plot position is giving an error about nanocompore HOT 5 CLOSED

Hi Muhammad5577,

Can you confirm for me which version of seaborn you're using?

from nanocompore.

Hi lmulroney
seaborn is v 0.11.2

from nanocompore.

Hi lmulroney
After updating to seaborn 0.12.2 i get this error now

ValueError Traceback (most recent call last)
Cell In [12], line 1
----> 1 fig, ax = db.plot_position ("YKL096W_mRNA",pos=1)

File ~/.local/lib/python3.8/site-packages/nanocompore/SampCompDB.py:865, in SampCompDB.plot_position(self, ref_id, pos, split_samples, figsize, palette, plot_style, xlim, ylim, alpha, pointSize, scatter, kde, model, gmm_levels)
863 for label, d in plot_data_dict.items():
864 if kde:
--> 865 _ = sns.kdeplot(
866 data=d["intensity"],
867 data2=d["dwell"],
868 cmap=sns.light_palette(d["color"], as_cmap=True),
869 ax=ax,
870 clip=((min(d["intensity"]), max(d["intensity"])), (min(d["dwell"]),max(d["dwell"]))))
871 if scatter:
872 _ = ax.scatter(
873 x=d["intensity"],
874 y=d["dwell"],
(...)
877 alpha=alpha,
878 s=pointSize)

File ~/.local/lib/python3.8/site-packages/seaborn/distributions.py:1717, in kdeplot(data, x, y, hue, weights, palette, hue_order, hue_norm, color, fill, multiple, common_norm, common_grid, cumulative, bw_method, bw_adjust, warn_singular, log_scale, levels, thresh, gridsize, cut, clip, legend, cbar, cbar_ax, cbar_kws, ax, **kwargs)
1713 if p.univariate:
1715 plot_kws = kwargs.copy()
-> 1717 p.plot_univariate_density(
1718 multiple=multiple,
1719 common_norm=common_norm,
1720 common_grid=common_grid,
1721 fill=fill,
1722 color=color,
1723 legend=legend,
1724 warn_singular=warn_singular,
1725 estimate_kws=estimate_kws,
1726 **plot_kws,
1727 )
1729 else:
1731 p.plot_bivariate_density(
1732 common_norm=common_norm,
1733 fill=fill,
(...)
1743 **kwargs,
1744 )

File ~/.local/lib/python3.8/site-packages/seaborn/distributions.py:937, in _DistributionPlotter.plot_univariate_density(self, multiple, common_norm, common_grid, warn_singular, fill, color, legend, estimate_kws, **plot_kws)
934 log_scale = self._log_scaled(self.data_variable)
936 # Do the computation
--> 937 densities = self._compute_univariate_density(
938 self.data_variable,
939 common_norm,
940 common_grid,
941 estimate_kws,
942 log_scale,
943 warn_singular,
944 )
946 # Adjust densities based on the multiple rule
947 densities, baselines = self._resolve_multiple(densities, multiple)

File ~/.local/lib/python3.8/site-packages/seaborn/distributions.py:349, in _DistributionPlotter._compute_univariate_density(self, data_variable, common_norm, common_grid, estimate_kws, log_scale, warn_singular)
345 try:
346 if not singular:
347 # Convoluted approach needed because numerical failures
348 # can manifest in a few different ways.
--> 349 density, support = estimator(observations, weights=weights)
350 except np.linalg.LinAlgError:
351 singular = True

File ~/.local/lib/python3.8/site-packages/seaborn/_statistics.py:192, in KDE.call(self, x1, x2, weights)
190 """Fit and evaluate on univariate or bivariate data."""
191 if x2 is None:
--> 192 return self._eval_univariate(x1, weights)
193 else:
194 return self._eval_bivariate(x1, x2, weights)

File ~/.local/lib/python3.8/site-packages/seaborn/_statistics.py:151, in KDE._eval_univariate(self, x, weights)
149 support = self.support
150 if support is None:
--> 151 support = self.define_support(x, cache=False)
153 kde = self._fit(x, weights)
155 if self.cumulative:

File ~/.local/lib/python3.8/site-packages/seaborn/_statistics.py:127, in KDE.define_support(self, x1, x2, weights, cache)
125 """Create the evaluation grid for a given data set."""
126 if x2 is None:
--> 127 support = self._define_support_univariate(x1, weights)
128 else:
129 support = self._define_support_bivariate(x1, x2, weights)

File ~/.local/lib/python3.8/site-packages/seaborn/_statistics.py:101, in KDE._define_support_univariate(self, x, weights)
99 kde = self._fit(x, weights)
100 bw = np.sqrt(kde.covariance.squeeze())
--> 101 grid = self._define_support_grid(
102 x, bw, self.cut, self.clip, self.gridsize
103 )
104 return grid

File ~/.local/lib/python3.8/site-packages/seaborn/_statistics.py:93, in KDE._define_support_grid(self, x, bw, cut, clip, gridsize)
91 clip_lo = -np.inf if clip[0] is None else clip[0]
92 clip_hi = +np.inf if clip[1] is None else clip[1]
---> 93 gridmin = max(x.min() - bw * cut, clip_lo)
94 gridmax = min(x.max() + bw * cut, clip_hi)
95 return np.linspace(gridmin, gridmax, gridsize)

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

from nanocompore.

It looks like seaborn changed the way that the do internal indexing in the versions you're using compared to the version recommended in nanocompore. Can you try using version 0.11.0 instead of 0.11.2 or 0.12.2?

Also, just to make sure, do you have data at position 1 of YKL096W_mRNA or pos 456 of YAL003W_mRNA? It might be throwing the error due to no data at those positions?

from nanocompore.

Hi lmulroney
thank you for your help.
after reinstalling seaborn 0.11 it worked !
cheers for the support !

from nanocompore.