只需要在random.rand(k,1)前面加上np.就行了。 解决方法:centroids[:,j] = minJ + rangeJ * np.random.rand(k,1) 3.ValueError: Masked arrays must be 1-D 具体报错的地方: for cent, c, marker in zip(range(k),['r','g','b','y'],['^','o','*','s']): ax.scatter(data[cent...
6.ValueError: Masked arrays must be 1-D #原代码为re_draw.a.scatter(re_draw.rawDat[:,0], re_draw.rawDat[:,1], s = 5)#修改为re_draw.a.scatter(re_draw.rawDat[:,0].tolist(), re_draw.rawDat[:,1].tolist(), s = 5)
1、绘制图形时报错:Masked arrays must be 1-D 解决:scatter()中参数必须是1-D的array,但plot()总参数可以是矩阵。 ax.scatter(xMat[:,1].flatten().getA(),yMat.getA()) #必须是数组的形式 1. 解释: numpy的flatten()可以将二维矩阵变为一维的矩阵,但此时依然是矩阵类型。 from numpy import * a=...
elif isinstance(val, np.ndarray) and val.ndim > 1: raise ValueError("Per-column arrays must each be 1-dimensional") 当字典的值是一个numpy数组且像你的示例一样具有多个维度时,根据源代码会抛出错误。因此,使用列表非常有效,因为即使它是一个嵌套列表,列表也没有超过一个维度。
shape[1]: raise IOError('Matrix must be square') # Create mask matrix and remove low values chrArray = np.array(self.binDF['chr']) maskMatrix = chrArray != chrArray[:,None] lowValues = probMatrix.sum(axis=0) < 0.5 maskMatrix[lowValues,:] = True maskMatrix[:,lowValues] = ...
default NoneMake the interval closed with respect to the given frequency tothe 'left', 'right', or both sides (None).Returns---TimedeltaIndexNotes---Of the four parameters ``start``, ``end``, ``periods``, and ``freq``,exactly three must be specified. If ``freq`` is omitted, the...
# subtract the two numpy arrayscube1.values = cube1.values - cube2.values # export the updated cube1 to SEGYcube1.to_file('diff.segy') 面数据和立体方数据的相互操作,可以很方便地提取层面地震属性和层间地震属性。 To sample cube values into a surface can be quite useful. Both direct sampli...
index = int(min(stability * len(palette), len(palette) - 1)) ... pixel.color = palette[index % len(palette)] The function takes a MandelbrotSet instance as an argument followed by Viewport, a color palette, and a smoothing flag. The color palette must be a list of tuples with ...
def _resize(masked, new_size): """ Masked arrays can not be resized inplace, and `np.resize` and `ma.resize` are both incompatible with structured arrays. Therefore, we do all this. """ new_array = ma.zeros((new_size,), dtype=masked.dtype) length = min(len(masked), new_size)...
filled() # Compare the sorting data flag = (sorteddata[:-1] == sorteddata[1:]) # If masked data must be ignored, set the flag to false where needed if ignoremask: sortedmask = sortedbase.recordmask flag[sortedmask[1:]] = False flag = np.concatenate(([False], flag)) # We ...