Is it possible to parser change marker size?

[LiuCMU]

I encountered the following error when parsing markersize:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-8-cfa7c3067ad6> in <module>
     14 fig = plt.figure(figsize=(8, 6), dpi=100)
     15 ax = fig.add_subplot(1, 1, 1, projection="scatter_density")
---> 16 density = ax.scatter_density(y_hat, y, cmap=white_viridis, markersize=10)
     17 fig.colorbar(density, label='Number of points per pixel')
     18 ax.grid()

~/miniconda3/envs/yields/lib/python3.6/site-packages/mpl_scatter_density/scatter_density_axes.py in scatter_density(self, x, y, dpi, downres_factor, color, cmap, alpha, norm, **kwargs)
     51         scatter = ScatterDensityArtist(self, x, y, dpi=dpi, downres_factor=downres_factor,
     52                                        color=color, cmap=cmap,
---> 53                                        alpha=alpha, norm=norm, **kwargs)
     54         self.add_artist(scatter)
     55 

~/miniconda3/envs/yields/lib/python3.6/site-packages/mpl_scatter_density/scatter_density_artist.py in __init__(self, ax, x, y, downres_factor, c, **kwargs)
     57         super(ScatterDensityArtist, self).__init__(ax,
     58                                                    histogram2d_func=self.histogram2d_helper,
---> 59                                                    **kwargs)
     60 
     61     def set_xy(self, x, y):

~/miniconda3/envs/yields/lib/python3.6/site-packages/mpl_scatter_density/generic_density_artist.py in __init__(self, ax, dpi, color, vmin, vmax, norm, histogram2d_func, update_while_panning, **kwargs)
     57                                                    dpi=dpi,
     58                                                    update_while_panning=update_while_panning,
---> 59                                                    **kwargs)
     60 
     61         if color is not None:

~/miniconda3/envs/yields/lib/python3.6/site-packages/mpl_scatter_density/base_image_artist.py in __init__(self, ax, dpi, array_func, update_while_panning, **kwargs)
     52     def __init__(self, ax, dpi=72, array_func=None, update_while_panning=True, **kwargs):
     53 
---> 54         super(BaseImageArtist, self).__init__(ax, **kwargs)
     55 
     56         self._array_func = array_func

~/miniconda3/envs/yields/lib/python3.6/site-packages/matplotlib/image.py in __init__(self, ax, cmap, norm, interpolation, origin, extent, filternorm, filterrad, resample, **kwargs)
    897             filterrad=filterrad,
    898             resample=resample,
--> 899             **kwargs
    900         )
    901 

~/miniconda3/envs/yields/lib/python3.6/site-packages/matplotlib/image.py in __init__(self, ax, cmap, norm, interpolation, origin, filternorm, filterrad, resample, **kwargs)
    259         self._imcache = None
    260 
--> 261         self.update(kwargs)
    262 
    263     def __getstate__(self):

~/miniconda3/envs/yields/lib/python3.6/site-packages/matplotlib/artist.py in update(self, props)
   1004 
   1005         with cbook._setattr_cm(self, eventson=False):
-> 1006             ret = [_update_property(self, k, v) for k, v in props.items()]
   1007 
   1008         if len(ret):

~/miniconda3/envs/yields/lib/python3.6/site-packages/matplotlib/artist.py in <listcomp>(.0)
   1004 
   1005         with cbook._setattr_cm(self, eventson=False):
-> 1006             ret = [_update_property(self, k, v) for k, v in props.items()]
   1007 
   1008         if len(ret):

~/miniconda3/envs/yields/lib/python3.6/site-packages/matplotlib/artist.py in _update_property(self, k, v)
   1000                 if not callable(func):
   1001                     raise AttributeError('{!r} object has no property {!r}'
-> 1002                                          .format(type(self).__name__, k))
   1003                 return func(v)
   1004 

AttributeError: 'ScatterDensityArtist' object has no property 'markersize'

The code is like this, where y and y_hat can be replaced by random lists for reproduction purpose:

from matplotlib.colors import LinearSegmentedColormap

# "Viridis-like" colormap with white background
white_viridis = LinearSegmentedColormap.from_list('white_viridis', [
    (0, '#ffffff'),
    (1e-20, '#440053'),
    (0.2, '#404388'),
    (0.4, '#2a788e'),
    (0.6, '#21a784'),
    (0.8, '#78d151'),
    (1, '#fde624'),
], N=256)

fig = plt.figure(figsize=(8, 6), dpi=100)
ax = fig.add_subplot(1, 1, 1, projection="scatter_density")
density = ax.scatter_density(y_hat, y, cmap=white_viridis, markersize=10)
fig.colorbar(density, label='Number of points per pixel')
ax.grid()
ax.set_xlim(0, 100)
ax.set_ylim(0, 100)
ax.set_xlabel("Predicted yields(Yield-BERT)")
ax.set_ylabel("Observed yields")

Thanks!