Flotilla fails with ValueError while executing "plot_pca" command #327

shassathe · 2015-12-09T22:56:03Z

I was able to generate a flotilla study with my data successfully. I am looking to generate pca plots using the "plot_pca" command:

%matplotlib inline
viz = stem_study.plot_pca(show_vectors=False, markersize=15)

However, "plot_pca" returns a ValueError with the following prompt

ValueError                                Traceback (most recent call last)
<ipython-input-12-4fda588d8572> in <module>()
      1 get_ipython().magic(u'matplotlib inline')
----> 2 viz = stem_study.plot_pca(show_vectors=False, markersize=15)
      3 #plt.savefig('/home/shsathe/projects/sebastian_run2/Paper_Figures/Stem_Cells_PCA.png', format='png')

/home/shsathe/anaconda/lib/python2.7/site-packages/flotilla-0.3.0-py2.7.egg/flotilla/study.pyc in plot_pca(self, data_type, x_pc, y_pc, sample_subset, feature_subset, title, featurewise, plot_violins, show_point_labels, reduce_kwargs, color_samples_by, bokeh, most_variant_features, std_multiplier, scale_by_variance, **kwargs)
    860                 bokeh=bokeh, most_variant_features=most_variant_features,
    861                 scale_by_variance=scale_by_variance,
--> 862                 **kwargs)
    863 
    864         elif "splicing".startswith(data_type):

/home/shsathe/anaconda/lib/python2.7/site-packages/flotilla-0.3.0-py2.7.egg/flotilla/data_model/base.pyc in plot_pca(self, **kwargs)
    597         """Call ``plot_dimensionality_reduction`` with PCA specifically"""
    598         return self.plot_dimensionality_reduction(reducer=DataFramePCA,
--> 599                                                   **kwargs)
    600 
    601     def _subset(self, data, sample_ids=None, feature_ids=None,

/home/shsathe/anaconda/lib/python2.7/site-packages/flotilla-0.3.0-py2.7.egg/flotilla/data_model/base.pyc in plot_dimensionality_reduction(self, x_pc, y_pc, sample_ids, feature_ids, featurewise, reducer, plot_violins, groupby, label_to_color, label_to_marker, order, reduce_kwargs, title, most_variant_features, std_multiplier, scale_by_variance, **plotting_kwargs)
    592         # **plotting_kwargs)
    593         return visualized.plot(title=title,
--> 594                                plot_violins=plot_violins, **plotting_kwargs)
    595 
    596     def plot_pca(self, **kwargs):

/home/shsathe/anaconda/lib/python2.7/site-packages/flotilla-0.3.0-py2.7.egg/flotilla/visualize/decomposition.pyc in plot(self, ax, title, plot_violins, show_point_labels, show_vectors, show_vector_labels, markersize, legend, bokeh, metadata, plot_loadings, n_components)
    284                 self.ax_empty.axis('off')  # self.fig_reduced = plt.gcf()
    285 
--> 286                 self.plot_loadings_heatmap(n_components=n_components)
    287 
    288             else:

/home/shsathe/anaconda/lib/python2.7/site-packages/flotilla-0.3.0-py2.7.egg/flotilla/visualize/decomposition.pyc in plot_loadings_heatmap(self, n_features, n_components)
    523         ymin = np.zeros(ymax.shape)
    524         x = np.arange(ymax.shape[0])
--> 525         self.ax_explained_variance.plot(ymax, 'o-', color='#262626')
    526         self.ax_explained_variance.fill_between(x, ymin, ymax,
    527                                                 color='lightgrey')

/home/shsathe/anaconda/lib/python2.7/site-packages/matplotlib/__init__.pyc in inner(ax, *args, **kwargs)
   1809                     warnings.warn(msg % (label_namer, func.__name__),
   1810                                   RuntimeWarning, stacklevel=2)
-> 1811             return func(ax, *args, **kwargs)
   1812         pre_doc = inner.__doc__
   1813         if pre_doc is None:

/home/shsathe/anaconda/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in plot(self, *args, **kwargs)
   1426 
   1427         for line in self._get_lines(*args, **kwargs):
-> 1428             self.add_line(line)
   1429             lines.append(line)
   1430 

/home/shsathe/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.pyc in add_line(self, line)
   1697             line.set_clip_path(self.patch)
   1698 
-> 1699         self._update_line_limits(line)
   1700         if not line.get_label():
   1701             line.set_label('_line%d' % len(self.lines))

/home/shsathe/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.pyc in _update_line_limits(self, line)
   1708         Figures out the data limit of the given line, updating self.dataLim.
   1709         """
-> 1710         path = line.get_path()
   1711         if path.vertices.size == 0:
   1712             return

/home/shsathe/anaconda/lib/python2.7/site-packages/matplotlib/lines.pyc in get_path(self)
    924         """
    925         if self._invalidy or self._invalidx:
--> 926             self.recache()
    927         return self._path
    928 

/home/shsathe/anaconda/lib/python2.7/site-packages/matplotlib/lines.pyc in recache(self, always)
    609                 x = ma.asarray(xconv, np.float_).filled(np.nan)
    610             else:
--> 611                 x = np.asarray(xconv, np.float_)
    612             x = x.ravel()
    613         else:

/home/shsathe/anaconda/lib/python2.7/site-packages/numpy/core/numeric.pyc in asarray(a, dtype, order)
    472 
    473     """
--> 474     return array(a, dtype, copy=False, order=order)
    475 
    476 def asanyarray(a, dtype=None, order=None):

ValueError: could not convert string to float: pc_5

The text was updated successfully, but these errors were encountered:

olgabot · 2015-12-12T01:54:05Z

Hmm I'm not sure exactly what the error is here. I'll look into it.

LeenMachine · 2016-01-19T18:26:55Z

I have the same issue as above

On Fri, Dec 11, 2015 at 5:54 PM, Olga Botvinnik notifications@github.com
wrote:

Hmm I'm not sure exactly what the error is here. I'll look into it.

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Reply to this email directly or view it on GitHub
#327 (comment).

olgabot · 2016-01-19T21:18:55Z

can either of you do "study.save('studyname')" and zip the folder it
creates in ~/flotilla_projects and send it to me?

On Tue, Jan 19, 2016 at 10:26 AM Leen notifications@github.com wrote:

I have the same issue as above

On Fri, Dec 11, 2015 at 5:54 PM, Olga Botvinnik notifications@github.com
wrote:

Hmm I'm not sure exactly what the error is here. I'll look into it.

—
Reply to this email directly or view it on GitHub
#327 (comment).

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#327 (comment).

LeenMachine · 2016-01-27T18:43:41Z

Hey sorry Olga, did anyone get back to you?

If not I can do this.

I need to get this working again.

Thanks,

Leen

On Tue, Jan 19, 2016 at 1:18 PM, Olga Botvinnik notifications@github.com
wrote:

can either of you do "study.save('studyname')" and zip the folder it
creates in ~/flotilla_projects and send it to me?

On Tue, Jan 19, 2016 at 10:26 AM Leen notifications@github.com wrote:

I have the same issue as above

On Fri, Dec 11, 2015 at 5:54 PM, Olga Botvinnik <
notifications@github.com>
wrote:

Hmm I'm not sure exactly what the error is here. I'll look into it.

—
Reply to this email directly or view it on GitHub
<#327 (comment)
.

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Reply to this email directly or view it on GitHub
#327 (comment).

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#327 (comment).

mlovci · 2016-01-27T19:12:14Z

Changing https://github.com/YeoLab/flotilla/blob/master/flotilla/visualize/decomposition.py#L522

from

ymax = self.explained_variance_ratio_[:n_components]

to:

ymax = self.explained_variance_ratio_[:n_components].values

fixes the problem i think.

LeenMachine · 2016-01-27T19:31:33Z

Cool can we do that? :)

Leen

On Wed, Jan 27, 2016 at 11:12 AM, Michael Lovci notifications@github.com
wrote:

Changing
https://github.com/YeoLab/flotilla/blob/master/flotilla/visualize/decomposition.py#L522

from

ymax = self.explained_variance_ratio_[:n_components]

to:

ymax = self.explained_variance_ratio_[:n_components].values

fixes the problem i think.

—
Reply to this email directly or view it on GitHub
#327 (comment).

mlovci · 2016-01-27T20:45:02Z

Go for it...
On Jan 27, 2016 11:31 AM, "Leen" notifications@github.com wrote:

Cool can we do that? :)

Leen

On Wed, Jan 27, 2016 at 11:12 AM, Michael Lovci notifications@github.com
wrote:

Changing

https://github.com/YeoLab/flotilla/blob/master/flotilla/visualize/decomposition.py#L522

from

ymax = self.explained_variance_ratio_[:n_components]

to:

ymax = self.explained_variance_ratio_[:n_components].values

fixes the problem i think.

—
Reply to this email directly or view it on GitHub
#327 (comment).

—
Reply to this email directly or view it on GitHub
#327 (comment).

LeenMachine · 2016-01-27T22:34:44Z

Fixed it. Boom.

LeenMachine closed this as completed Jan 27, 2016

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Flotilla fails with ValueError while executing "plot_pca" command #327

Flotilla fails with ValueError while executing "plot_pca" command #327

shassathe commented Dec 9, 2015

olgabot commented Dec 12, 2015

LeenMachine commented Jan 19, 2016

olgabot commented Jan 19, 2016

LeenMachine commented Jan 27, 2016

mlovci commented Jan 27, 2016

LeenMachine commented Jan 27, 2016

mlovci commented Jan 27, 2016

LeenMachine commented Jan 27, 2016

Flotilla fails with ValueError while executing "plot_pca" command #327

Flotilla fails with ValueError while executing "plot_pca" command #327

Comments

shassathe commented Dec 9, 2015

olgabot commented Dec 12, 2015

LeenMachine commented Jan 19, 2016

olgabot commented Jan 19, 2016

LeenMachine commented Jan 27, 2016

mlovci commented Jan 27, 2016

LeenMachine commented Jan 27, 2016

mlovci commented Jan 27, 2016

LeenMachine commented Jan 27, 2016