Merge pull request #59 from brianhie/matplotlib_backend

remove changes to matplotlib defaults

bin/mouse_brain_sketched.py

@@ -43,27 +43,28 @@
 
     datasets = datasets_merged
 
-    labels = []
     names = []
-    curr_label = 0
     for i, a in enumerate(datasets_dimred):
-        labels += list(np.zeros(a.shape[0]) + curr_label)
         names.append(data_names[i])
-        curr_label += 1
-    labels = np.array(labels, dtype=int)
 
     mouse_brain_genes = [
         'Gja1', 'Flt1', 'Gabra6', 'Syt1', 'Gabrb2', 'Gabra1',
         'Meg3', 'Mbp', 'Rgs5',
     ]
 
     # Downsample for visualization purposes
+    rand_idxs = []
+    labels = []
+    curr_label = 0
     for i in range(len(data_names)):
         ds = datasets_dimred[i]
         rand_idx = np.random.choice(ds.shape[0], size=int(ds.shape[0]/10),
                                     replace=False)
         datasets_dimred[i] = ds[rand_idx, :]
         datasets[i] = datasets[i][rand_idx, :]
+        labels += list(np.zeros(datasets_dimred[i].shape[0]) + curr_label)
+        curr_label += 1
+    labels = np.array(labels, dtype=int)
 
     embedding = visualize(datasets_dimred,
                           labels, NAMESPACE + '_ds', names,

scanorama/__init__.py

@@ -1,3 +1,3 @@
 from .scanorama import *
 
-__version__ = 1.5
+__version__ = 1.5.1

scanorama/utils.py

@@ -1,8 +1,5 @@
 import errno
 from fbpca import pca
-import matplotlib as mpl
-mpl.rcParams['figure.figsize'] = [10.0, 9.0]
-mpl.use('Agg')
 import matplotlib.pyplot as plt
 from matplotlib import cm
 import numpy as np
@@ -22,7 +19,7 @@ def dispersion(X):
     dispersion[mean > 1e-10] = temp.A1
     dispersion[mean <= 1e-10] = float('-inf')
     return dispersion
-        
+
 def reduce_dimensionality(X, dim_red_k=100):
     k = min((dim_red_k, X.shape[0], X.shape[1]))
     U, s, Vt = pca(X, k=k) # Automatically centers.
@@ -48,16 +45,16 @@ def visualize_cluster(coords, cluster, cluster_labels,
                 c=colors[1], s=size)
     plt.title(str(cluster_name))
     plt.savefig(image_fname, dpi=500)
-        
+
 def visualize_expr(X, coords, genes, viz_gene, image_suffix='.svg',
                    new_fig=True, size=1, viz_prefix='ve'):
     genes = [ gene.upper() for gene in genes ]
     viz_gene = viz_gene.upper()
-    
+
     if not viz_gene.upper() in genes:
         sys.stderr.write('Warning: Could not find gene {}\n'.format(viz_gene))
         return
-    
+
     image_fname = '{}_{}{}'.format(
         viz_prefix, viz_gene, image_suffix
     )
@@ -111,7 +108,7 @@ def visualize_dropout(X, coords, image_suffix='.svg',
     plt.scatter(coords[:, 0], coords[:, 1],
                 c=colors, cmap=cm.get_cmap('Reds'), s=size)
     plt.savefig(image_fname, dpi=500)
-    
+
 def mkdir_p(path):
     try:
         os.makedirs(path)

setup.py

@@ -2,10 +2,10 @@
 
 setup(
     name='scanorama',
-    version='1.5',
+    version='1.5.1',
     description='Panoramic stitching of heterogeneous single cell transcriptomic data',
     url='https://github.com/brianhie/scanorama',
-    download_url='https://github.com/brianhie/scanorama/archive/v1.5.tar.gz',
+    download_url='https://github.com/brianhie/scanorama/archive/v1.5.1.tar.gz',
     packages=find_packages(exclude=['bin', 'conf', 'data', 'target']),
     install_requires=[
         'annoy>=1.11.5',