ary = np.piecewise(源数组, 条件序列, 取值序列) 演示代码: a = np.array([70, 80, 60, 30, 40]) d = np.piecewise( a, [a < 60, a == 60, a > 60], [-1, 0, 1]) # d = [ 1 1 0 -1 -1] 矢量化 矢量化指的是用数组代替标量来操作数组里的每个元素。 numpy提供了vectorize...
class PiecewiseLinearModel(torch.nn.Module): def __init__(self, n_breaks): super(PiecewiseLinearModel, self).__init__() self.breaks = torch.nn.Parameter(torch.randn((1,n_breaks))) self.linear = torch.nn.Linear(n_breaks+1, 1) def forward(self, x): return self.linear(torch.cat([...
108 numpy.piecewise 根据条件对数组进行分段 无 numpy.piecewise(x, condlist, funclist, args, *kw) numpy.piecewise(numpy.array([1, 2, 3]), [numpy.array([1, 2, 3]) < 2, numpy.array([1, 2, 3]) >= 2], [lambda x: x2, lambda x: x3]) array([1, 4, 27]) 根据条件对数组进...
Returns the one-dimensional piecewise linear interpolant to a function(xp, fp), evaluated at x. 对一元线性函数 fp = f(xp), xp 需要单调递增,返回 x 所在位置的线性插值。 x 超过 xp 的范围时,返回边界值,除非指定 left 和 right 参数。 # 相关系数 corrcoef(x, y=None, rowvar=True, bias=<no...
By default it performs piecewise linear interpolation, which in your example seems the most suitable approach. from scipy.interpolate import griddata x = [(2,2), (1,2), (2,3), (3,2), (2,1)] y = [5,7,8,10,3] evaluate_at = [(2.7, 2.3)] # could be an array of points ...
开发者ID:pmelchior,项目名称:scarlet,代码行数:20,代码来源:interpolation.py 示例2: B_0123 ▲点赞 6▼ # 需要导入模块: import numpy [as 别名]# 或者: from numpy importpiecewise[as 别名]defB_0123(x, der=0):"""A quadratic B-spline function B(x | 0, 1, 2, 3)."""x = np.atleast...
It will return the one-dimensional piecewise linear interpolant values to the function given with distinct data points xp and fp, which is evaluated at x. Parameters x: it is a one-dimensional array for which we need to do interpolation. It contains the x coordinates of the interpolated data...
F = piecewise(scale, ((-np.inf, xmn),0), ((xmn,xmx), scale/2* (1+ cos(np.pi*(0.5- (identity - offset)/width)))ifis_const_potential(f):returnconst_potential(F.value(f.c))elifis_identity_potential(f):returnFelse:returncompose(F, f) 开发...
_iops self._cpu_count = int( numpy.piecewise([value], [[value <= 15000], [ (value > 15000) & (value <= 25000) ], [value > 25000]], [lambda x: 1, lambda x: 16, lambda x: 32])) elif self._provider == AWS: self._cpu_count = 2 Example #3...
浏览完整代码 来源:consistency.py 项目:costika1234/PiecewiseLinear 示例18 def resample(self, dx, dy, method='nearest'): """ Resample array to have spacing `dx`, `dy'. The grid origin remains in the same position. Parameters --- dx : float cell dimension 1 dy : float cell dimension 2...