##PACKAGES##
from __future__ import division
+from builtins import range
from .._externals.srm import SRM
from .procrustes import procrustes
import numpy as np
from .._shared.helpers import format_data
+from warnings import warn
##MAIN FUNCTION##
[docs]def align(data, method='hyper'):
@@ -174,11 +176,16 @@ Source code for hypertools.tools.align
data = format_data(data)
+ if data[0].shape[1]>=data[0].shape[0]:
+ warn('The number of features exceeds number of samples. This can lead \
+ to overfitting. We recommend reducing the dimensionality to be \
+ less than the number of samples prior to hyperalignment.')
+
if method=='hyper':
##STEP 0: STANDARDIZE SIZE AND SHAPE##
- sizes_0 = map(lambda x: x.shape[0], data)
- sizes_1 = map(lambda x: x.shape[1], data)
+ sizes_0 = [x.shape[0] for x in data]
+ sizes_1 = [x.shape[1] for x in data]
#find the smallest number of rows
R = min(sizes_0)
diff --git a/docs/_build/html/_modules/hypertools/tools/describe_pca.html b/docs/_build/html/_modules/hypertools/tools/describe_pca.html
index ab352158..a5b26fb8 100644
--- a/docs/_build/html/_modules/hypertools/tools/describe_pca.html
+++ b/docs/_build/html/_modules/hypertools/tools/describe_pca.html
@@ -114,6 +114,7 @@ Source code for hypertools.tools.describe_pca
##PACKAGES##
from __future__ import division
+from builtins import range
import warnings
import numpy as np
from scipy.spatial.distance import pdist
diff --git a/docs/_build/html/_modules/hypertools/tools/load.html b/docs/_build/html/_modules/hypertools/tools/load.html
new file mode 100644
index 00000000..f2a3753b
--- /dev/null
+++ b/docs/_build/html/_modules/hypertools/tools/load.html
@@ -0,0 +1,190 @@
+
+
+
+
+
+
+
+ hypertools.tools.load — hypertools 0.1.2 documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Source code for hypertools.tools.load
+import requests
+import pickle
+import pandas as pd
+import sys
+
+[docs]def load(dataset):
+ """
+ Load example data
+
+ Parameters
+ ----------
+ dataset : string
+ The name of the example dataset. `weights` is an fmri dataset comprised of
+ 36 subjects. For each subject, the rows are fMRI measurements and the columns
+ are parameters of a model fit to the fMRI data. `weights_sample` is a
+ sample of 3 subjects from that dataset. `weights_avg` is the dataset split
+ in half and averaged into two groups. `spiral` is 3D spiral to
+ highlight the `procrustes` function. `mushrooms` is an example dataset
+ comprised of features (columns) of a collection of mushroomm samples (rows).
+
+ Returns
+ ----------
+ data : Numpy Array
+ Example data
+
+ """
+ if sys.version_info[0]==3:
+ pickle_options = {
+ 'encoding' : 'latin1'
+ }
+ else:
+ pickle_options = {}
+
+ if dataset is 'weights':
+ fileid = '0B7Ycm4aSYdPPREJrZ2stdHBFdjg'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pickle.loads(requests.get(url, stream=True).content, **pickle_options)
+ if dataset is 'weights_avg':
+ fileid = '0B7Ycm4aSYdPPRmtPRnBJc3pieDg'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pickle.loads(requests.get(url, stream=True).content, **pickle_options)
+ if dataset is 'weights_sample':
+ fileid = '0B7Ycm4aSYdPPTl9IUUVlamJ2VjQ'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pickle.loads(requests.get(url, stream=True).content, **pickle_options)
+ elif dataset is 'spiral':
+ fileid = '0B7Ycm4aSYdPPQS0xN3FmQ1FZSzg'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pickle.loads(requests.get(url, stream=True).content, **pickle_options)
+ elif dataset is 'mushrooms':
+ fileid = '0B7Ycm4aSYdPPY3J0U2tRNFB4T3c'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pd.read_csv(url)
+
+ return data
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/docs/_build/html/_modules/hypertools/tools/normalize.html b/docs/_build/html/_modules/hypertools/tools/normalize.html
index 90474259..7987bd94 100644
--- a/docs/_build/html/_modules/hypertools/tools/normalize.html
+++ b/docs/_build/html/_modules/hypertools/tools/normalize.html
@@ -113,6 +113,7 @@ Source code for hypertools.tools.normalize
#!/usr/bin/env python
from __future__ import division
+from builtins import range
from sklearn.preprocessing import FunctionTransformer
import numpy as np
from .._shared.helpers import format_data
diff --git a/docs/_build/html/_modules/hypertools/tools/procrustes.html b/docs/_build/html/_modules/hypertools/tools/procrustes.html
index 0144092d..0c7c58d1 100644
--- a/docs/_build/html/_modules/hypertools/tools/procrustes.html
+++ b/docs/_build/html/_modules/hypertools/tools/procrustes.html
@@ -114,6 +114,8 @@ Source code for hypertools.tools.procrustes
##PACKAGES##
from __future__ import division
+from builtins import zip
+from builtins import range
import numpy as np
##MAIN FUNCTION##
@@ -196,19 +198,20 @@ Source code for hypertools.tools.procrustes
# Check the sizes
if sn != tn:
- raise ValueError, "Data for both spaces should have the same " \
+ pass
+ raise ValueError("Data for both spaces should have the same " \
"number of samples. Got %d in template and %d in target space" \
- % (sn, tn)
+ % (sn, tn))
# Sums of squares
ssqs = [np.sum(d**2, axis=0) for d in datas]
# XXX check for being invariant?
# needs to be tuned up properly and not raise but handle
- for i in xrange(2):
+ for i in range(2):
if np.all(ssqs[i] <= np.abs((np.finfo(datas[i].dtype).eps
* sn * means[i] )**2)):
- raise ValueError, "For now do not handle invariant in time datasets"
+ raise ValueError("For now do not handle invariant in time datasets")
norms = [ np.sqrt(np.sum(ssq)) for ssq in ssqs ]
normed = [ data/norm for (data, norm) in zip(datas, norms) ]
@@ -221,10 +224,10 @@ Source code for hypertools.tools.procrustes
if reduction:
normed[1] = np.hstack( (normed[1], np.zeros((sn, sm-tm))) )
else:
- raise ValueError, "reduction=False, so mapping from " \
+ raise ValueError("reduction=False, so mapping from " \
"higher dimensionality " \
"template space is not supported. template space had %d " \
- "while target %d dimensions (features)" % (sm, tm)
+ "while target %d dimensions (features)" % (sm, tm))
source, target = normed
if oblique:
@@ -277,7 +280,7 @@ Source code for hypertools.tools.procrustes
def transform(data,proj):
if proj is None:
- raise RuntimeError, "Mapper needs to be train before used."
+ raise RuntimeError("Mapper needs to be train before used.")
# local binding
demean = _demean
diff --git a/docs/_build/html/_modules/hypertools/tools/reduce.html b/docs/_build/html/_modules/hypertools/tools/reduce.html
index f7c31f9d..c671131a 100644
--- a/docs/_build/html/_modules/hypertools/tools/reduce.html
+++ b/docs/_build/html/_modules/hypertools/tools/reduce.html
@@ -115,7 +115,7 @@ Source code for hypertools.tools.reduce
##PACKAGES##
import warnings
import numpy as np
-from ppca import PPCA
+from .._externals.ppca import PPCA
from sklearn.decomposition import PCA as PCA
from ..tools.df2mat import df2mat
from ..tools.normalize import normalize as normalizer
@@ -166,8 +166,8 @@ Source code for hypertools.tools.reduce
warnings.warn('Missing data: Inexact solution computed with PPCA (see https://github.com/allentran/pca-magic for details)')
# ppca if missing data
- m = PPCA(np.vstack(x))
- m.fit(d=ndim)
+ m = PPCA()
+ m.fit(data=np.vstack(x), d=ndim)
x_pca = m.transform()
# if the whole row is missing, return nans
diff --git a/docs/_build/html/_modules/index.html b/docs/_build/html/_modules/index.html
index 358469eb..5b485aa0 100644
--- a/docs/_build/html/_modules/index.html
+++ b/docs/_build/html/_modules/index.html
@@ -114,6 +114,7 @@ All modules for which code is available
hypertools.tools.align
hypertools.tools.cluster
hypertools.tools.describe_pca
+hypertools.tools.load
hypertools.tools.missing_inds
hypertools.tools.normalize
hypertools.tools.procrustes
diff --git a/docs/_build/html/_sources/api.rst.txt b/docs/_build/html/_sources/api.rst.txt
index d089b0b9..11eb7e8b 100644
--- a/docs/_build/html/_sources/api.rst.txt
+++ b/docs/_build/html/_sources/api.rst.txt
@@ -50,5 +50,10 @@ Tools
.. autosummary::
:toctree:
-
+
hypertools.tools.missing_inds
+
+.. autosummary::
+ :toctree:
+
+ hypertools.tools.load
diff --git a/docs/_build/html/_sources/auto_examples/animate.rst.txt b/docs/_build/html/_sources/auto_examples/animate.rst.txt
index ca53dc69..5e13809a 100644
--- a/docs/_build/html/_sources/auto_examples/animate.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/animate.rst.txt
@@ -23,15 +23,14 @@ from one subject. The rows are timepoints and the columns are neural
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=data['weights'][0]
- w = [i for i in w]
+ data = hyp.tools.load('weights')
+ w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
w2 = np.mean(aligned_w[18:],0)
- hyp.plot([w1,w2],animate=True, duration=100)
+ hyp.plot([w1,w2],animate=True)
**Total running time of the script:** ( 0 minutes 0.000 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/explore.rst.txt b/docs/_build/html/_sources/auto_examples/explore.rst.txt
index 84401d4f..c6ab119f 100644
--- a/docs/_build/html/_sources/auto_examples/explore.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/explore.rst.txt
@@ -26,10 +26,9 @@ along with the PCA coordinate.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:2]]
+ data = hyp.tools.load('weights_sample')
- hyp.plot(w,'o', explore=True)
+ hyp.plot(data, 'o', explore=True)
**Total running time of the script:** ( 0 minutes 0.000 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/index.rst.txt b/docs/_build/html/_sources/auto_examples/index.rst.txt
index fc6f6327..b183bfff 100644
--- a/docs/_build/html/_sources/auto_examples/index.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/index.rst.txt
@@ -9,13 +9,13 @@ Gallery of Examples
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_clusters_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_basic_thumb.png
- :ref:`sphx_glr_auto_examples_plot_clusters.py`
+ :ref:`sphx_glr_auto_examples_plot_basic.py`
.. raw:: html
@@ -25,17 +25,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_clusters
+ /auto_examples/plot_basic
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_dataframe_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_clusters_thumb.png
- :ref:`sphx_glr_auto_examples_plot_dataframe.py`
+ :ref:`sphx_glr_auto_examples_plot_clusters.py`
.. raw:: html
@@ -45,17 +45,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_dataframe
+ /auto_examples/plot_clusters
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_basic_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_describe_thumb.png
- :ref:`sphx_glr_auto_examples_plot_basic.py`
+ :ref:`sphx_glr_auto_examples_plot_describe.py`
.. raw:: html
@@ -65,17 +65,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_basic
+ /auto_examples/plot_describe
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_digits_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_dataframe_thumb.png
- :ref:`sphx_glr_auto_examples_plot_digits.py`
+ :ref:`sphx_glr_auto_examples_plot_dataframe.py`
.. raw:: html
@@ -85,17 +85,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_digits
+ /auto_examples/plot_dataframe
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_describe_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_explore_thumb.png
- :ref:`sphx_glr_auto_examples_plot_describe.py`
+ :ref:`sphx_glr_auto_examples_explore.py`
.. raw:: html
@@ -105,17 +105,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_describe
+ /auto_examples/explore
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_explore_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_legend_thumb.png
- :ref:`sphx_glr_auto_examples_explore.py`
+ :ref:`sphx_glr_auto_examples_plot_legend.py`
.. raw:: html
@@ -125,17 +125,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/explore
+ /auto_examples/plot_legend
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_save_image_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_digits_thumb.png
- :ref:`sphx_glr_auto_examples_save_image.py`
+ :ref:`sphx_glr_auto_examples_plot_digits.py`
.. raw:: html
@@ -145,17 +145,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/save_image
+ /auto_examples/plot_digits
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_legend_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_save_image_thumb.png
- :ref:`sphx_glr_auto_examples_plot_legend.py`
+ :ref:`sphx_glr_auto_examples_save_image.py`
.. raw:: html
@@ -165,17 +165,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_legend
+ /auto_examples/save_image
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_align_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_animate_thumb.png
- :ref:`sphx_glr_auto_examples_plot_align.py`
+ :ref:`sphx_glr_auto_examples_animate.py`
.. raw:: html
@@ -185,17 +185,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_align
+ /auto_examples/animate
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_animate_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_align_thumb.png
- :ref:`sphx_glr_auto_examples_animate.py`
+ :ref:`sphx_glr_auto_examples_plot_align.py`
.. raw:: html
@@ -205,7 +205,7 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/animate
+ /auto_examples/plot_align
.. raw:: html
@@ -229,13 +229,13 @@ Gallery of Examples
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_clusters2_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_labels_thumb.png
- :ref:`sphx_glr_auto_examples_plot_clusters2.py`
+ :ref:`sphx_glr_auto_examples_plot_labels.py`
.. raw:: html
@@ -245,17 +245,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_clusters2
+ /auto_examples/plot_labels
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_labels_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_clusters2_thumb.png
- :ref:`sphx_glr_auto_examples_plot_labels.py`
+ :ref:`sphx_glr_auto_examples_plot_clusters2.py`
.. raw:: html
@@ -265,7 +265,7 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_labels
+ /auto_examples/plot_clusters2
.. raw:: html
diff --git a/docs/_build/html/_sources/auto_examples/plot_PPCA.rst.txt b/docs/_build/html/_sources/auto_examples/plot_PPCA.rst.txt
index b10fb90d..f0101cc7 100644
--- a/docs/_build/html/_sources/auto_examples/plot_PPCA.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_PPCA.rst.txt
@@ -41,13 +41,13 @@ both the original and data with missing values together to see how it performed.
missing = .1
inds = [(i,j) for i in range(data2.shape[0]) for j in range(data2.shape[1])]
- missing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]
+ missing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]
for i,j in missing_data:
data2[i,j]=np.nan
hyp.plot([data1,data2],linestyle=['-',':'], legend=['Original', 'PPCA'])
-**Total running time of the script:** ( 0 minutes 0.050 seconds)
+**Total running time of the script:** ( 0 minutes 0.063 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_align.rst.txt b/docs/_build/html/_sources/auto_examples/plot_align.rst.txt
index 7e800d0c..a0e46fcc 100644
--- a/docs/_build/html/_sources/auto_examples/plot_align.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_align.rst.txt
@@ -32,10 +32,8 @@ Then we average the data into two groups, and plot.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
-
- w=data['weights'][0]
- w = [i for i in w]
+ data = hyp.tools.load('weights')
+ w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
@@ -43,7 +41,7 @@ Then we average the data into two groups, and plot.
hyp.plot([w1[:100,:],w2[:100,:]])
-**Total running time of the script:** ( 0 minutes 0.407 seconds)
+**Total running time of the script:** ( 0 minutes 5.852 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_basic.rst.txt b/docs/_build/html/_sources/auto_examples/plot_basic.rst.txt
index 1b9bcce0..3e8c1c43 100644
--- a/docs/_build/html/_sources/auto_examples/plot_basic.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_basic.rst.txt
@@ -28,15 +28,12 @@ with the 'o'. Hypertools can handle all format strings supported by matplotlib.
# License: MIT
import hypertools as hyp
- import scipy.io as sio
- import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:2]]
+ data = hyp.tools.load('weights_sample')
- hyp.plot(w,'o')
+ hyp.plot(data,'o')
-**Total running time of the script:** ( 0 minutes 0.064 seconds)
+**Total running time of the script:** ( 0 minutes 7.001 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_clusters.rst.txt b/docs/_build/html/_sources/auto_examples/plot_clusters.rst.txt
index e5badcf5..1aefbe6b 100644
--- a/docs/_build/html/_sources/auto_examples/plot_clusters.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_clusters.rst.txt
@@ -31,11 +31,11 @@ yourself.
import hypertools as hyp
import pandas as pd
- data=pd.read_csv('sample_data/mushrooms.csv')
+ data = hyp.tools.load('mushrooms')
hyp.plot(data,'o',n_clusters=10)
-**Total running time of the script:** ( 0 minutes 0.390 seconds)
+**Total running time of the script:** ( 0 minutes 1.426 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_customize_figure.rst.txt b/docs/_build/html/_sources/auto_examples/plot_customize_figure.rst.txt
index 7478bc5e..edc26479 100644
--- a/docs/_build/html/_sources/auto_examples/plot_customize_figure.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_customize_figure.rst.txt
@@ -31,10 +31,9 @@ attributes.
import numpy as np
import matplotlib.pyplot as plt
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:2]]
+ data = hyp.tools.load('weights_sample')
- fig,ax,data = hyp.plot(w,'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)
+ fig,ax,data = hyp.plot(data[:2], 'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)
ax.set_title('This is an example title', fontsize=20)
ax.set_ylabel('PCA Dimension 2', fontsize=15)
@@ -44,7 +43,7 @@ attributes.
plt.show()
-**Total running time of the script:** ( 0 minutes 0.104 seconds)
+**Total running time of the script:** ( 0 minutes 3.390 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_dataframe.rst.txt b/docs/_build/html/_sources/auto_examples/plot_dataframe.rst.txt
index af4b88d0..cd764113 100644
--- a/docs/_build/html/_sources/auto_examples/plot_dataframe.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_dataframe.rst.txt
@@ -32,12 +32,13 @@ presence or absences of the feature (see Pandas.Dataframe.get_dummies for more).
import hypertools as hyp
import pandas as pd
- data = pd.read_csv('sample_data/mushrooms.csv')
+ data = hyp.tools.load('mushrooms')
+
group = data.pop('class')
- hyp.plot(data,'o', group=group)
+ hyp.plot(data, 'o', group=group)
-**Total running time of the script:** ( 0 minutes 0.199 seconds)
+**Total running time of the script:** ( 0 minutes 1.579 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_describe.rst.txt b/docs/_build/html/_sources/auto_examples/plot_describe.rst.txt
index 0289f82e..448704c9 100644
--- a/docs/_build/html/_sources/auto_examples/plot_describe.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_describe.rst.txt
@@ -13,7 +13,7 @@ dimensional visualizations, we built the `describe_pca` function, which computes
the covariance (samples by samples) of both the raw and reduced datasets, and
plots their correlation. The function repeats this analysis from 2:N dimensions
until the correlation reaches a local maximum. Often times this will be less
-than the total number of dimensions because the PCA model is whitened.
+than the total number of dimensions because the PCA model is whitened.
@@ -35,12 +35,11 @@ than the total number of dimensions because the PCA model is whitened.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:3]]
+ data = hyp.tools.load('weights_sample')
- hyp.tools.describe_pca(w)
+ hyp.tools.describe_pca(data)
-**Total running time of the script:** ( 0 minutes 3.749 seconds)
+**Total running time of the script:** ( 0 minutes 5.902 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_group.rst.txt b/docs/_build/html/_sources/auto_examples/plot_group.rst.txt
index 36694500..b845f4a5 100644
--- a/docs/_build/html/_sources/auto_examples/plot_group.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_group.rst.txt
@@ -45,22 +45,21 @@ palette.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:3]]
+ data = hyp.tools.load('weights_sample')
- group = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in w]
- hyp.plot(w,'o',group=group)
+ group = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in data]
+ hyp.plot(data, 'o', group=group)
group=[]
- for idx,i in enumerate(w):
+ for idx,i in enumerate(data):
tmp=[]
for iidx,ii in enumerate(i):
tmp.append(int(np.random.randint(1000, size=1)))
group.append(tmp)
- hyp.plot(w,'o',group=group)
+ hyp.plot(data, 'o', group=group)
-**Total running time of the script:** ( 0 minutes 0.349 seconds)
+**Total running time of the script:** ( 0 minutes 1.118 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_labels.rst.txt b/docs/_build/html/_sources/auto_examples/plot_labels.rst.txt
index f43afe49..c7b6c549 100644
--- a/docs/_build/html/_sources/auto_examples/plot_labels.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_labels.rst.txt
@@ -31,11 +31,10 @@ are simply labeling the first datapoint for each matrix in the list.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:3]]
+ data = hyp.tools.load('weights_sample')
labels=[]
- for idx,i in enumerate(w):
+ for idx,i in enumerate(data):
tmp=[]
for iidx,ii in enumerate(i):
if iidx==0:
@@ -44,9 +43,9 @@ are simply labeling the first datapoint for each matrix in the list.
tmp.append(None)
labels.append(tmp)
- hyp.plot(w,'o',labels=labels)
+ hyp.plot(data, 'o', labels=labels)
-**Total running time of the script:** ( 0 minutes 0.165 seconds)
+**Total running time of the script:** ( 0 minutes 1.602 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_legend.rst.txt b/docs/_build/html/_sources/auto_examples/plot_legend.rst.txt
index c17d3649..5a825384 100644
--- a/docs/_build/html/_sources/auto_examples/plot_legend.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_legend.rst.txt
@@ -29,12 +29,11 @@ An example of how to use the `legend` kwarg to generate a legend.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:2]]
+ data = hyp.tools.load('weights_sample')
- hyp.plot(w,'o', legend=['Group A', 'Group B'])
+ hyp.plot(data, 'o', legend=['Group A', 'Group B', 'Group C'])
-**Total running time of the script:** ( 0 minutes 0.088 seconds)
+**Total running time of the script:** ( 0 minutes 1.146 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_missing_data.rst.txt b/docs/_build/html/_sources/auto_examples/plot_missing_data.rst.txt
index f1d87213..7294bc03 100644
--- a/docs/_build/html/_sources/auto_examples/plot_missing_data.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_missing_data.rst.txt
@@ -41,7 +41,7 @@ with stars.
missing = .05
inds = [(i,j) for i in range(data1.shape[0]) for j in range(data1.shape[1])]
- missing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]
+ missing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]
for i,j in missing_data:
data2[i,j]=np.nan
@@ -52,7 +52,7 @@ with stars.
hyp.plot([data1_r, data2_r, missing_data], ['r','b--','b*'])
-**Total running time of the script:** ( 0 minutes 0.028 seconds)
+**Total running time of the script:** ( 0 minutes 0.057 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/plot_procrustes.rst.txt b/docs/_build/html/_sources/auto_examples/plot_procrustes.rst.txt
index a598475d..4d681d0c 100644
--- a/docs/_build/html/_sources/auto_examples/plot_procrustes.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/plot_procrustes.rst.txt
@@ -43,8 +43,8 @@ space of a target matrix.
import numpy as np
import matplotlib.pyplot as plt
- data = sio.loadmat('sample_data/test_data.mat')
- target = data['spiral']
+ data = hyp.tools.load('spiral')
+ target = data
# A random rotation matrix
rot = np.array([[-0.89433495, -0.44719485, -0.01348182],
@@ -63,7 +63,7 @@ space of a target matrix.
ax.set_title('After Procrustes')
plt.show()
-**Total running time of the script:** ( 0 minutes 0.151 seconds)
+**Total running time of the script:** ( 0 minutes 0.563 seconds)
diff --git a/docs/_build/html/_sources/auto_examples/save_image.rst.txt b/docs/_build/html/_sources/auto_examples/save_image.rst.txt
index 7ab9ae5c..abb3c6eb 100644
--- a/docs/_build/html/_sources/auto_examples/save_image.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/save_image.rst.txt
@@ -22,8 +22,8 @@ the image to be saved, including the file extension (e.g. pdf)
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:3]]
+ data = hyp.tools.load('weights')
+ w=[i for i in data[0:3]]
hyp.plot(w,'o', save_path='test-image.pdf')
diff --git a/docs/_build/html/_sources/auto_examples/save_movie.rst.txt b/docs/_build/html/_sources/auto_examples/save_movie.rst.txt
index 75b4d19d..b83cc114 100644
--- a/docs/_build/html/_sources/auto_examples/save_movie.rst.txt
+++ b/docs/_build/html/_sources/auto_examples/save_movie.rst.txt
@@ -23,9 +23,8 @@ depends on having ffmpeg installed on your computer.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('example_data/weights.mat')
- w=data['weights'][0]
- w = [i for i in w]
+ data = hyp.tools.load('weights')
+ w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
diff --git a/docs/_build/html/_sources/hypertools.tools.load.rst.txt b/docs/_build/html/_sources/hypertools.tools.load.rst.txt
new file mode 100644
index 00000000..6668815b
--- /dev/null
+++ b/docs/_build/html/_sources/hypertools.tools.load.rst.txt
@@ -0,0 +1,6 @@
+hypertools.tools.load
+=====================
+
+.. currentmodule:: hypertools.tools
+
+.. autofunction:: load
\ No newline at end of file
diff --git a/docs/_build/html/api.html b/docs/_build/html/api.html
index 706a8fe3..d7a91933 100644
--- a/docs/_build/html/api.html
+++ b/docs/_build/html/api.html
@@ -213,6 +213,17 @@ Tools
+
+
+
+
+hypertools.tools.load(dataset)Load example data
+
diff --git a/docs/_build/html/auto_examples/animate.html b/docs/_build/html/auto_examples/animate.html
index 0cd22849..3f6d5b77 100644
--- a/docs/_build/html/auto_examples/animate.html
+++ b/docs/_build/html/auto_examples/animate.html
@@ -124,15 +124,14 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=data['weights'][0]
-w = [i for i in w]
+data = hyp.tools.load('weights')
+w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
w2 = np.mean(aligned_w[18:],0)
-hyp.plot([w1,w2],animate=True, duration=100)
+hyp.plot([w1,w2],animate=True)
Total running time of the script: ( 0 minutes 0.000 seconds)
diff --git a/docs/_build/html/auto_examples/explore.html b/docs/_build/html/auto_examples/explore.html
index b3aef38a..c60a429c 100644
--- a/docs/_build/html/auto_examples/explore.html
+++ b/docs/_build/html/auto_examples/explore.html
@@ -127,10 +127,9 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:2]]
+data = hyp.tools.load('weights_sample')
-hyp.plot(w,'o', explore=True)
+hyp.plot(data, 'o', explore=True)
Total running time of the script: ( 0 minutes 0.000 seconds)
diff --git a/docs/_build/html/auto_examples/index.html b/docs/_build/html/auto_examples/index.html
index 8b3b8033..dd1a81df 100644
--- a/docs/_build/html/auto_examples/index.html
+++ b/docs/_build/html/auto_examples/index.html
@@ -116,81 +116,81 @@
Gallery of Examples¶
-
+
+
+
+
+
+
+
-
-
-
+
-
-
-
+
-
-
-Visualizing the digits dataset
+
-
-
-Using describe_pca to evaluate the integrity of your visualization
+
-
-
-
+
-
+
-
-
-
+
-
+
-
-
-
-
-Using the cluster function to label clusters
+
-
-
-
+
diff --git a/docs/_build/html/auto_examples/plot_PPCA.html b/docs/_build/html/auto_examples/plot_PPCA.html
index e9b70c16..af49050e 100644
--- a/docs/_build/html/auto_examples/plot_PPCA.html
+++ b/docs/_build/html/auto_examples/plot_PPCA.html
@@ -135,14 +135,14 @@
missing = .1
inds = [(i,j) for i in range(data2.shape[0]) for j in range(data2.shape[1])]
-missing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]
+missing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]
for i,j in missing_data:
data2[i,j]=np.nan
hyp.plot([data1,data2],linestyle=['-',':'], legend=['Original', 'PPCA'])
-Total running time of the script: ( 0 minutes 0.050 seconds)
+Total running time of the script: ( 0 minutes 0.063 seconds)
-Total running time of the script: ( 0 minutes 0.407 seconds)
+Total running time of the script: ( 0 minutes 5.852 seconds)
-Total running time of the script: ( 0 minutes 0.064 seconds)
+Total running time of the script: ( 0 minutes 7.001 seconds)
-Total running time of the script: ( 0 minutes 0.390 seconds)
+Total running time of the script: ( 0 minutes 1.426 seconds)
-Total running time of the script: ( 0 minutes 0.104 seconds)
+Total running time of the script: ( 0 minutes 3.390 seconds)
-Total running time of the script: ( 0 minutes 0.199 seconds)
+Total running time of the script: ( 0 minutes 1.579 seconds)
-Total running time of the script: ( 0 minutes 3.749 seconds)
+Total running time of the script: ( 0 minutes 5.902 seconds)
-Total running time of the script: ( 0 minutes 0.349 seconds)
+Total running time of the script: ( 0 minutes 1.118 seconds)
-Total running time of the script: ( 0 minutes 0.165 seconds)
+Total running time of the script: ( 0 minutes 1.602 seconds)
-Total running time of the script: ( 0 minutes 0.088 seconds)
+Total running time of the script: ( 0 minutes 1.146 seconds)
-Total running time of the script: ( 0 minutes 0.028 seconds)
+Total running time of the script: ( 0 minutes 0.057 seconds)
-Total running time of the script: ( 0 minutes 0.151 seconds)
+Total running time of the script: ( 0 minutes 0.563 seconds)
diff --git a/docs/_build/html/auto_examples/save_movie.html b/docs/_build/html/auto_examples/save_movie.html
index ab31584d..4c4b6466 100644
--- a/docs/_build/html/auto_examples/save_movie.html
+++ b/docs/_build/html/auto_examples/save_movie.html
@@ -124,9 +124,8 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('example_data/weights.mat')
-w=data['weights'][0]
-w = [i for i in w]
+data = hyp.tools.load('weights')
+w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
diff --git a/docs/_build/html/genindex.html b/docs/_build/html/genindex.html
index aa97a339..02b4fcda 100644
--- a/docs/_build/html/genindex.html
+++ b/docs/_build/html/genindex.html
@@ -117,6 +117,7 @@ Index
A
| C
| D
+ | L
| M
| N
| P
@@ -147,6 +148,14 @@ D
+L
+
+
+
M
diff --git a/docs/_build/html/hypertools.tools.load.html b/docs/_build/html/hypertools.tools.load.html
new file mode 100644
index 00000000..1f15a9e1
--- /dev/null
+++ b/docs/_build/html/hypertools.tools.load.html
@@ -0,0 +1,174 @@
+
+
+
+
+
+
+
+ hypertools.tools.load — hypertools 0.1.2 documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+hypertools.tools.load¶
+
+-
+
hypertools.tools.load(dataset)[source]¶
+Load example data
+
+Parameters: dataset : string
+
+The name of the example dataset. weights is an fmri dataset comprised of
+36 subjects. For each subject, the rows are fMRI measurements and the columns
+are parameters of a model fit to the fMRI data. weights_sample is a
+sample of 3 subjects from that dataset. weights_avg is the dataset split
+in half and averaged into two groups. spiral is 3D spiral to
+highlight the procrustes function. mushrooms is an example dataset
+comprised of features (columns) of a collection of mushroomm samples (rows).
+
+Returns: data : Numpy Array
+
+Example data
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/docs/_build/html/objects.inv b/docs/_build/html/objects.inv
index 831cbe53..c486867c 100644
Binary files a/docs/_build/html/objects.inv and b/docs/_build/html/objects.inv differ
diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js
index c7cf7dfd..71cb7298 100644
--- a/docs/_build/html/searchindex.js
+++ b/docs/_build/html/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
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reference","Hyperalign a list of arrays and create an animated plot","Explore mode!","Gallery of Examples","Interpolating missing data with probabalistic PCA","Aligning matrices to a common space","A basic example","Discovering clusters","Using the cluster function to label clusters","Customizing figures","Plotting a Pandas Dataframe","Using describe_pca to evaluate the integrity of your visualization","Visualizing the digits dataset","Grouping data by category","Labeling your datapoints","Generating a legend","Using the missing_inds function to label interpolated values","Normalizing your features","Aligning two matrices with the procrustes function","Saving a plot","Saving an animation","hypertools.tools.load","HyperTools: A python toolbox for visualizing and manipulating high-dimensional data"],titleterms:{"function":[8,16,18],Using:[8,11,16],align:[5,18],anim:[1,20],api:0,arrai:1,basic:6,categori:13,choos:[],cluster:[7,8],common:5,creat:1,custom:9,data:[4,13,22],datafram:10,datapoint:14,dataset:12,describe_pca:11,digit:12,dimension:22,discov:7,evalu:11,exampl:[3,6],explor:2,featur:17,figur:9,galleri:3,gener:15,group:13,high:22,hyperalign:1,hypertool:[21,22],integr:11,interpol:[4,16],label:[8,14,16],legend:15,list:1,load:21,manipul:22,matric:[5,18],miss:4,missing_ind:16,mode:2,normal:17,panda:10,pca:4,plot:[0,1,10,19],probabalist:4,procrust:18,python:22,reduc:[],refer:0,save:[19,20],space:5,thumbnail:[],tool:[0,21],toolbox:22,two:18,valu:16,visual:[11,12,22],your:[11,14,17]}})
\ No newline at end of file
diff --git a/docs/api.rst b/docs/api.rst
index d089b0b9..d5dc860c 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -1,3 +1,5 @@
+:orphan:
+
.. _api_ref:
.. currentmodule:: hypertools
@@ -50,5 +52,10 @@ Tools
.. autosummary::
:toctree:
-
+
hypertools.tools.missing_inds
+
+.. autosummary::
+ :toctree:
+
+ hypertools.tools.load
diff --git a/docs/auto_examples/animate.ipynb b/docs/auto_examples/animate.ipynb
index 1ef30c69..480f0a47 100644
--- a/docs/auto_examples/animate.ipynb
+++ b/docs/auto_examples/animate.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('sample_data/weights.mat')\nw=data['weights'][0]\nw = [i for i in w]\naligned_w = hyp.tools.align(w)\n\nw1 = np.mean(aligned_w[:17],0)\nw2 = np.mean(aligned_w[18:],0)\n\nhyp.plot([w1,w2],animate=True, duration=100)"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights')\nw = [i for i in data]\naligned_w = hyp.tools.align(w)\n\nw1 = np.mean(aligned_w[:17],0)\nw2 = np.mean(aligned_w[18:],0)\n\nhyp.plot([w1,w2],animate=True)"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/animate.py b/docs/auto_examples/animate.py
index bcee52a3..9f6e8365 100644
--- a/docs/auto_examples/animate.py
+++ b/docs/auto_examples/animate.py
@@ -16,12 +16,11 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=data['weights'][0]
-w = [i for i in w]
+data = hyp.tools.load('weights')
+w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
w2 = np.mean(aligned_w[18:],0)
-hyp.plot([w1,w2],animate=True, duration=100)
+hyp.plot([w1,w2],animate=True)
diff --git a/docs/auto_examples/animate.rst b/docs/auto_examples/animate.rst
index ca53dc69..5e13809a 100644
--- a/docs/auto_examples/animate.rst
+++ b/docs/auto_examples/animate.rst
@@ -23,15 +23,14 @@ from one subject. The rows are timepoints and the columns are neural
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=data['weights'][0]
- w = [i for i in w]
+ data = hyp.tools.load('weights')
+ w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
w2 = np.mean(aligned_w[18:],0)
- hyp.plot([w1,w2],animate=True, duration=100)
+ hyp.plot([w1,w2],animate=True)
**Total running time of the script:** ( 0 minutes 0.000 seconds)
diff --git a/docs/auto_examples/animate_codeobj.pickle b/docs/auto_examples/animate_codeobj.pickle
index 6fd2f1ed..4feadebc 100644
--- a/docs/auto_examples/animate_codeobj.pickle
+++ b/docs/auto_examples/animate_codeobj.pickle
@@ -1,4 +1,5 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.tools.align}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.tools.align}q(hU
hypertoolshUalignhUhypertools.toolsuUnp.mean}q(hUnumpyqhUmeanhhuUhyp.plot}q (hU
hypertoolsq
hUplothh
diff --git a/docs/auto_examples/auto_examples_jupyter.zip b/docs/auto_examples/auto_examples_jupyter.zip
index a9286769..3234cf33 100644
Binary files a/docs/auto_examples/auto_examples_jupyter.zip and b/docs/auto_examples/auto_examples_jupyter.zip differ
diff --git a/docs/auto_examples/auto_examples_python.zip b/docs/auto_examples/auto_examples_python.zip
index ef89fa26..dfb669e6 100644
Binary files a/docs/auto_examples/auto_examples_python.zip and b/docs/auto_examples/auto_examples_python.zip differ
diff --git a/docs/auto_examples/explore.ipynb b/docs/auto_examples/explore.ipynb
index 20b2f50a..2482ba1a 100644
--- a/docs/auto_examples/explore.ipynb
+++ b/docs/auto_examples/explore.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('sample_data/weights.mat')\nw=[i for i in data['weights'][0][0:2]]\n\nhyp.plot(w,'o', explore=True)"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights_sample')\n\nhyp.plot(data, 'o', explore=True)"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/explore.py b/docs/auto_examples/explore.py
index fae6367e..32d05b5b 100644
--- a/docs/auto_examples/explore.py
+++ b/docs/auto_examples/explore.py
@@ -19,7 +19,6 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:2]]
+data = hyp.tools.load('weights_sample')
-hyp.plot(w,'o', explore=True)
+hyp.plot(data, 'o', explore=True)
diff --git a/docs/auto_examples/explore.rst b/docs/auto_examples/explore.rst
index 84401d4f..c6ab119f 100644
--- a/docs/auto_examples/explore.rst
+++ b/docs/auto_examples/explore.rst
@@ -26,10 +26,9 @@ along with the PCA coordinate.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:2]]
+ data = hyp.tools.load('weights_sample')
- hyp.plot(w,'o', explore=True)
+ hyp.plot(data, 'o', explore=True)
**Total running time of the script:** ( 0 minutes 0.000 seconds)
diff --git a/docs/auto_examples/explore_codeobj.pickle b/docs/auto_examples/explore_codeobj.pickle
index 698f0630..4f8237c8 100644
--- a/docs/auto_examples/explore_codeobj.pickle
+++ b/docs/auto_examples/explore_codeobj.pickle
@@ -1,2 +1,3 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.plot}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.plot}q(hU
hypertoolsqhUplothhuu.
\ No newline at end of file
diff --git a/docs/auto_examples/images/sphx_glr_plot_PPCA_001.png b/docs/auto_examples/images/sphx_glr_plot_PPCA_001.png
index 5fbec89a..c891a9d1 100644
Binary files a/docs/auto_examples/images/sphx_glr_plot_PPCA_001.png and b/docs/auto_examples/images/sphx_glr_plot_PPCA_001.png differ
diff --git a/docs/auto_examples/images/sphx_glr_plot_align_001.png b/docs/auto_examples/images/sphx_glr_plot_align_001.png
index 3e3bff68..0e346a12 100644
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index 87725cd2..244b0abd 100644
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diff --git a/docs/auto_examples/images/thumb/sphx_glr_plot_labels_thumb.png b/docs/auto_examples/images/thumb/sphx_glr_plot_labels_thumb.png
index f667dedf..3e2324b8 100644
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diff --git a/docs/auto_examples/images/thumb/sphx_glr_plot_legend_thumb.png b/docs/auto_examples/images/thumb/sphx_glr_plot_legend_thumb.png
index 7eb38289..6d0c4594 100644
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diff --git a/docs/auto_examples/images/thumb/sphx_glr_plot_missing_data_thumb.png b/docs/auto_examples/images/thumb/sphx_glr_plot_missing_data_thumb.png
index 340babe8..1516a6f8 100644
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diff --git a/docs/auto_examples/images/thumb/sphx_glr_plot_procrustes_thumb.png b/docs/auto_examples/images/thumb/sphx_glr_plot_procrustes_thumb.png
index 9459f438..5712cff2 100644
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diff --git a/docs/auto_examples/index.rst b/docs/auto_examples/index.rst
index fc6f6327..b183bfff 100644
--- a/docs/auto_examples/index.rst
+++ b/docs/auto_examples/index.rst
@@ -9,13 +9,13 @@ Gallery of Examples
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_clusters_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_basic_thumb.png
- :ref:`sphx_glr_auto_examples_plot_clusters.py`
+ :ref:`sphx_glr_auto_examples_plot_basic.py`
.. raw:: html
@@ -25,17 +25,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_clusters
+ /auto_examples/plot_basic
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_dataframe_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_clusters_thumb.png
- :ref:`sphx_glr_auto_examples_plot_dataframe.py`
+ :ref:`sphx_glr_auto_examples_plot_clusters.py`
.. raw:: html
@@ -45,17 +45,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_dataframe
+ /auto_examples/plot_clusters
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_basic_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_describe_thumb.png
- :ref:`sphx_glr_auto_examples_plot_basic.py`
+ :ref:`sphx_glr_auto_examples_plot_describe.py`
.. raw:: html
@@ -65,17 +65,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_basic
+ /auto_examples/plot_describe
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_digits_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_dataframe_thumb.png
- :ref:`sphx_glr_auto_examples_plot_digits.py`
+ :ref:`sphx_glr_auto_examples_plot_dataframe.py`
.. raw:: html
@@ -85,17 +85,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_digits
+ /auto_examples/plot_dataframe
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_describe_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_explore_thumb.png
- :ref:`sphx_glr_auto_examples_plot_describe.py`
+ :ref:`sphx_glr_auto_examples_explore.py`
.. raw:: html
@@ -105,17 +105,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_describe
+ /auto_examples/explore
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_explore_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_legend_thumb.png
- :ref:`sphx_glr_auto_examples_explore.py`
+ :ref:`sphx_glr_auto_examples_plot_legend.py`
.. raw:: html
@@ -125,17 +125,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/explore
+ /auto_examples/plot_legend
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_save_image_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_digits_thumb.png
- :ref:`sphx_glr_auto_examples_save_image.py`
+ :ref:`sphx_glr_auto_examples_plot_digits.py`
.. raw:: html
@@ -145,17 +145,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/save_image
+ /auto_examples/plot_digits
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_legend_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_save_image_thumb.png
- :ref:`sphx_glr_auto_examples_plot_legend.py`
+ :ref:`sphx_glr_auto_examples_save_image.py`
.. raw:: html
@@ -165,17 +165,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_legend
+ /auto_examples/save_image
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_align_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_animate_thumb.png
- :ref:`sphx_glr_auto_examples_plot_align.py`
+ :ref:`sphx_glr_auto_examples_animate.py`
.. raw:: html
@@ -185,17 +185,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_align
+ /auto_examples/animate
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_animate_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_align_thumb.png
- :ref:`sphx_glr_auto_examples_animate.py`
+ :ref:`sphx_glr_auto_examples_plot_align.py`
.. raw:: html
@@ -205,7 +205,7 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/animate
+ /auto_examples/plot_align
.. raw:: html
@@ -229,13 +229,13 @@ Gallery of Examples
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_clusters2_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_labels_thumb.png
- :ref:`sphx_glr_auto_examples_plot_clusters2.py`
+ :ref:`sphx_glr_auto_examples_plot_labels.py`
.. raw:: html
@@ -245,17 +245,17 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_clusters2
+ /auto_examples/plot_labels
.. raw:: html
-
+
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_labels_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_clusters2_thumb.png
- :ref:`sphx_glr_auto_examples_plot_labels.py`
+ :ref:`sphx_glr_auto_examples_plot_clusters2.py`
.. raw:: html
@@ -265,7 +265,7 @@ Gallery of Examples
.. toctree::
:hidden:
- /auto_examples/plot_labels
+ /auto_examples/plot_clusters2
.. raw:: html
diff --git a/docs/auto_examples/plot_PPCA.ipynb b/docs/auto_examples/plot_PPCA.ipynb
index fa594e8b..204ed40b 100644
--- a/docs/auto_examples/plot_PPCA.ipynb
+++ b/docs/auto_examples/plot_PPCA.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nfrom scipy.linalg import toeplitz\nimport numpy as np\nfrom copy import copy\nimport hypertools as hyp\n\nK = 10 - toeplitz(np.arange(10))\n\ndata1 = np.cumsum(np.random.multivariate_normal(np.zeros(10), K, 250), axis=0)\ndata2 = copy(data1)\n\nmissing = .1\ninds = [(i,j) for i in range(data2.shape[0]) for j in range(data2.shape[1])]\nmissing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]\nfor i,j in missing_data:\n data2[i,j]=np.nan\n\nhyp.plot([data1,data2],linestyle=['-',':'], legend=['Original', 'PPCA'])"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nfrom scipy.linalg import toeplitz\nimport numpy as np\nfrom copy import copy\nimport hypertools as hyp\n\nK = 10 - toeplitz(np.arange(10))\n\ndata1 = np.cumsum(np.random.multivariate_normal(np.zeros(10), K, 250), axis=0)\ndata2 = copy(data1)\n\nmissing = .1\ninds = [(i,j) for i in range(data2.shape[0]) for j in range(data2.shape[1])]\nmissing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]\nfor i,j in missing_data:\n data2[i,j]=np.nan\n\nhyp.plot([data1,data2],linestyle=['-',':'], legend=['Original', 'PPCA'])"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_PPCA.py b/docs/auto_examples/plot_PPCA.py
index 919eb3ed..11a741f2 100644
--- a/docs/auto_examples/plot_PPCA.py
+++ b/docs/auto_examples/plot_PPCA.py
@@ -26,7 +26,7 @@
missing = .1
inds = [(i,j) for i in range(data2.shape[0]) for j in range(data2.shape[1])]
-missing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]
+missing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]
for i,j in missing_data:
data2[i,j]=np.nan
diff --git a/docs/auto_examples/plot_PPCA.py.md5 b/docs/auto_examples/plot_PPCA.py.md5
index 4c1a1058..58e38e60 100644
--- a/docs/auto_examples/plot_PPCA.py.md5
+++ b/docs/auto_examples/plot_PPCA.py.md5
@@ -1 +1 @@
-9ef9ac433fd411b226ff40c1b9729b5f
\ No newline at end of file
+a546ae5c9da997f3d9e47a60c96a68d7
\ No newline at end of file
diff --git a/docs/auto_examples/plot_PPCA.rst b/docs/auto_examples/plot_PPCA.rst
index b10fb90d..f0101cc7 100644
--- a/docs/auto_examples/plot_PPCA.rst
+++ b/docs/auto_examples/plot_PPCA.rst
@@ -41,13 +41,13 @@ both the original and data with missing values together to see how it performed.
missing = .1
inds = [(i,j) for i in range(data2.shape[0]) for j in range(data2.shape[1])]
- missing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]
+ missing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]
for i,j in missing_data:
data2[i,j]=np.nan
hyp.plot([data1,data2],linestyle=['-',':'], legend=['Original', 'PPCA'])
-**Total running time of the script:** ( 0 minutes 0.050 seconds)
+**Total running time of the script:** ( 0 minutes 0.063 seconds)
diff --git a/docs/auto_examples/plot_align.ipynb b/docs/auto_examples/plot_align.ipynb
index efe763f0..e3e47b97 100644
--- a/docs/auto_examples/plot_align.ipynb
+++ b/docs/auto_examples/plot_align.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('sample_data/weights.mat')\n\nw=data['weights'][0]\nw = [i for i in w]\naligned_w = hyp.tools.align(w)\n\nw1 = np.mean(aligned_w[:17],0)\nw2 = np.mean(aligned_w[18:],0)\n\nhyp.plot([w1[:100,:],w2[:100,:]])"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights')\nw = [i for i in data]\naligned_w = hyp.tools.align(w)\n\nw1 = np.mean(aligned_w[:17],0)\nw2 = np.mean(aligned_w[18:],0)\n\nhyp.plot([w1[:100,:],w2[:100,:]])"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_align.py b/docs/auto_examples/plot_align.py
index ba9484ae..f247c184 100644
--- a/docs/auto_examples/plot_align.py
+++ b/docs/auto_examples/plot_align.py
@@ -17,10 +17,8 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-
-w=data['weights'][0]
-w = [i for i in w]
+data = hyp.tools.load('weights')
+w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
diff --git a/docs/auto_examples/plot_align.py.md5 b/docs/auto_examples/plot_align.py.md5
index 845100dd..29cdf770 100644
--- a/docs/auto_examples/plot_align.py.md5
+++ b/docs/auto_examples/plot_align.py.md5
@@ -1 +1 @@
-aa5402c23d2e8a5966dd130f4b447356
\ No newline at end of file
+a16e6347b83f81a6ceef4d7d7f996787
\ No newline at end of file
diff --git a/docs/auto_examples/plot_align.rst b/docs/auto_examples/plot_align.rst
index 7e800d0c..a0e46fcc 100644
--- a/docs/auto_examples/plot_align.rst
+++ b/docs/auto_examples/plot_align.rst
@@ -32,10 +32,8 @@ Then we average the data into two groups, and plot.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
-
- w=data['weights'][0]
- w = [i for i in w]
+ data = hyp.tools.load('weights')
+ w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
@@ -43,7 +41,7 @@ Then we average the data into two groups, and plot.
hyp.plot([w1[:100,:],w2[:100,:]])
-**Total running time of the script:** ( 0 minutes 0.407 seconds)
+**Total running time of the script:** ( 0 minutes 5.852 seconds)
diff --git a/docs/auto_examples/plot_align_codeobj.pickle b/docs/auto_examples/plot_align_codeobj.pickle
index 6fd2f1ed..4feadebc 100644
--- a/docs/auto_examples/plot_align_codeobj.pickle
+++ b/docs/auto_examples/plot_align_codeobj.pickle
@@ -1,4 +1,5 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.tools.align}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.tools.align}q(hU
hypertoolshUalignhUhypertools.toolsuUnp.mean}q(hUnumpyqhUmeanhhuUhyp.plot}q (hU
hypertoolsq
hUplothh
diff --git a/docs/auto_examples/plot_basic.ipynb b/docs/auto_examples/plot_basic.ipynb
index 7c933bf8..acd20d57 100644
--- a/docs/auto_examples/plot_basic.ipynb
+++ b/docs/auto_examples/plot_basic.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('sample_data/weights.mat')\nw=[i for i in data['weights'][0][0:2]]\n\nhyp.plot(w,'o')"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\n\ndata = hyp.tools.load('weights_sample')\n\nhyp.plot(data,'o')"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_basic.py b/docs/auto_examples/plot_basic.py
index 6743d259..9ac9d401 100644
--- a/docs/auto_examples/plot_basic.py
+++ b/docs/auto_examples/plot_basic.py
@@ -13,10 +13,7 @@
# License: MIT
import hypertools as hyp
-import scipy.io as sio
-import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:2]]
+data = hyp.tools.load('weights_sample')
-hyp.plot(w,'o')
+hyp.plot(data,'o')
diff --git a/docs/auto_examples/plot_basic.py.md5 b/docs/auto_examples/plot_basic.py.md5
index 101dfc6b..f05cd9ca 100644
--- a/docs/auto_examples/plot_basic.py.md5
+++ b/docs/auto_examples/plot_basic.py.md5
@@ -1 +1 @@
-7ce07dcc8d7be3a84a5fda23bf528797
\ No newline at end of file
+e2f6a23b4131d09113c5a19677452202
\ No newline at end of file
diff --git a/docs/auto_examples/plot_basic.rst b/docs/auto_examples/plot_basic.rst
index 1b9bcce0..3e8c1c43 100644
--- a/docs/auto_examples/plot_basic.rst
+++ b/docs/auto_examples/plot_basic.rst
@@ -28,15 +28,12 @@ with the 'o'. Hypertools can handle all format strings supported by matplotlib.
# License: MIT
import hypertools as hyp
- import scipy.io as sio
- import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:2]]
+ data = hyp.tools.load('weights_sample')
- hyp.plot(w,'o')
+ hyp.plot(data,'o')
-**Total running time of the script:** ( 0 minutes 0.064 seconds)
+**Total running time of the script:** ( 0 minutes 7.001 seconds)
diff --git a/docs/auto_examples/plot_basic_codeobj.pickle b/docs/auto_examples/plot_basic_codeobj.pickle
index 698f0630..4f8237c8 100644
--- a/docs/auto_examples/plot_basic_codeobj.pickle
+++ b/docs/auto_examples/plot_basic_codeobj.pickle
@@ -1,2 +1,3 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.plot}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.plot}q(hU
hypertoolsqhUplothhuu.
\ No newline at end of file
diff --git a/docs/auto_examples/plot_clusters.ipynb b/docs/auto_examples/plot_clusters.ipynb
index 1e233c79..75f7436a 100644
--- a/docs/auto_examples/plot_clusters.ipynb
+++ b/docs/auto_examples/plot_clusters.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport pandas as pd\n\ndata=pd.read_csv('sample_data/mushrooms.csv')\n\nhyp.plot(data,'o',n_clusters=10)"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport pandas as pd\n\ndata = hyp.tools.load('mushrooms')\n\nhyp.plot(data,'o',n_clusters=10)"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_clusters.py b/docs/auto_examples/plot_clusters.py
index ca15f86f..a4e855cb 100644
--- a/docs/auto_examples/plot_clusters.py
+++ b/docs/auto_examples/plot_clusters.py
@@ -16,6 +16,6 @@
import hypertools as hyp
import pandas as pd
-data=pd.read_csv('sample_data/mushrooms.csv')
+data = hyp.tools.load('mushrooms')
hyp.plot(data,'o',n_clusters=10)
diff --git a/docs/auto_examples/plot_clusters.py.md5 b/docs/auto_examples/plot_clusters.py.md5
index 6b31413b..2ccfe3f5 100644
--- a/docs/auto_examples/plot_clusters.py.md5
+++ b/docs/auto_examples/plot_clusters.py.md5
@@ -1 +1 @@
-9569ba9e2367acb9c8fd6f1832a1d385
\ No newline at end of file
+0864ba5c561cfea620937fefbdf9731f
\ No newline at end of file
diff --git a/docs/auto_examples/plot_clusters.rst b/docs/auto_examples/plot_clusters.rst
index e5badcf5..1aefbe6b 100644
--- a/docs/auto_examples/plot_clusters.rst
+++ b/docs/auto_examples/plot_clusters.rst
@@ -31,11 +31,11 @@ yourself.
import hypertools as hyp
import pandas as pd
- data=pd.read_csv('sample_data/mushrooms.csv')
+ data = hyp.tools.load('mushrooms')
hyp.plot(data,'o',n_clusters=10)
-**Total running time of the script:** ( 0 minutes 0.390 seconds)
+**Total running time of the script:** ( 0 minutes 1.426 seconds)
diff --git a/docs/auto_examples/plot_clusters_codeobj.pickle b/docs/auto_examples/plot_clusters_codeobj.pickle
index 3bc4b776..4f8237c8 100644
--- a/docs/auto_examples/plot_clusters_codeobj.pickle
+++ b/docs/auto_examples/plot_clusters_codeobj.pickle
@@ -1,2 +1,3 @@
-€}q(U pd.read_csv}q(U module_shortqUpandasqUnameqUread_csvUmoduleqhuUhyp.plot}q(hU
-hypertoolsqhUplothhuu.
\ No newline at end of file
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.plot}q(hU
+hypertoolsqhUplothhuu.
\ No newline at end of file
diff --git a/docs/auto_examples/plot_customize_figure.ipynb b/docs/auto_examples/plot_customize_figure.ipynb
index f9b5e45d..f1d83cfd 100644
--- a/docs/auto_examples/plot_customize_figure.ipynb
+++ b/docs/auto_examples/plot_customize_figure.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ndata=sio.loadmat('sample_data/weights.mat')\nw=[i for i in data['weights'][0][0:2]]\n\nfig,ax,data = hyp.plot(w,'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)\n\nax.set_title('This is an example title', fontsize=20)\nax.set_ylabel('PCA Dimension 2', fontsize=15)\nax.set_xlabel('PCA Dimension 1', fontsize=15)\nlegend_text = plt.gca().get_legend().get_texts()\nplt.setp(legend_text, fontsize=15)\n\nplt.show()"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ndata = hyp.tools.load('weights_sample')\n\nfig,ax,data = hyp.plot(data[:2], 'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)\n\nax.set_title('This is an example title', fontsize=20)\nax.set_ylabel('PCA Dimension 2', fontsize=15)\nax.set_xlabel('PCA Dimension 1', fontsize=15)\nlegend_text = plt.gca().get_legend().get_texts()\nplt.setp(legend_text, fontsize=15)\n\nplt.show()"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_customize_figure.py b/docs/auto_examples/plot_customize_figure.py
index c1acb35a..3b83d609 100644
--- a/docs/auto_examples/plot_customize_figure.py
+++ b/docs/auto_examples/plot_customize_figure.py
@@ -16,10 +16,9 @@
import numpy as np
import matplotlib.pyplot as plt
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:2]]
+data = hyp.tools.load('weights_sample')
-fig,ax,data = hyp.plot(w,'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)
+fig,ax,data = hyp.plot(data[:2], 'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)
ax.set_title('This is an example title', fontsize=20)
ax.set_ylabel('PCA Dimension 2', fontsize=15)
diff --git a/docs/auto_examples/plot_customize_figure.py.md5 b/docs/auto_examples/plot_customize_figure.py.md5
index 229f9661..018c6e5a 100644
--- a/docs/auto_examples/plot_customize_figure.py.md5
+++ b/docs/auto_examples/plot_customize_figure.py.md5
@@ -1 +1 @@
-f2baff27a5e990f6de80caac44d88b5f
\ No newline at end of file
+97168744305c7d1f26203caa4293032d
\ No newline at end of file
diff --git a/docs/auto_examples/plot_customize_figure.rst b/docs/auto_examples/plot_customize_figure.rst
index 7478bc5e..edc26479 100644
--- a/docs/auto_examples/plot_customize_figure.rst
+++ b/docs/auto_examples/plot_customize_figure.rst
@@ -31,10 +31,9 @@ attributes.
import numpy as np
import matplotlib.pyplot as plt
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:2]]
+ data = hyp.tools.load('weights_sample')
- fig,ax,data = hyp.plot(w,'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)
+ fig,ax,data = hyp.plot(data[:2], 'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)
ax.set_title('This is an example title', fontsize=20)
ax.set_ylabel('PCA Dimension 2', fontsize=15)
@@ -44,7 +43,7 @@ attributes.
plt.show()
-**Total running time of the script:** ( 0 minutes 0.104 seconds)
+**Total running time of the script:** ( 0 minutes 3.390 seconds)
diff --git a/docs/auto_examples/plot_customize_figure_codeobj.pickle b/docs/auto_examples/plot_customize_figure_codeobj.pickle
index 5b8d307f..ae09898c 100644
--- a/docs/auto_examples/plot_customize_figure_codeobj.pickle
+++ b/docs/auto_examples/plot_customize_figure_codeobj.pickle
@@ -1,3 +1,4 @@
-€}q(Uplt.gca}q(U module_shortqUmatplotlib.pyplotUnameqUgcaUmoduleqUmatplotlib.pyplotuU sio.loadmat}q(hUscipy.iohUloadmathUscipy.iouUplt.setp}q(hUmatplotlib.pyplothUsetphUmatplotlib.pyplotuUhyp.plot}q(hU
+€}q(Uplt.setp}q(U module_shortqUmatplotlib.pyplotUnameqUsetpUmoduleqUmatplotlib.pyplotuUhyp.tools.load}q(hU
+hypertoolshUloadhUhypertools.toolsuUplt.gca}q(hUmatplotlib.pyplothUgcahUmatplotlib.pyplotuUhyp.plot}q(hU
hypertoolsq hUplothh uUplt.show}q
(hUmatplotlib.pyplothUshowhUmatplotlib.pyplotuu.
\ No newline at end of file
diff --git a/docs/auto_examples/plot_dataframe.ipynb b/docs/auto_examples/plot_dataframe.ipynb
index 5f564598..e3f7839c 100644
--- a/docs/auto_examples/plot_dataframe.ipynb
+++ b/docs/auto_examples/plot_dataframe.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport pandas as pd\n\ndata = pd.read_csv('sample_data/mushrooms.csv')\ngroup = data.pop('class')\n\nhyp.plot(data,'o', group=group)"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport pandas as pd\n\ndata = hyp.tools.load('mushrooms')\n\ngroup = data.pop('class')\n\nhyp.plot(data, 'o', group=group)"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_dataframe.py b/docs/auto_examples/plot_dataframe.py
index d7032354..9b5e0856 100644
--- a/docs/auto_examples/plot_dataframe.py
+++ b/docs/auto_examples/plot_dataframe.py
@@ -17,7 +17,8 @@
import hypertools as hyp
import pandas as pd
-data = pd.read_csv('sample_data/mushrooms.csv')
+data = hyp.tools.load('mushrooms')
+
group = data.pop('class')
-hyp.plot(data,'o', group=group)
+hyp.plot(data, 'o', group=group)
diff --git a/docs/auto_examples/plot_dataframe.py.md5 b/docs/auto_examples/plot_dataframe.py.md5
index df84e608..320cd6a7 100644
--- a/docs/auto_examples/plot_dataframe.py.md5
+++ b/docs/auto_examples/plot_dataframe.py.md5
@@ -1 +1 @@
-7fd3ec6eb3c225f38eb9aaa1293ed772
\ No newline at end of file
+9202459c577bec457e7fa313c8a1578c
\ No newline at end of file
diff --git a/docs/auto_examples/plot_dataframe.rst b/docs/auto_examples/plot_dataframe.rst
index af4b88d0..cd764113 100644
--- a/docs/auto_examples/plot_dataframe.rst
+++ b/docs/auto_examples/plot_dataframe.rst
@@ -32,12 +32,13 @@ presence or absences of the feature (see Pandas.Dataframe.get_dummies for more).
import hypertools as hyp
import pandas as pd
- data = pd.read_csv('sample_data/mushrooms.csv')
+ data = hyp.tools.load('mushrooms')
+
group = data.pop('class')
- hyp.plot(data,'o', group=group)
+ hyp.plot(data, 'o', group=group)
-**Total running time of the script:** ( 0 minutes 0.199 seconds)
+**Total running time of the script:** ( 0 minutes 1.579 seconds)
diff --git a/docs/auto_examples/plot_dataframe_codeobj.pickle b/docs/auto_examples/plot_dataframe_codeobj.pickle
index 3bc4b776..4f8237c8 100644
--- a/docs/auto_examples/plot_dataframe_codeobj.pickle
+++ b/docs/auto_examples/plot_dataframe_codeobj.pickle
@@ -1,2 +1,3 @@
-€}q(U pd.read_csv}q(U module_shortqUpandasqUnameqUread_csvUmoduleqhuUhyp.plot}q(hU
-hypertoolsqhUplothhuu.
\ No newline at end of file
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.plot}q(hU
+hypertoolsqhUplothhuu.
\ No newline at end of file
diff --git a/docs/auto_examples/plot_describe.ipynb b/docs/auto_examples/plot_describe.ipynb
index 2260048f..10024762 100644
--- a/docs/auto_examples/plot_describe.ipynb
+++ b/docs/auto_examples/plot_describe.ipynb
@@ -15,7 +15,7 @@
},
{
"source": [
- "\n# Using describe_pca to evaluate the integrity of your visualization\n\n\nThe downside to using PCA to visualize your data is that some variance will\nlikely be removed. To help get a sense for the integrity of your low\ndimensional visualizations, we built the `describe_pca` function, which computes\nthe covariance (samples by samples) of both the raw and reduced datasets, and\nplots their correlation. The function repeats this analysis from 2:N dimensions\nuntil the correlation reaches a local maximum. Often times this will be less\nthan the total number of dimensions because the PCA model is whitened. \n\n"
+ "\n# Using describe_pca to evaluate the integrity of your visualization\n\n\nThe downside to using PCA to visualize your data is that some variance will\nlikely be removed. To help get a sense for the integrity of your low\ndimensional visualizations, we built the `describe_pca` function, which computes\nthe covariance (samples by samples) of both the raw and reduced datasets, and\nplots their correlation. The function repeats this analysis from 2:N dimensions\nuntil the correlation reaches a local maximum. Often times this will be less\nthan the total number of dimensions because the PCA model is whitened.\n\n"
],
"cell_type": "markdown",
"metadata": {}
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('sample_data/weights.mat')\nw=[i for i in data['weights'][0][0:3]]\n\nhyp.tools.describe_pca(w)"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights_sample')\n\nhyp.tools.describe_pca(data)"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_describe.py b/docs/auto_examples/plot_describe.py
index f87c0837..0bbceab5 100644
--- a/docs/auto_examples/plot_describe.py
+++ b/docs/auto_examples/plot_describe.py
@@ -10,7 +10,7 @@
the covariance (samples by samples) of both the raw and reduced datasets, and
plots their correlation. The function repeats this analysis from 2:N dimensions
until the correlation reaches a local maximum. Often times this will be less
-than the total number of dimensions because the PCA model is whitened.
+than the total number of dimensions because the PCA model is whitened.
"""
# Code source: Andrew Heusser
@@ -20,7 +20,6 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:3]]
+data = hyp.tools.load('weights_sample')
-hyp.tools.describe_pca(w)
+hyp.tools.describe_pca(data)
diff --git a/docs/auto_examples/plot_describe.py.md5 b/docs/auto_examples/plot_describe.py.md5
index a7ba676d..8367a571 100644
--- a/docs/auto_examples/plot_describe.py.md5
+++ b/docs/auto_examples/plot_describe.py.md5
@@ -1 +1 @@
-88d8c06ff67589864459567b58402566
\ No newline at end of file
+c179484603b1e5d3f56d79a70063dfe6
\ No newline at end of file
diff --git a/docs/auto_examples/plot_describe.rst b/docs/auto_examples/plot_describe.rst
index 0289f82e..448704c9 100644
--- a/docs/auto_examples/plot_describe.rst
+++ b/docs/auto_examples/plot_describe.rst
@@ -13,7 +13,7 @@ dimensional visualizations, we built the `describe_pca` function, which computes
the covariance (samples by samples) of both the raw and reduced datasets, and
plots their correlation. The function repeats this analysis from 2:N dimensions
until the correlation reaches a local maximum. Often times this will be less
-than the total number of dimensions because the PCA model is whitened.
+than the total number of dimensions because the PCA model is whitened.
@@ -35,12 +35,11 @@ than the total number of dimensions because the PCA model is whitened.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:3]]
+ data = hyp.tools.load('weights_sample')
- hyp.tools.describe_pca(w)
+ hyp.tools.describe_pca(data)
-**Total running time of the script:** ( 0 minutes 3.749 seconds)
+**Total running time of the script:** ( 0 minutes 5.902 seconds)
diff --git a/docs/auto_examples/plot_describe_codeobj.pickle b/docs/auto_examples/plot_describe_codeobj.pickle
index d13e0a9f..99f7cb40 100644
--- a/docs/auto_examples/plot_describe_codeobj.pickle
+++ b/docs/auto_examples/plot_describe_codeobj.pickle
@@ -1,2 +1,3 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.tools.describe_pca}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.tools.describe_pca}q(hU
hypertoolshU describe_pcahUhypertools.toolsuu.
\ No newline at end of file
diff --git a/docs/auto_examples/plot_group.ipynb b/docs/auto_examples/plot_group.ipynb
index 971668e4..a5faf6cb 100644
--- a/docs/auto_examples/plot_group.ipynb
+++ b/docs/auto_examples/plot_group.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('sample_data/weights.mat')\nw=[i for i in data['weights'][0][0:3]]\n\ngroup = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in w]\nhyp.plot(w,'o',group=group)\n\ngroup=[]\nfor idx,i in enumerate(w):\n tmp=[]\n for iidx,ii in enumerate(i):\n tmp.append(int(np.random.randint(1000, size=1)))\n group.append(tmp)\n\nhyp.plot(w,'o',group=group)"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights_sample')\n\ngroup = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in data]\nhyp.plot(data, 'o', group=group)\n\ngroup=[]\nfor idx,i in enumerate(data):\n tmp=[]\n for iidx,ii in enumerate(i):\n tmp.append(int(np.random.randint(1000, size=1)))\n group.append(tmp)\n\nhyp.plot(data, 'o', group=group)"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_group.py b/docs/auto_examples/plot_group.py
index de2921ef..9b55f312 100644
--- a/docs/auto_examples/plot_group.py
+++ b/docs/auto_examples/plot_group.py
@@ -20,17 +20,16 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:3]]
+data = hyp.tools.load('weights_sample')
-group = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in w]
-hyp.plot(w,'o',group=group)
+group = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in data]
+hyp.plot(data, 'o', group=group)
group=[]
-for idx,i in enumerate(w):
+for idx,i in enumerate(data):
tmp=[]
for iidx,ii in enumerate(i):
tmp.append(int(np.random.randint(1000, size=1)))
group.append(tmp)
-hyp.plot(w,'o',group=group)
+hyp.plot(data, 'o', group=group)
diff --git a/docs/auto_examples/plot_group.py.md5 b/docs/auto_examples/plot_group.py.md5
index d74d231f..5ca4a2ab 100644
--- a/docs/auto_examples/plot_group.py.md5
+++ b/docs/auto_examples/plot_group.py.md5
@@ -1 +1 @@
-27d885882713753a6e646dc241bde2b6
\ No newline at end of file
+4f7e317f92e45ddb0d5607db5dfa5bed
\ No newline at end of file
diff --git a/docs/auto_examples/plot_group.rst b/docs/auto_examples/plot_group.rst
index 36694500..b845f4a5 100644
--- a/docs/auto_examples/plot_group.rst
+++ b/docs/auto_examples/plot_group.rst
@@ -45,22 +45,21 @@ palette.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:3]]
+ data = hyp.tools.load('weights_sample')
- group = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in w]
- hyp.plot(w,'o',group=group)
+ group = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in data]
+ hyp.plot(data, 'o', group=group)
group=[]
- for idx,i in enumerate(w):
+ for idx,i in enumerate(data):
tmp=[]
for iidx,ii in enumerate(i):
tmp.append(int(np.random.randint(1000, size=1)))
group.append(tmp)
- hyp.plot(w,'o',group=group)
+ hyp.plot(data, 'o', group=group)
-**Total running time of the script:** ( 0 minutes 0.349 seconds)
+**Total running time of the script:** ( 0 minutes 1.118 seconds)
diff --git a/docs/auto_examples/plot_group_codeobj.pickle b/docs/auto_examples/plot_group_codeobj.pickle
index e7194c02..3aeee9dc 100644
--- a/docs/auto_examples/plot_group_codeobj.pickle
+++ b/docs/auto_examples/plot_group_codeobj.pickle
@@ -1,2 +1,3 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.plot}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.plot}q(hU
hypertoolsqhUplothhuUnp.random.randint}q(hU numpy.randomhUrandinthU numpy.randomuu.
\ No newline at end of file
diff --git a/docs/auto_examples/plot_labels.ipynb b/docs/auto_examples/plot_labels.ipynb
index b4f9c77a..8dfab8ec 100644
--- a/docs/auto_examples/plot_labels.ipynb
+++ b/docs/auto_examples/plot_labels.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('sample_data/weights.mat')\nw=[i for i in data['weights'][0][0:3]]\n\nlabels=[]\nfor idx,i in enumerate(w):\n tmp=[]\n for iidx,ii in enumerate(i):\n if iidx==0:\n tmp.append('Subject ' + str(idx))\n else:\n tmp.append(None)\n labels.append(tmp)\n\nhyp.plot(w,'o',labels=labels)"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights_sample')\n\nlabels=[]\nfor idx,i in enumerate(data):\n tmp=[]\n for iidx,ii in enumerate(i):\n if iidx==0:\n tmp.append('Subject ' + str(idx))\n else:\n tmp.append(None)\n labels.append(tmp)\n\nhyp.plot(data, 'o', labels=labels)"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_labels.py b/docs/auto_examples/plot_labels.py
index f4c02a22..7883648e 100644
--- a/docs/auto_examples/plot_labels.py
+++ b/docs/auto_examples/plot_labels.py
@@ -16,11 +16,10 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:3]]
+data = hyp.tools.load('weights_sample')
labels=[]
-for idx,i in enumerate(w):
+for idx,i in enumerate(data):
tmp=[]
for iidx,ii in enumerate(i):
if iidx==0:
@@ -29,4 +28,4 @@
tmp.append(None)
labels.append(tmp)
-hyp.plot(w,'o',labels=labels)
+hyp.plot(data, 'o', labels=labels)
diff --git a/docs/auto_examples/plot_labels.py.md5 b/docs/auto_examples/plot_labels.py.md5
index b21a7831..2ab2d6c5 100644
--- a/docs/auto_examples/plot_labels.py.md5
+++ b/docs/auto_examples/plot_labels.py.md5
@@ -1 +1 @@
-22069a217c76ace5effd4c99571c4770
\ No newline at end of file
+f989789e65b40a46806be2433540b56e
\ No newline at end of file
diff --git a/docs/auto_examples/plot_labels.rst b/docs/auto_examples/plot_labels.rst
index f43afe49..c7b6c549 100644
--- a/docs/auto_examples/plot_labels.rst
+++ b/docs/auto_examples/plot_labels.rst
@@ -31,11 +31,10 @@ are simply labeling the first datapoint for each matrix in the list.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:3]]
+ data = hyp.tools.load('weights_sample')
labels=[]
- for idx,i in enumerate(w):
+ for idx,i in enumerate(data):
tmp=[]
for iidx,ii in enumerate(i):
if iidx==0:
@@ -44,9 +43,9 @@ are simply labeling the first datapoint for each matrix in the list.
tmp.append(None)
labels.append(tmp)
- hyp.plot(w,'o',labels=labels)
+ hyp.plot(data, 'o', labels=labels)
-**Total running time of the script:** ( 0 minutes 0.165 seconds)
+**Total running time of the script:** ( 0 minutes 1.602 seconds)
diff --git a/docs/auto_examples/plot_labels_codeobj.pickle b/docs/auto_examples/plot_labels_codeobj.pickle
index 698f0630..4f8237c8 100644
--- a/docs/auto_examples/plot_labels_codeobj.pickle
+++ b/docs/auto_examples/plot_labels_codeobj.pickle
@@ -1,2 +1,3 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.plot}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.plot}q(hU
hypertoolsqhUplothhuu.
\ No newline at end of file
diff --git a/docs/auto_examples/plot_legend.ipynb b/docs/auto_examples/plot_legend.ipynb
index 6ec8509c..db177ebb 100644
--- a/docs/auto_examples/plot_legend.ipynb
+++ b/docs/auto_examples/plot_legend.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('sample_data/weights.mat')\nw=[i for i in data['weights'][0][0:2]]\n\nhyp.plot(w,'o', legend=['Group A', 'Group B'])"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights_sample')\n\nhyp.plot(data, 'o', legend=['Group A', 'Group B', 'Group C'])"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_legend.py b/docs/auto_examples/plot_legend.py
index ee659f1d..7b17bc8c 100644
--- a/docs/auto_examples/plot_legend.py
+++ b/docs/auto_examples/plot_legend.py
@@ -14,7 +14,6 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:2]]
+data = hyp.tools.load('weights_sample')
-hyp.plot(w,'o', legend=['Group A', 'Group B'])
+hyp.plot(data, 'o', legend=['Group A', 'Group B', 'Group C'])
diff --git a/docs/auto_examples/plot_legend.py.md5 b/docs/auto_examples/plot_legend.py.md5
index 0b7591f3..ddd57f1d 100644
--- a/docs/auto_examples/plot_legend.py.md5
+++ b/docs/auto_examples/plot_legend.py.md5
@@ -1 +1 @@
-d776c2c1cd1b8372e6a083d7b3a9ee48
\ No newline at end of file
+cdc39dddb23d4dc264c4a13b0f65e5d1
\ No newline at end of file
diff --git a/docs/auto_examples/plot_legend.rst b/docs/auto_examples/plot_legend.rst
index c17d3649..5a825384 100644
--- a/docs/auto_examples/plot_legend.rst
+++ b/docs/auto_examples/plot_legend.rst
@@ -29,12 +29,11 @@ An example of how to use the `legend` kwarg to generate a legend.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:2]]
+ data = hyp.tools.load('weights_sample')
- hyp.plot(w,'o', legend=['Group A', 'Group B'])
+ hyp.plot(data, 'o', legend=['Group A', 'Group B', 'Group C'])
-**Total running time of the script:** ( 0 minutes 0.088 seconds)
+**Total running time of the script:** ( 0 minutes 1.146 seconds)
diff --git a/docs/auto_examples/plot_legend_codeobj.pickle b/docs/auto_examples/plot_legend_codeobj.pickle
index 698f0630..4f8237c8 100644
--- a/docs/auto_examples/plot_legend_codeobj.pickle
+++ b/docs/auto_examples/plot_legend_codeobj.pickle
@@ -1,2 +1,3 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.plot}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.plot}q(hU
hypertoolsqhUplothhuu.
\ No newline at end of file
diff --git a/docs/auto_examples/plot_missing_data.ipynb b/docs/auto_examples/plot_missing_data.ipynb
index 86223044..60681629 100644
--- a/docs/auto_examples/plot_missing_data.ipynb
+++ b/docs/auto_examples/plot_missing_data.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nfrom scipy.linalg import toeplitz\nimport numpy as np\nfrom copy import copy\nimport hypertools as hyp\n\nK = 10 - toeplitz(np.arange(10))\ndata1 = np.cumsum(np.random.multivariate_normal(np.zeros(10), K, 250), axis=0)\ndata2 = copy(data1)\n\nmissing = .05\ninds = [(i,j) for i in range(data1.shape[0]) for j in range(data1.shape[1])]\nmissing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]\nfor i,j in missing_data:\n data2[i,j]=np.nan\n\ndata1_r,data2_r = hyp.tools.reduce([data1,data2],ndims=3)\n\nmissing_inds = hyp.tools.missing_inds(data2)\nmissing_data = data2_r[missing_inds,:]\n\nhyp.plot([data1_r, data2_r, missing_data], ['r','b--','b*'])"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nfrom scipy.linalg import toeplitz\nimport numpy as np\nfrom copy import copy\nimport hypertools as hyp\n\nK = 10 - toeplitz(np.arange(10))\ndata1 = np.cumsum(np.random.multivariate_normal(np.zeros(10), K, 250), axis=0)\ndata2 = copy(data1)\n\nmissing = .05\ninds = [(i,j) for i in range(data1.shape[0]) for j in range(data1.shape[1])]\nmissing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]\nfor i,j in missing_data:\n data2[i,j]=np.nan\n\ndata1_r,data2_r = hyp.tools.reduce([data1,data2],ndims=3)\n\nmissing_inds = hyp.tools.missing_inds(data2)\nmissing_data = data2_r[missing_inds,:]\n\nhyp.plot([data1_r, data2_r, missing_data], ['r','b--','b*'])"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_missing_data.py b/docs/auto_examples/plot_missing_data.py
index 95ea78ff..79159270 100644
--- a/docs/auto_examples/plot_missing_data.py
+++ b/docs/auto_examples/plot_missing_data.py
@@ -26,7 +26,7 @@
missing = .05
inds = [(i,j) for i in range(data1.shape[0]) for j in range(data1.shape[1])]
-missing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]
+missing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]
for i,j in missing_data:
data2[i,j]=np.nan
diff --git a/docs/auto_examples/plot_missing_data.py.md5 b/docs/auto_examples/plot_missing_data.py.md5
index 966e6c69..b083af00 100644
--- a/docs/auto_examples/plot_missing_data.py.md5
+++ b/docs/auto_examples/plot_missing_data.py.md5
@@ -1 +1 @@
-0ef4dcb947261e30fb08303e827ed748
\ No newline at end of file
+9f84addbf3112f52fd6d6d08e917f2f7
\ No newline at end of file
diff --git a/docs/auto_examples/plot_missing_data.rst b/docs/auto_examples/plot_missing_data.rst
index f1d87213..7294bc03 100644
--- a/docs/auto_examples/plot_missing_data.rst
+++ b/docs/auto_examples/plot_missing_data.rst
@@ -41,7 +41,7 @@ with stars.
missing = .05
inds = [(i,j) for i in range(data1.shape[0]) for j in range(data1.shape[1])]
- missing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]
+ missing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]
for i,j in missing_data:
data2[i,j]=np.nan
@@ -52,7 +52,7 @@ with stars.
hyp.plot([data1_r, data2_r, missing_data], ['r','b--','b*'])
-**Total running time of the script:** ( 0 minutes 0.028 seconds)
+**Total running time of the script:** ( 0 minutes 0.057 seconds)
diff --git a/docs/auto_examples/plot_procrustes.ipynb b/docs/auto_examples/plot_procrustes.ipynb
index 2f664f69..084f439f 100644
--- a/docs/auto_examples/plot_procrustes.ipynb
+++ b/docs/auto_examples/plot_procrustes.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ndata = sio.loadmat('sample_data/test_data.mat')\ntarget = data['spiral']\n\n# A random rotation matrix\nrot = np.array([[-0.89433495, -0.44719485, -0.01348182],\n [-0.43426149, 0.87492975, -0.21427761],\n [-0.10761949, 0.18578133, 0.97667976]])\n# creating new spiral with some noise\nsource = np.dot(target, rot)\n\n# Before hyperalignment\nfig,ax,data = hyp.plot([target, source], show=False, return_data=True)\nax.set_title('Before Procrustes')\nplt.show()\n\n# After hyperalignment\nfig,ax,data = hyp.plot([hyp.tools.procrustes(source, target), target], ['-','--'], show=False, return_data=True)\nax.set_title('After Procrustes')\nplt.show()"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ndata = hyp.tools.load('spiral')\ntarget = data\n\n# A random rotation matrix\nrot = np.array([[-0.89433495, -0.44719485, -0.01348182],\n [-0.43426149, 0.87492975, -0.21427761],\n [-0.10761949, 0.18578133, 0.97667976]])\n# creating new spiral with some noise\nsource = np.dot(target, rot)\n\n# Before hyperalignment\nfig,ax,data = hyp.plot([target, source], show=False, return_data=True)\nax.set_title('Before Procrustes')\nplt.show()\n\n# After hyperalignment\nfig,ax,data = hyp.plot([hyp.tools.procrustes(source, target), target], ['-','--'], show=False, return_data=True)\nax.set_title('After Procrustes')\nplt.show()"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/plot_procrustes.py b/docs/auto_examples/plot_procrustes.py
index e641e25f..575be8fa 100644
--- a/docs/auto_examples/plot_procrustes.py
+++ b/docs/auto_examples/plot_procrustes.py
@@ -18,8 +18,8 @@
import numpy as np
import matplotlib.pyplot as plt
-data = sio.loadmat('sample_data/test_data.mat')
-target = data['spiral']
+data = hyp.tools.load('spiral')
+target = data
# A random rotation matrix
rot = np.array([[-0.89433495, -0.44719485, -0.01348182],
diff --git a/docs/auto_examples/plot_procrustes.py.md5 b/docs/auto_examples/plot_procrustes.py.md5
index b89b115a..e5a9b2bc 100644
--- a/docs/auto_examples/plot_procrustes.py.md5
+++ b/docs/auto_examples/plot_procrustes.py.md5
@@ -1 +1 @@
-af8a2f4eb61db28935f3cd35fb6de594
\ No newline at end of file
+badc20687cdf97685e35dbcb27d19730
\ No newline at end of file
diff --git a/docs/auto_examples/plot_procrustes.rst b/docs/auto_examples/plot_procrustes.rst
index a598475d..4d681d0c 100644
--- a/docs/auto_examples/plot_procrustes.rst
+++ b/docs/auto_examples/plot_procrustes.rst
@@ -43,8 +43,8 @@ space of a target matrix.
import numpy as np
import matplotlib.pyplot as plt
- data = sio.loadmat('sample_data/test_data.mat')
- target = data['spiral']
+ data = hyp.tools.load('spiral')
+ target = data
# A random rotation matrix
rot = np.array([[-0.89433495, -0.44719485, -0.01348182],
@@ -63,7 +63,7 @@ space of a target matrix.
ax.set_title('After Procrustes')
plt.show()
-**Total running time of the script:** ( 0 minutes 0.151 seconds)
+**Total running time of the script:** ( 0 minutes 0.563 seconds)
diff --git a/docs/auto_examples/plot_procrustes_codeobj.pickle b/docs/auto_examples/plot_procrustes_codeobj.pickle
index 73ec5f21..676e11a4 100644
--- a/docs/auto_examples/plot_procrustes_codeobj.pickle
+++ b/docs/auto_examples/plot_procrustes_codeobj.pickle
@@ -1,5 +1,7 @@
€}q(Uplt.show}q(U module_shortqUmatplotlib.pyplotUnameqUshowUmoduleqUmatplotlib.pyplotuUhyp.tools.procrustes}q(hU
hypertoolshU
-procrusteshUhypertools.toolsuU sio.loadmat}q(hUscipy.iohUloadmathUscipy.iouUnp.array}q(hUnumpyq hUarrayhh uUnp.dot}q
-(hUnumpyq hUdothh uUhyp.plot}q (hU
+procrusteshUhypertools.toolsuUnp.array}q(hUnumpyqhUarrayhhuUnp.dot}q (hUnumpyq
+hUdothh
+uUhyp.tools.load}q (hU
+hypertoolshUloadhUhypertools.toolsuUhyp.plot}q (hU
hypertoolsq
hUplothh
uu.
\ No newline at end of file
diff --git a/docs/auto_examples/save_image.ipynb b/docs/auto_examples/save_image.ipynb
index 08a857fe..bae39009 100644
--- a/docs/auto_examples/save_image.ipynb
+++ b/docs/auto_examples/save_image.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('sample_data/weights.mat')\nw=[i for i in data['weights'][0][0:3]]\n\nhyp.plot(w,'o', save_path='test-image.pdf')"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights')\nw=[i for i in data[0:3]]\n\nhyp.plot(w,'o', save_path='test-image.pdf')"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/save_image.py b/docs/auto_examples/save_image.py
index cb0f92a9..5f85d23a 100644
--- a/docs/auto_examples/save_image.py
+++ b/docs/auto_examples/save_image.py
@@ -15,7 +15,7 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:3]]
+data = hyp.tools.load('weights')
+w=[i for i in data[0:3]]
hyp.plot(w,'o', save_path='test-image.pdf')
diff --git a/docs/auto_examples/save_image.rst b/docs/auto_examples/save_image.rst
index 7ab9ae5c..abb3c6eb 100644
--- a/docs/auto_examples/save_image.rst
+++ b/docs/auto_examples/save_image.rst
@@ -22,8 +22,8 @@ the image to be saved, including the file extension (e.g. pdf)
import scipy.io as sio
import numpy as np
- data=sio.loadmat('sample_data/weights.mat')
- w=[i for i in data['weights'][0][0:3]]
+ data = hyp.tools.load('weights')
+ w=[i for i in data[0:3]]
hyp.plot(w,'o', save_path='test-image.pdf')
diff --git a/docs/auto_examples/save_image_codeobj.pickle b/docs/auto_examples/save_image_codeobj.pickle
index 698f0630..4f8237c8 100644
--- a/docs/auto_examples/save_image_codeobj.pickle
+++ b/docs/auto_examples/save_image_codeobj.pickle
@@ -1,2 +1,3 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.plot}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.plot}q(hU
hypertoolsqhUplothhuu.
\ No newline at end of file
diff --git a/docs/auto_examples/save_movie.ipynb b/docs/auto_examples/save_movie.ipynb
index 8c3ab71a..863cc5ca 100644
--- a/docs/auto_examples/save_movie.ipynb
+++ b/docs/auto_examples/save_movie.ipynb
@@ -24,7 +24,7 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata=sio.loadmat('example_data/weights.mat')\nw=data['weights'][0]\nw = [i for i in w]\naligned_w = hyp.tools.align(w)\n\nw1 = np.mean(aligned_w[:17],0)\nw2 = np.mean(aligned_w[18:],0)\n\nhyp.plot([w1,w2], animate=True, zoom=2.5, save_path='animation.mp4')"
+ "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights')\nw = [i for i in data]\naligned_w = hyp.tools.align(w)\n\nw1 = np.mean(aligned_w[:17],0)\nw2 = np.mean(aligned_w[18:],0)\n\nhyp.plot([w1,w2], animate=True, zoom=2.5, save_path='animation.mp4')"
],
"outputs": [],
"metadata": {
diff --git a/docs/auto_examples/save_movie.py b/docs/auto_examples/save_movie.py
index dc9f9255..7e7801d5 100644
--- a/docs/auto_examples/save_movie.py
+++ b/docs/auto_examples/save_movie.py
@@ -16,9 +16,8 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('example_data/weights.mat')
-w=data['weights'][0]
-w = [i for i in w]
+data = hyp.tools.load('weights')
+w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
diff --git a/docs/auto_examples/save_movie.rst b/docs/auto_examples/save_movie.rst
index 75b4d19d..b83cc114 100644
--- a/docs/auto_examples/save_movie.rst
+++ b/docs/auto_examples/save_movie.rst
@@ -23,9 +23,8 @@ depends on having ffmpeg installed on your computer.
import scipy.io as sio
import numpy as np
- data=sio.loadmat('example_data/weights.mat')
- w=data['weights'][0]
- w = [i for i in w]
+ data = hyp.tools.load('weights')
+ w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
diff --git a/docs/auto_examples/save_movie_codeobj.pickle b/docs/auto_examples/save_movie_codeobj.pickle
index 6fd2f1ed..4feadebc 100644
--- a/docs/auto_examples/save_movie_codeobj.pickle
+++ b/docs/auto_examples/save_movie_codeobj.pickle
@@ -1,4 +1,5 @@
-€}q(U sio.loadmat}q(U module_shortqUscipy.ioUnameqUloadmatUmoduleqUscipy.iouUhyp.tools.align}q(hU
+€}q(Uhyp.tools.load}q(U module_shortqU
+hypertoolsUnameqUloadUmoduleqUhypertools.toolsuUhyp.tools.align}q(hU
hypertoolshUalignhUhypertools.toolsuUnp.mean}q(hUnumpyqhUmeanhhuUhyp.plot}q (hU
hypertoolsq
hUplothh
diff --git a/docs/conf.py b/docs/conf.py
index a060d282..d2884c8a 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -64,7 +64,7 @@
# The short X.Y version.
version = u'0.1'
# The full version, including alpha/beta/rc tags.
-release = u'0.1.2'
+release = u'0.1.7'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
diff --git a/docs/doc_requirements.txt b/docs/doc_requirements.txt
index f3f6ad98..1269a613 100644
--- a/docs/doc_requirements.txt
+++ b/docs/doc_requirements.txt
@@ -1,3 +1,4 @@
+sphinx>=1.5.5
sphinx_bootstrap_theme
sphinx-gallery
numpydoc
diff --git a/docs/hypertools.tools.load.rst b/docs/hypertools.tools.load.rst
new file mode 100644
index 00000000..6668815b
--- /dev/null
+++ b/docs/hypertools.tools.load.rst
@@ -0,0 +1,6 @@
+hypertools.tools.load
+=====================
+
+.. currentmodule:: hypertools.tools
+
+.. autofunction:: load
\ No newline at end of file
diff --git a/docs/index.rst b/docs/index.rst
index e9f943e3..b79c7c7e 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -26,4 +26,3 @@ Some key features of HyperTools are:
5. Support for lists of Numpy arrays or Pandas dataframes
.. toctree::
- :maxdepth: 2
diff --git a/docs/modules/generated/hypertools.tools.load.examples b/docs/modules/generated/hypertools.tools.load.examples
new file mode 100644
index 00000000..e69de29b
diff --git a/examples/animate.py b/examples/animate.py
index bcee52a3..9f6e8365 100644
--- a/examples/animate.py
+++ b/examples/animate.py
@@ -16,12 +16,11 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=data['weights'][0]
-w = [i for i in w]
+data = hyp.tools.load('weights')
+w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
w2 = np.mean(aligned_w[18:],0)
-hyp.plot([w1,w2],animate=True, duration=100)
+hyp.plot([w1,w2],animate=True)
diff --git a/examples/explore.py b/examples/explore.py
index fae6367e..32d05b5b 100644
--- a/examples/explore.py
+++ b/examples/explore.py
@@ -19,7 +19,6 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:2]]
+data = hyp.tools.load('weights_sample')
-hyp.plot(w,'o', explore=True)
+hyp.plot(data, 'o', explore=True)
diff --git a/examples/plot_PPCA.py b/examples/plot_PPCA.py
index 919eb3ed..11a741f2 100644
--- a/examples/plot_PPCA.py
+++ b/examples/plot_PPCA.py
@@ -26,7 +26,7 @@
missing = .1
inds = [(i,j) for i in range(data2.shape[0]) for j in range(data2.shape[1])]
-missing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]
+missing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]
for i,j in missing_data:
data2[i,j]=np.nan
diff --git a/examples/plot_align.py b/examples/plot_align.py
index ba9484ae..f247c184 100644
--- a/examples/plot_align.py
+++ b/examples/plot_align.py
@@ -17,10 +17,8 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-
-w=data['weights'][0]
-w = [i for i in w]
+data = hyp.tools.load('weights')
+w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
diff --git a/examples/plot_basic.py b/examples/plot_basic.py
index 6743d259..9ac9d401 100644
--- a/examples/plot_basic.py
+++ b/examples/plot_basic.py
@@ -13,10 +13,7 @@
# License: MIT
import hypertools as hyp
-import scipy.io as sio
-import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:2]]
+data = hyp.tools.load('weights_sample')
-hyp.plot(w,'o')
+hyp.plot(data,'o')
diff --git a/examples/plot_clusters.py b/examples/plot_clusters.py
index ca15f86f..a4e855cb 100644
--- a/examples/plot_clusters.py
+++ b/examples/plot_clusters.py
@@ -16,6 +16,6 @@
import hypertools as hyp
import pandas as pd
-data=pd.read_csv('sample_data/mushrooms.csv')
+data = hyp.tools.load('mushrooms')
hyp.plot(data,'o',n_clusters=10)
diff --git a/examples/plot_customize_figure.py b/examples/plot_customize_figure.py
index c1acb35a..3b83d609 100644
--- a/examples/plot_customize_figure.py
+++ b/examples/plot_customize_figure.py
@@ -16,10 +16,9 @@
import numpy as np
import matplotlib.pyplot as plt
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:2]]
+data = hyp.tools.load('weights_sample')
-fig,ax,data = hyp.plot(w,'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)
+fig,ax,data = hyp.plot(data[:2], 'o', ndims=2, legend=['Group A', 'Group B'], show=False, return_data=True)
ax.set_title('This is an example title', fontsize=20)
ax.set_ylabel('PCA Dimension 2', fontsize=15)
diff --git a/examples/plot_dataframe.py b/examples/plot_dataframe.py
index d7032354..9b5e0856 100644
--- a/examples/plot_dataframe.py
+++ b/examples/plot_dataframe.py
@@ -17,7 +17,8 @@
import hypertools as hyp
import pandas as pd
-data = pd.read_csv('sample_data/mushrooms.csv')
+data = hyp.tools.load('mushrooms')
+
group = data.pop('class')
-hyp.plot(data,'o', group=group)
+hyp.plot(data, 'o', group=group)
diff --git a/examples/plot_describe.py b/examples/plot_describe.py
index f87c0837..0bbceab5 100644
--- a/examples/plot_describe.py
+++ b/examples/plot_describe.py
@@ -10,7 +10,7 @@
the covariance (samples by samples) of both the raw and reduced datasets, and
plots their correlation. The function repeats this analysis from 2:N dimensions
until the correlation reaches a local maximum. Often times this will be less
-than the total number of dimensions because the PCA model is whitened.
+than the total number of dimensions because the PCA model is whitened.
"""
# Code source: Andrew Heusser
@@ -20,7 +20,6 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:3]]
+data = hyp.tools.load('weights_sample')
-hyp.tools.describe_pca(w)
+hyp.tools.describe_pca(data)
diff --git a/examples/plot_group.py b/examples/plot_group.py
index de2921ef..9b55f312 100644
--- a/examples/plot_group.py
+++ b/examples/plot_group.py
@@ -20,17 +20,16 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:3]]
+data = hyp.tools.load('weights_sample')
-group = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in w]
-hyp.plot(w,'o',group=group)
+group = [['a' if idx % 2 == 0 else 'b' for idx,j in enumerate(i)] for i in data]
+hyp.plot(data, 'o', group=group)
group=[]
-for idx,i in enumerate(w):
+for idx,i in enumerate(data):
tmp=[]
for iidx,ii in enumerate(i):
tmp.append(int(np.random.randint(1000, size=1)))
group.append(tmp)
-hyp.plot(w,'o',group=group)
+hyp.plot(data, 'o', group=group)
diff --git a/examples/plot_labels.py b/examples/plot_labels.py
index f4c02a22..7883648e 100644
--- a/examples/plot_labels.py
+++ b/examples/plot_labels.py
@@ -16,11 +16,10 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:3]]
+data = hyp.tools.load('weights_sample')
labels=[]
-for idx,i in enumerate(w):
+for idx,i in enumerate(data):
tmp=[]
for iidx,ii in enumerate(i):
if iidx==0:
@@ -29,4 +28,4 @@
tmp.append(None)
labels.append(tmp)
-hyp.plot(w,'o',labels=labels)
+hyp.plot(data, 'o', labels=labels)
diff --git a/examples/plot_legend.py b/examples/plot_legend.py
index ee659f1d..7b17bc8c 100644
--- a/examples/plot_legend.py
+++ b/examples/plot_legend.py
@@ -14,7 +14,6 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:2]]
+data = hyp.tools.load('weights_sample')
-hyp.plot(w,'o', legend=['Group A', 'Group B'])
+hyp.plot(data, 'o', legend=['Group A', 'Group B', 'Group C'])
diff --git a/examples/plot_missing_data.py b/examples/plot_missing_data.py
index 95ea78ff..79159270 100644
--- a/examples/plot_missing_data.py
+++ b/examples/plot_missing_data.py
@@ -26,7 +26,7 @@
missing = .05
inds = [(i,j) for i in range(data1.shape[0]) for j in range(data1.shape[1])]
-missing_data = [inds[i] for i in np.random.choice(len(inds), len(inds)*missing)]
+missing_data = [inds[i] for i in np.random.choice(int(len(inds)), int(len(inds)*missing))]
for i,j in missing_data:
data2[i,j]=np.nan
diff --git a/examples/plot_procrustes.py b/examples/plot_procrustes.py
index e641e25f..575be8fa 100644
--- a/examples/plot_procrustes.py
+++ b/examples/plot_procrustes.py
@@ -18,8 +18,8 @@
import numpy as np
import matplotlib.pyplot as plt
-data = sio.loadmat('sample_data/test_data.mat')
-target = data['spiral']
+data = hyp.tools.load('spiral')
+target = data
# A random rotation matrix
rot = np.array([[-0.89433495, -0.44719485, -0.01348182],
diff --git a/examples/sample_data/mushrooms.csv b/examples/sample_data/mushrooms.csv
deleted file mode 100644
index abf74eeb..00000000
--- a/examples/sample_data/mushrooms.csv
+++ /dev/null
@@ -1,8125 +0,0 @@
-class,cap-shape,cap-surface,cap-color,bruises,odor,gill-attachment,gill-spacing,gill-size,gill-color,stalk-shape,stalk-root,stalk-surface-above-ring,stalk-surface-below-ring,stalk-color-above-ring,stalk-color-below-ring,veil-type,veil-color,ring-number,ring-type,spore-print-color,population,habitat
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-e,k,s,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g
-p,k,y,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p
-p,x,s,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d
-p,k,y,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l
-e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,b,c,l
-e,b,f,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g
-e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,b,v,l
-p,k,y,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d
-e,x,y,g,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p
-p,k,s,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l
-e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,y,v,l
-p,k,y,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p
-e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,b,c,l
-e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,b,v,l
-e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,y,c,l
-p,k,y,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p
-e,b,f,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g
-p,k,s,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d
-p,k,s,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d
-p,k,y,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l
-p,k,s,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d
-e,x,f,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g
-e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,o,v,l
-p,k,y,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d
-e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,n,v,l
-e,b,f,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g
-e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,y,v,l
-e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,o,v,l
-p,k,s,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l
-p,k,s,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p
-p,k,s,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d
-p,k,s,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p
-p,k,y,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l
-e,k,f,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g
-p,k,y,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l
-e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,b,v,l
-p,k,s,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p
-e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,b,c,l
-e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,b,c,l
-e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,n,c,l
-p,k,y,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l
-e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,y,v,l
-p,k,y,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p
-e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,y,v,l
-e,b,f,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g
-e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,o,c,l
-e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,y,c,l
-e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,o,v,l
-e,b,f,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g
-p,k,y,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l
-p,k,s,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d
-p,k,y,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p
-p,k,s,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p
-p,k,y,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l
-e,b,f,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g
-e,k,f,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g
-e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,o,v,l
-p,x,s,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p
-e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,n,v,l
-p,k,y,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d
-p,k,s,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d
-p,k,y,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p
-p,k,y,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p
-p,x,s,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d
-e,b,s,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g
-p,x,y,c,f,m,f,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d
-e,k,f,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g
-p,k,y,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l
-p,k,s,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d
-e,k,f,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g
-e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,b,v,l
-p,k,s,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p
-e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,n,c,l
-e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,o,c,l
-e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,n,v,l
-e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,y,v,l
-e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,n,v,l
-e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,n,c,l
-p,k,y,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l
-e,b,s,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g
-e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,n,v,l
-e,k,s,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g
-e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,b,v,l
-p,k,y,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d
-p,f,y,c,f,m,a,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d
-e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,o,v,l
-p,k,y,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l
-p,k,s,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d
-p,k,y,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d
-e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,b,c,l
-e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,b,v,l
-e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,b,c,l
-p,k,y,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l
-e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,o,c,l
\ No newline at end of file
diff --git a/examples/sample_data/test_data.mat b/examples/sample_data/test_data.mat
deleted file mode 100644
index 7f53faef..00000000
Binary files a/examples/sample_data/test_data.mat and /dev/null differ
diff --git a/examples/sample_data/weights.mat b/examples/sample_data/weights.mat
deleted file mode 100644
index 05c27174..00000000
Binary files a/examples/sample_data/weights.mat and /dev/null differ
diff --git a/examples/save_image.py b/examples/save_image.py
index cb0f92a9..5f85d23a 100644
--- a/examples/save_image.py
+++ b/examples/save_image.py
@@ -15,7 +15,7 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('sample_data/weights.mat')
-w=[i for i in data['weights'][0][0:3]]
+data = hyp.tools.load('weights')
+w=[i for i in data[0:3]]
hyp.plot(w,'o', save_path='test-image.pdf')
diff --git a/examples/save_movie.py b/examples/save_movie.py
index dc9f9255..7e7801d5 100644
--- a/examples/save_movie.py
+++ b/examples/save_movie.py
@@ -16,9 +16,8 @@
import scipy.io as sio
import numpy as np
-data=sio.loadmat('example_data/weights.mat')
-w=data['weights'][0]
-w = [i for i in w]
+data = hyp.tools.load('weights')
+w = [i for i in data]
aligned_w = hyp.tools.align(w)
w1 = np.mean(aligned_w[:17],0)
diff --git a/hypertools/_externals/ppca.py b/hypertools/_externals/ppca.py
index 233896bb..0cefe0f3 100644
--- a/hypertools/_externals/ppca.py
+++ b/hypertools/_externals/ppca.py
@@ -111,10 +111,6 @@ def fit(self, data, d=None, tol=1e-4, min_obs=10, verbose=False):
self.eig_vals = vals
self._calc_var()
- import IPython
- IPython.embed()
- assert False
-
def transform(self, data=None):
if self.C is None:
diff --git a/hypertools/tools/__init__.py b/hypertools/tools/__init__.py
index d810bd53..63775a4a 100644
--- a/hypertools/tools/__init__.py
+++ b/hypertools/tools/__init__.py
@@ -8,3 +8,4 @@
from .df2mat import df2mat
from .normalize import normalize
from .procrustes import procrustes
+from .load import load
diff --git a/hypertools/tools/load.py b/hypertools/tools/load.py
new file mode 100644
index 00000000..275de40b
--- /dev/null
+++ b/hypertools/tools/load.py
@@ -0,0 +1,55 @@
+import requests
+import pickle
+import pandas as pd
+import sys
+
+def load(dataset):
+ """
+ Load example data
+
+ Parameters
+ ----------
+ dataset : string
+ The name of the example dataset. `weights` is an fmri dataset comprised of
+ 36 subjects. For each subject, the rows are fMRI measurements and the columns
+ are parameters of a model fit to the fMRI data. `weights_sample` is a
+ sample of 3 subjects from that dataset. `weights_avg` is the dataset split
+ in half and averaged into two groups. `spiral` is 3D spiral to
+ highlight the `procrustes` function. `mushrooms` is an example dataset
+ comprised of features (columns) of a collection of mushroomm samples (rows).
+
+ Returns
+ ----------
+ data : Numpy Array
+ Example data
+
+ """
+ if sys.version_info[0]==3:
+ pickle_options = {
+ 'encoding' : 'latin1'
+ }
+ else:
+ pickle_options = {}
+
+ if dataset is 'weights':
+ fileid = '0B7Ycm4aSYdPPREJrZ2stdHBFdjg'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pickle.loads(requests.get(url, stream=True).content, **pickle_options)
+ if dataset is 'weights_avg':
+ fileid = '0B7Ycm4aSYdPPRmtPRnBJc3pieDg'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pickle.loads(requests.get(url, stream=True).content, **pickle_options)
+ if dataset is 'weights_sample':
+ fileid = '0B7Ycm4aSYdPPTl9IUUVlamJ2VjQ'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pickle.loads(requests.get(url, stream=True).content, **pickle_options)
+ elif dataset is 'spiral':
+ fileid = '0B7Ycm4aSYdPPQS0xN3FmQ1FZSzg'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pickle.loads(requests.get(url, stream=True).content, **pickle_options)
+ elif dataset is 'mushrooms':
+ fileid = '0B7Ycm4aSYdPPY3J0U2tRNFB4T3c'
+ url = 'https://docs.google.com/uc?export=download&id=' + fileid
+ data = pd.read_csv(url)
+
+ return data
diff --git a/hypertools/tools/reduce.py b/hypertools/tools/reduce.py
index bc032d7d..9c8e1b6d 100644
--- a/hypertools/tools/reduce.py
+++ b/hypertools/tools/reduce.py
@@ -54,8 +54,8 @@ def reducePCA(x, ndim):
warnings.warn('Missing data: Inexact solution computed with PPCA (see https://github.com/allentran/pca-magic for details)')
# ppca if missing data
- m = PPCA(np.vstack(x))
- m.fit(d=ndim)
+ m = PPCA()
+ m.fit(data=np.vstack(x), d=ndim)
x_pca = m.transform()
# if the whole row is missing, return nans
diff --git a/requirements.txt b/requirements.txt
index f5ae7989..b1e74d70 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -6,3 +6,4 @@ matplotlib>=1.5.1
scipy>=0.17.1
numpy>=1.10.4
future
+requests
diff --git a/tests/test_align.py b/tests/test_align.py
index ce219f07..a21550e9 100644
--- a/tests/test_align.py
+++ b/tests/test_align.py
@@ -1,14 +1,13 @@
# -*- coding: utf-8 -*-
import pytest
-
-import scipy.io as sio
import numpy as np
from hypertools.tools.align import align
+from hypertools.tools.load import load
+
def test_procrustes():
- data = sio.loadmat('examples/sample_data/test_data.mat')
- data1 = data['spiral']
+ data1 = load('spiral')
rot = np.array([[-0.89433495, -0.44719485, -0.01348182],
[-0.43426149, 0.87492975, -0.21427761],
[-0.10761949, 0.18578133, 0.97667976]])
@@ -17,8 +16,7 @@ def test_procrustes():
assert np.allclose(result[0],result[1])
def test_srm():
- data = sio.loadmat('examples/sample_data/test_data.mat')
- data1 = data['spiral']
+ data1 = load('spiral')
rot = np.array([[-0.89433495, -0.44719485, -0.01348182],
[-0.43426149, 0.87492975, -0.21427761],
[-0.10761949, 0.18578133, 0.97667976]])
diff --git a/tests/test_procrustes.py b/tests/test_procrustes.py
index db2f376d..e28bba4e 100644
--- a/tests/test_procrustes.py
+++ b/tests/test_procrustes.py
@@ -6,10 +6,10 @@
import numpy as np
from hypertools.tools.procrustes import procrustes
+from hypertools.tools.load import load
def test_procrustes_func():
- data = sio.loadmat('examples/sample_data/test_data.mat')
- target = data['spiral']
+ target = load('spiral')
rot = np.array([[-0.89433495, -0.44719485, -0.01348182],
[-0.43426149, 0.87492975, -0.21427761],
[-0.10761949, 0.18578133, 0.97667976]])
+
