`ValueError` from the `matplotlib` backend

I’m just trying to plot 3 genes but I’m getting a ValueError from the matplotlib backend

features = [
]
data = df_gff3.iloc[loc_target]
start = int(data["pos_start"])
end = int(data["pos_end"])
print(end - start)
features.append(GraphicFeature(start=start, end=end, strand={"+":+1, "-":-1}[data["sense"]], color="teal", label=data["locus_tag"]))
record = GraphicRecord(sequence_length=end - start, features=features)
record.plot(figure_width=100)


# ---------------------------------------------------------------------------
# ValueError                                Traceback (most recent call last)
# ~/anaconda/envs/µ_env/lib/python3.6/site-packages/IPython/core/formatters.py in __call__(self, obj)
#     339                 pass
#     340             else:
# --> 341                 return printer(obj)
#     342             # Finally look for special method names
#     343             method = get_real_method(obj, self.print_method)

# ~/anaconda/envs/µ_env/lib/python3.6/site-packages/IPython/core/pylabtools.py in <lambda>(fig)
#     242 
#     243     if 'png' in formats:
# --> 244         png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
#     245     if 'retina' in formats or 'png2x' in formats:
#     246         png_formatter.for_type(Figure, lambda fig: retina_figure(fig, **kwargs))

# ~/anaconda/envs/µ_env/lib/python3.6/site-packages/IPython/core/pylabtools.py in print_figure(fig, fmt, bbox_inches, **kwargs)
#     126 
#     127     bytes_io = BytesIO()
# --> 128     fig.canvas.print_figure(bytes_io, **kw)
#     129     data = bytes_io.getvalue()
#     130     if fmt == 'svg':

# ~/anaconda/envs/µ_env/lib/python3.6/site-packages/matplotlib/backend_bases.py in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, **kwargs)
#    2073                     orientation=orientation,
#    2074                     bbox_inches_restore=_bbox_inches_restore,
# -> 2075                     **kwargs)
#    2076             finally:
#    2077                 if bbox_inches and restore_bbox:

# ~/anaconda/envs/µ_env/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py in print_png(self, filename_or_obj, *args, **kwargs)
#     508 
#     509         """
# --> 510         FigureCanvasAgg.draw(self)
#     511         renderer = self.get_renderer()
#     512 

# ~/anaconda/envs/µ_env/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py in draw(self)
#     394         Draw the figure using the renderer.
#     395         """
# --> 396         self.renderer = self.get_renderer(cleared=True)
#     397         # acquire a lock on the shared font cache
#     398         RendererAgg.lock.acquire()

# ~/anaconda/envs/µ_env/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py in get_renderer(self, cleared)
#     415 
#     416         if need_new_renderer:
# --> 417             self.renderer = RendererAgg(w, h, self.figure.dpi)
#     418             self._lastKey = key
#     419         elif cleared:

# ~/anaconda/envs/µ_env/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py in __init__(self, width, height, dpi)
#      85         self.width = width
#      86         self.height = height
# ---> 87         self._renderer = _RendererAgg(int(width), int(height), dpi)
#      88         self._filter_renderers = []
#      89 

# ValueError: Image size of 427363x153 pixels is too large. It must be less than 2^16 in each direction.
# <Figure size 7200x158.4 with 1 Axes>

[Zulko]

Great, happy I could be of some help! Let me know if you run into any other trouble.

[jolespin]

Haha, yea a 2.5 meter figure is a little much for what I was trying to do. Thank you so much for responding! I was almost about to recreate the wheel and was very bummed out b/c your figures already look so good.

I ended up using this edit that you suggested

sequence_length = 4653851
features = list()
positions = list()
pad = 10
for k in range(-n_peripheral, n_peripheral+1):
    data = df_gff3.iloc[loc_target+k]
    start = int(data["pos_start"])
    end = int(data["pos_end"])
    strand = {"+":+1, "-":-1}[data["sense"]]
    label = data["locus_tag"]
    feature = GraphicFeature(start=start, end=end, strand=strand, label=label)
    features.append(feature)
    positions += [start, end]
record = GraphicRecord(sequence_length=sequence_length, features=features).crop((min(positions)-pad, max(positions)+pad))
record.plot(figure_width=10)