.216592,15.768077,27.386694,0,0,0,0,0,0,0,0,0,0,0,0],
[9.537899,25.202589,58.20041,0,0,0,0,0,0,0,0,0,0,0,0,0],
[16.083374,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[54.936775,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[89.185974,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]])
my_col = cm.jet(Z/np.amax(Z))
surf = ax.plot_surface(X, Y, Z,cmap=cm.coolwarm)
ax.tick_params(axis='both', which='major', labelsize=6)
ax.set_zlim(0, 300)
ax.xaxis.set_major_locator(IndexLocator(1, 0))
ax.xaxis.set_major_formatter(FixedFormatter([repr(v) for v in x]))
ax.yaxis.set_major_locator(IndexLocator(1, 0))
ax.yaxis.set_major_formatter(FixedFormatter([repr(v) for v in y]))
fig.colorbar(surf, shrink=0.5, aspect=5)