SStar1314
commented
6 years ago @bois93 打开reg_utils.py 文件，修改load_2D_dataset 函数， 把其中一行换成 ： plt.scatter(train_X[0, :], train_X[1, :], c=np.squeeze(train_Y), s=40, cmap=plt.cm.Spectral); 重新运行jupyter notebook 就可以了
你好，我在运行的时候一直遇到这样的问题 比如第二课，第一周的Regularization train_X, train_Y, test_X, test_Y = load_2D_dataset() 哎困扰我很久了，一直没有找到原因
TypeError Traceback (most recent call last) c:\users\administrator\appdata\local\programs\python\python36-32\lib\site-packages\matplotlib\colors.py in to_rgba(c, alpha) 131 try: --> 132 rgba = _colors_full_map.cache[c, alpha] 133 except (KeyError, TypeError): # Not in cache, or unhashable.
TypeError: unhashable type: 'numpy.ndarray'
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last) c:\users\administrator\appdata\local\programs\python\python36-32\lib\site-packages\matplotlib\axes_axes.py in scatter(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, **kwargs) 3985 # must be acceptable as PathCollection facecolors -> 3986 colors = mcolors.to_rgba_array(c) 3987 except ValueError:
c:\users\administrator\appdata\local\programs\python\python36-32\lib\site-packages\matplotlib\colors.py in to_rgba_array(c, alpha) 232 for i, cc in enumerate(c): --> 233 result[i] = to_rgba(cc, alpha) 234 return result
c:\users\administrator\appdata\local\programs\python\python36-32\lib\site-packages\matplotlib\colors.py in to_rgba(c, alpha) 133 except (KeyError, TypeError): # Not in cache, or unhashable. --> 134 rgba = _to_rgba_no_colorcycle(c, alpha) 135 try:
c:\users\administrator\appdata\local\programs\python\python36-32\lib\site-packages\matplotlib\colors.py in _to_rgba_no_colorcycle(c, alpha) 188 if len(c) not in [3, 4]: --> 189 raise ValueError("RGBA sequence should have length 3 or 4") 190 if len(c) == 3 and alpha is None:
ValueError: RGBA sequence should have length 3 or 4
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last) in () ----> 1 train_X, train_Y, test_X, test_Y = load_2D_dataset()
~\Desktop\deeplearning.ai_JupyterNotebooks-master\deeplearning.ai_JupyterNotebooks-master\2_Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization\week1\2_Regularization\reg_utils.py in load_2D_dataset() 332 test_Y = data['yval'].T 333 --> 334 plt.scatter(train_X[0, :], train_X[1, :], c=train_Y, s=40, cmap=plt.cm.Spectral); 335 336 return train_X, train_Y, test_X, test_Y
c:\users\administrator\appdata\local\programs\python\python36-32\lib\site-packages\matplotlib\pyplot.py in scatter(x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, hold, data, kwargs) 3376 vmin=vmin, vmax=vmax, alpha=alpha, 3377 linewidths=linewidths, verts=verts, -> 3378 edgecolors=edgecolors, data=data, kwargs) 3379 finally: 3380 ax._hold = washold
c:\users\administrator\appdata\local\programs\python\python36-32\lib\site-packages\matplotlibinit.py in inner(ax, *args, *kwargs) 1715 warnings.warn(msg % (label_namer, func.name), 1716 RuntimeWarning, stacklevel=2) -> 1717 return func(ax, args, **kwargs) 1718 pre_doc = inner.doc 1719 if pre_doc is None:
c:\users\administrator\appdata\local\programs\python\python36-32\lib\site-packages\matplotlib\axes_axes.py in scatter(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, **kwargs) 3989 msg = ("c of shape {0} not acceptable as a color sequence " 3990 "for x with size {1}, y with size {2}") -> 3991 raise ValueError(msg.format(c.shape, x.size, y.size)) 3992 else: 3993 colors = None # use cmap, norm after collection is created
ValueError: c of shape (1, 211) not acceptable as a color sequence for x with size 211, y with size 211