API

Apply to all mesh objects:

mesh.max
mesh.mean
mesh.median
mesh.min
mesh.shape
mesh.read_pickle
mesh.to_pickle

mesh2d

mesh2d.apply(f[, axis, inplace]) Apply a function along axis
mesh2d.diff([n]) Checked
mesh2d.dropnan() Drop NaN values and return new mesh2d.
mesh2d.extrapolate(x, *args, **kwargs) np.interp function with linear extrapolation
mesh2d.gradient([x])
mesh2d.interpolate(x[, assume_sorted]) Purpose of this method is to return a linear interpolation of a d vector for an unknown value x.
mesh2d.plot(data, *args, **kwargs)
mesh2d.polyfit([degree])
mesh2d.push([x, d]) Pushes an element/array to the array
mesh2d.read_clipboard()
mesh2d.resample(x)
mesh2d.step
mesh2d.steps
mesh2d.to_clipboard([transpose, decimal])
mesh2d.to_csv([fileName, nbreDecimales]) Export CUR data into csv

mesh3d

mesh3d.apply(f[, inplace])
mesh3d.diff([axis, n])
mesh3d.extrapolate(x, y)
mesh3d.from_pandas(obj)
mesh3d.interpolate([x, y])
mesh3d.plot([xy, filename])
mesh3d.pop([axis])
mesh3d.push([s, d, axis, inplace])
mesh3d.read_clipboard()
mesh3d.reshape([sort])
mesh3d.sort()

mesh4d

mesh4d.interpolate([x, y, z]) a
mesh4d.push([s, d, axis])
mesh4d.reshape()
mesh4d.sort()

polymesh2d

polymesh2d.resample(x)

polymesh3d

polymesh3d.resample(y)
polymesh3d.plot(*pargs, **kwargs)
polymesh3d.push(y, p)