be_viz_utils.jupyter_visualize_beps_sho not working for relaxation SHO fits

Created by: ramav87

Need to check dimensional reshaping

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TypeError Traceback (most recent call last) in () 1 step_chan = 'DC_Offset' ----> 2 px.be_viz_utils.jupyter_visualize_beps_sho(h5_sho_fit, step_chan)

~\Documents\GitHub\pycroscopy\pycroscopy\viz\be_viz_utils.py in jupyter_visualize_beps_sho(pc_sho_dset, step_chan, resp_func, resp_label, cmap) 324 bias_slider = ax_bias.axvline(x=step_ind, color='r') 325 --> 326 img_map, img_cmap = plot_map(ax_map, spatial_map.T, show_xy_ticks=None) 327 328 map_title = '{} - {}={}'.format(sho_quantity, step_chan, bias_mat[step_ind][0])

~\Documents\GitHub\pycroscopy\pycroscopy\viz\plot_utils.py in plot_map(axis, img, show_xy_ticks, show_cbar, x_size, y_size, num_ticks, stdevs, cbar_label, tick_font_size, origin, **kwargs) 430 kwargs.update({'origin': origin}) 431 --> 432 im_handle = axis.imshow(img, **kwargs) 433 434 if show_xy_ticks is True:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\matplotlib_init_.py in inner(ax, *args, **kwargs) 1843 "the Matplotlib list!)" % (label_namer, func.name), 1844 RuntimeWarning, stacklevel=2) -> 1845 return func(ax, *args, **kwargs) 1846 1847 inner.doc = _add_data_doc(inner.doc,

~\AppData\Local\Continuum\anaconda3\lib\site-packages\matplotlib\axes_axes.py in imshow(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, shape, filternorm, filterrad, imlim, resample, url, **kwargs) 5471 resample=resample, **kwargs) 5472 -> 5473 im.set_data(X) 5474 im.set_alpha(alpha) 5475 if im.get_clip_path() is None:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\matplotlib\image.py in set_data(self, A) 651 if not (self._A.ndim == 2 652 or self._A.ndim == 3 and self._A.shape[-1] in [3, 4]): --> 653 raise TypeError("Invalid dimensions for image data") 654 655 if self._A.ndim == 3:

TypeError: Invalid dimensions for image data