fix test warnings

docs/source/examples/categoryData.py

@@ -3,6 +3,7 @@
 import nixio
 import matplotlib.pyplot as plt
 
+import docutils
 
 def create_data():
     categories = ["Jan", "Feb", "Mar", "Apr", "May", "Jun"]
@@ -23,7 +24,10 @@ def plot(data_array):
     plt.bar(range(data_array.shape[0]), data_array[:], color="tab:blue")
     plt.xticks(range(data_array.shape[0]), labels=data_array.dimensions[0].labels)
     plt.ylabel("%s %s" % (data_array.label, "[%s]" % data_array.unit if data_array.unit else ""))
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        plt.show()
 
 
 def main():

docs/source/examples/docutils.py

@@ -0,0 +1,4 @@
+import os
+
+def is_running_under_pytest():
+    return "PYTEST_CURRENT_TEST" in os.environ

docs/source/examples/imageData.py

@@ -29,6 +29,8 @@
 import numpy as np
 from PIL import Image as img
 
+import docutils
+
 
 def load_image():
     image = img.open('lenna.png')
@@ -42,7 +44,8 @@ def plot_data(data_array):
     data_array.read_direct(img_data)
     img_data = np.array(img_data, dtype='uint8')
     new_img = img.fromarray(img_data)
-    new_img.show()
+    if not docutils.is_running_under_pytest():
+        new_img.show()
 
 
 if __name__ == '__main__':

docs/source/examples/imageWithMetadata.py

@@ -23,12 +23,14 @@
  http://en.wikipedia.org/wiki/File:Lenna.png#mediaviewer/File:Lenna.png
 
 """
-
-import nixio as nix
 import numpy as np
-from PIL import Image as img
+import nixio as nix
 import matplotlib.pyplot as plt
 
+import docutils
+
+from PIL import Image as img
+
 
 def print_metadata_table(section, ax):
     columns = ['Name', 'Value']
@@ -73,10 +75,13 @@ def plot_data(data_array):
     img_axis.imshow(new_img)
 
     info_axis = fig.add_subplot(122)
-    print_metadata_table(data.metadata, info_axis)
+    print_metadata_table(data_array.metadata, info_axis)
     fig.subplots_adjust(left=0.075, right=0.975, bottom=0.075, top=0.975)
-    fig.savefig('image_with_metadata.png')
-    fig.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        fig.savefig('image_with_metadata.png')
+        fig.show()
 
 
 def add_image_information(nix_file):

docs/source/examples/irregularlySampledData.py

@@ -18,6 +18,8 @@
 import numpy as np
 import matplotlib.pyplot as plt
 
+import docutils
+
 
 def create_data(duration, interval):
     times = np.around(np.cumsum(np.random.poisson(interval * 1000, int(1.5 * duration / interval))) / 1000., 3)
@@ -37,7 +39,10 @@ def plot_data(data_array):
     plt.legend()
     plt.xlim([0, x[-1]])
     plt.ylim(np.min(y) * 1.1, np.max(y) * 1.1)
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        plt.show()
 
 
 def main():

docs/source/examples/multipleROIs.py

@@ -29,6 +29,8 @@
 from PIL import Image as img
 import matplotlib.pyplot as plt
 
+import docutils
+
 
 def load_image():
     image = img.open('lenna.png')
@@ -57,8 +59,12 @@ def plot_data(tag):
     # new_img = img.fromarray(img_data)
     plt.imshow(img_data)
     plt.gcf().set_size_inches((5.5, 5.5))
-    # plt.savefig("../images/multiple_rois.png")
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        # plt.savefig("../images/multiple_rois.png")
+        plt.show()
+
 
 def plot_roi_data(tag):
     position_count = tag.positions.shape[0]
@@ -71,8 +77,11 @@ def plot_roi_data(tag):
         image = img.fromarray(roi_data)
         ax.imshow(image)
 
-    # fig.savefig('../images/retrieved_rois.png')
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        # fig.savefig('../images/retrieved_rois.png')
+        plt.show()
 
 
 def main():

docs/source/examples/multipleTimeSeries.py

@@ -18,6 +18,8 @@
 import numpy as np
 import matplotlib.pylab as plt
 
+import docutils
+
 
 def create_data(duration=1, freq=10, stepsize=0.01):
     x = np.arange(0, duration * 2 * np.pi, stepsize)
@@ -42,8 +44,11 @@ def plot_data(data_array):
     plt.xlim(0, np.max(x))
     plt.ylim((1.1 * np.min(y), 1.1 * np.max(y)))
     plt.legend()
-    plt.savefig('multiple_time_series.png')
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        plt.savefig('multiple_time_series.png')
+        plt.show()
 
 def main():
     # fake some data

docs/source/examples/multiple_points.py

@@ -1,4 +1,5 @@
 import nixio
+import docutils
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -36,8 +37,11 @@ def plot(multi_tag):
     ax.spines["right"].set_visible(False)
     fig.subplots_adjust(bottom=0.175, left=0.15, right=0.95, top=0.95)
     ax.legend(loc=3, frameon=False, ncol=2)
-    # fig.savefig("../images/multiple_points.png")
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        # fig.savefig("../images/multiple_points.png")
+        plt.show()
 
 
 def main():

docs/source/examples/multiple_regions.py

@@ -1,8 +1,10 @@
-import numpy as np
 import nixio
+import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib.patches as patches
 
+import docutils
+
 
 def create_example_data(nixfile):
     sampling_interval = 0.001
@@ -79,8 +81,11 @@ def plot(nixfile):
     ax.spines["top"].set_visible(False)
     ax.spines["right"].set_visible(False)
     fig.subplots_adjust(bottom=0.175, left=0.15, right=0.95, top=0.95)
-    # fig.savefig("../images/multiple_regions.png")
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        # fig.savefig("../images/multiple_regions.png")
+        plt.show()
 
 
 def plot_tagged_data(nixfile):
@@ -106,8 +111,11 @@ def plot_tagged_data(nixfile):
         else:
             ax.set_yticklabels([])
     fig.subplots_adjust(left=0.15, bottom=0.2, wspace=0.5, right=0.975)
-    # fig.savefig("../images/reading_tagged_data.png")
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        # fig.savefig("../images/reading_tagged_data.png")
+        plt.show()
 
 
 def main():

docs/source/examples/regularlySampledData.py

@@ -18,6 +18,8 @@
 import numpy as np
 import matplotlib.pyplot as plt
 
+import docutils
+
 
 def create_sinewave(duration=1, freq=10, stepsize=0.01):
     x = np.arange(0, duration * 2 * np.pi, stepsize)
@@ -36,7 +38,10 @@ def plot_data(data_array):
     plt.xlim(0, np.max(x))
     plt.ylim((1.1 * np.min(y), 1.1 * np.max(y)))
     plt.legend()
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        plt.show()
 
 
 def main():

docs/source/examples/singleROI.py

@@ -26,6 +26,8 @@
 import numpy as np
 from PIL import Image as img
 
+import docutils
+
 
 def load_image():
     image = img.open('lenna.png')
@@ -51,9 +53,9 @@ def plot_data(tag):
     ext = tuple(map(int, tag.extent))
     draw_rect(img_data, pos, ext)
     new_img = img.fromarray(img_data)
-
-    # new_img.save("../images/single_roi.png")
-    new_img.show()
+    if not docutils.is_running_under_pytest():
+        # new_img.save("../images/single_roi.png")
+        new_img.show()
 
 
 def main():

docs/source/examples/spikeFeatures.py

@@ -14,13 +14,13 @@
  See https://github.com/G-node/nix/wiki for more information.
 
 """
-
-import lif
 import nixio
 import numpy as np
 import scipy.signal as signal
 import matplotlib.pylab as plt
 
+import lif
+import docutils
 
 def fake_neuron(stepsize=0.001, offset=.8, sta_offset=1000):
     stimulus = np.random.randn(102000) * 3.5
@@ -97,7 +97,10 @@ def plot_data(tag):
     plt.subplots_adjust(left=0.15, top=0.875, bottom=0.1, right=0.98, hspace=0.35, wspace=0.25)
     plt.gcf().set_size_inches((5.5, 4.5))
     # plt.savefig("../images/spike_features.png")
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        plt.show()
 
 
 def main():

docs/source/examples/spikeTagging.py

@@ -20,6 +20,8 @@
 import numpy as np
 import matplotlib.pylab as plt
 
+import docutils
+
 
 def fake_neuron():
     lif_model = lif.LIF(offset=1.0)
@@ -48,8 +50,11 @@ def plot_data(tag):
     ax.set_ylim((1.5 * np.min(voltage), 1.5 * np.max(voltage)))
     ax.legend()
     fig.subplots_adjust(bottom=0.175, top=0.975, right=0.975)
-    # fig.savefig("../images/spike_tagging.png")
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        # fig.savefig("../images/spike_tagging.png")
+        plt.show()
 
 
 if __name__ == '__main__':

docs/source/examples/taggedFeature.py

@@ -15,11 +15,13 @@
 
 """
 import nixio
-import lif
 import numpy as np
 import scipy.signal as signal
 import matplotlib.pyplot as plt
 
+import lif
+import docutils
+
 
 def fake_neuron(stepsize=0.001, offset=.8):
     stimulus = np.random.randn(102000) * 2.5
@@ -119,7 +121,10 @@ def plot_data(tag):
     plt.subplots_adjust(left=0.125, top=0.975, bottom=0.1, right=0.98, hspace=0.25, wspace=0.35)
     plt.gcf().set_size_inches((5.5, 4.5))
     # plt.savefig('../images/tagged_feature.png')
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        plt.show()
 
 
 if __name__ == '__main__':

docs/source/examples/tagging_example.py

@@ -1,7 +1,9 @@
-import matplotlib.pyplot as plt
-import scipy.signal as signal
-import numpy as np
 import nixio
+import numpy as np
+import scipy.signal as signal
+import matplotlib.pyplot as plt
+
+import docutils
 
 interval = 0.001
 duration = 3.5
@@ -56,7 +58,10 @@ def plot(time, response):
                 arrowprops=dict(facecolor='silver', connectionstyle="arc3", arrowstyle="->"),
                 )
     # fig.savefig('../images/tag2.png')
-    plt.show()
+    if docutils.is_running_under_pytest():
+        plt.close()
+    else:
+        plt.show()
 
 
 def create_data():