Why `ValueError: minvalue must be positive` occurred after that I run `plt.savefig()`?

Question

Now I have one (1024, 1024) NumPy array named field which is stored in a .bigfile. And I want to visualize its values on the x-y plane by using plt.imshow. By the way, the minimum of field is 0.0, the maximum is 89297.414.Here is a snippet of this code.

# plot in the linuxremote server
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt

import bigfile

with bigfile.File('filename.bigfile') as bf:
     shape = bf['Field'].attrs['ndarray.shape']
     field = bf['Field'][:].reshape(shape)

plt.imshow(field, norm=mpl.colors.LogNorm());
plt.savefig('field.pdf')

After this code has run, ValueError:minvalue must be positive occured.

I guess that the the minimum value 0.0 caused the error, so I set field += 0.001. However, it is useless and the error still occurs.

---

ValueError                                Traceback (most recent call last)
<ipython-input-20-a10e1bbeb736> in <module>
----> 1 plt.savefig('field.pdf')

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/pyplot.py in savefig(*args, **kwargs)
    841 def savefig(*args, **kwargs):
    842     fig = gcf()
--> 843     res = fig.savefig(*args, **kwargs)
    844     fig.canvas.draw_idle()   # need this if 'transparent=True' to reset colors
    845     return res

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/figure.py in savefig(self, fname, transparent, **kwargs)
   2309                 patch.set_edgecolor('none')
   2310 
-> 2311         self.canvas.print_figure(fname, **kwargs)
   2312 
   2313         if transparent:

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/backend_bases.py in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2208 
   2209             try:
-> 2210                 result = print_method(
   2211                     filename,
   2212                     dpi=dpi,

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/backend_bases.py in wrapper(*args, **kwargs)
   1637             kwargs.pop(arg)
   1638 
-> 1639         return func(*args, **kwargs)
   1640 
   1641     return wrapper

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/backends/backend_pdf.py in print_pdf(self, filename, dpi, bbox_inches_restore, metadata)
   2591                 RendererPdf(file, dpi, height, width),
   2592                 bbox_inches_restore=bbox_inches_restore)
-> 2593             self.figure.draw(renderer)
   2594             renderer.finalize()
   2595             if not isinstance(filename, PdfPages):

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
     39                 renderer.start_filter()
     40 
---> 41             return draw(artist, renderer, *args, **kwargs)
     42         finally:
     43             if artist.get_agg_filter() is not None:

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/figure.py in draw(self, renderer)
   1861 
   1862             self.patch.draw(renderer)
-> 1863             mimage._draw_list_compositing_images(
   1864                 renderer, self, artists, self.suppressComposite)
   1865 

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/image.py in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    129     if not_composite or not has_images:
    130         for a in artists:
--> 131             a.draw(renderer)
    132     else:
    133         # Composite any adjacent images together

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
     39                 renderer.start_filter()
     40 
---> 41             return draw(artist, renderer, *args, **kwargs)
     42         finally:
     43             if artist.get_agg_filter() is not None:

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/cbook/deprecation.py in wrapper(*inner_args, **inner_kwargs)
    409                          else deprecation_addendum,
    410                 **kwargs)
--> 411         return func(*inner_args, **inner_kwargs)
    412 
    413     return wrapper

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/axes/_base.py in draw(self, renderer, inframe)
   2746             renderer.stop_rasterizing()
   2747 
-> 2748         mimage._draw_list_compositing_images(renderer, self, artists)
   2749 
   2750         renderer.close_group('axes')

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/image.py in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    153                 image_group.append(a)
    154             else:
--> 155                 flush_images()
    156                 a.draw(renderer)
    157         flush_images()

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/image.py in flush_images()
    139                 image_group[0].draw(renderer)
    140             elif len(image_group) > 1:
--> 141                 data, l, b = composite_images(image_group, renderer, mag)
    142                 if data.size != 0:
    143                     gc = renderer.new_gc()

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/image.py in composite_images(images, renderer, magnification)
     87     bboxes = []
     88     for image in images:
---> 89         data, x, y, trans = image.make_image(renderer, magnification)
     90         if data is not None:
     91             x *= magnification

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/image.py in make_image(self, renderer, magnification, unsampled)
    920         clip = ((self.get_clip_box() or self.axes.bbox) if self.get_clip_on()
    921                 else self.figure.bbox)
--> 922         return self._make_image(self._A, bbox, transformed_bbox, clip,
    923                                 magnification, unsampled=unsampled)
    924 

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/image.py in _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification, unsampled, round_to_pixel_border)
    539                                        vmax=vrange[1],
    540                                        ):
--> 541                     output = self.norm(resampled_masked)
    542             else:
    543                 if A.shape[2] == 3:

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/colors.py in __call__(self, value, clip)
   1190 
   1191         self.autoscale_None(result)
-> 1192         self._check_vmin_vmax()
   1193         vmin, vmax = self.vmin, self.vmax
   1194         if vmin == vmax:

/opt/miniconda3/lib/python3.8/site-packages/matplotlib/colors.py in _check_vmin_vmax(self)
   1179             raise ValueError("minvalue must be less than or equal to maxvalue")
   1180         elif self.vmin <= 0:
-> 1181             raise ValueError("minvalue must be positive")
   1182 
   1183     def __call__(self, value, clip=None):

ValueError: minvalue must be positive

Answer 1

I have the same error when using plt.show(), instead of plt.savefig, and I hope that my solution could work also for you.

I discovered that in my case this error was due to the fact that I was specifying a value of vmax (parameter of imshow) that was too small compared to the maximum value of the array I was plotting.

My code reads:

ax[i].imshow(data, origin = 'lower', interpolation=None, norm = LogNorm(), vmin=min, vmax=max, cmap = cmap[i])

where vmax was some order of magnitude less than the actual maximum of data. I know that in the most recent versions of matplotlib the specification of vmin and vmax in the presence of norm is deprecated, but anyway you can specify your own limits in the norm function, if you are not using the default.

Adjusting the maximum limit solved my problem.