现在我有一个名为 (1024, 1024) 的 NumPy 数组field，它存储在一个 .bigfile 中。我想通过使用在 xy 平面上可视化它的值plt.imshow。顺便说一句，最小值field是0.0，最大值是89297.414。这是这段代码的片段。
# 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')
此代码运行后，ValueError:minvalue must be positive发生了。
我猜是最小值0.0导致了错误，所以我设置了field += 0.001. 但是，它没有用，错误仍然存在。
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