Merge master into v1.5

.travis.yml

@@ -23,9 +23,25 @@ matrix:
     - language: generic
       os: osx
       env: pymajor=2
+      addons:
+        homebrew:
+          packages:
+            - python2
+            - cmake
+            - cppunit
+            - hdf5
+            - numpy
     - language: generic
       os: osx
       env: pymajor=3
+      addons:
+        homebrew:
+          packages:
+            - python3
+            - cmake
+            - cppunit
+            - hdf5
+            - numpy
 
 addons:
   apt:
@@ -40,15 +56,9 @@ before_install:
   - export NIX_INCDIR=${nixprefix}/include/nixio-1.0
   - export NIX_LIBDIR=${nixprefix}/lib
   - export PKG_CONFIG_PATH=${PKG_CONFIG_PATH}:${nixprefix}/lib/pkgconfig
-  - if [[ "${TRAVIS_OS_NAME}" == "osx" ]]; then
-      brew upgrade cmake;
-      brew install cppunit hdf5;
-      if [[ "${pymajor}" == "3" ]]; then
-        brew upgrade python${pymajor} || true;
-      else
-        alias pip2='pip';
-      fi;
-    fi
+  - alias pip2='pip'
+  - if [[ "${TRAVIS_OS_NAME}" != "osx" ]]; then pip${pymajor} install --upgrade numpy; fi
+  - pip${pymajor} install --upgrade coveralls h5py pytest-xdist;
   - git clone --branch ${NIX_BRANCH} https://github.com/G-Node/nix /tmp/libnix
   - pushd /tmp/libnix
   - mkdir build
@@ -59,7 +69,6 @@ before_install:
   - popd
   - popd
   - which pip${pymajor}
-  - pip${pymajor} install --upgrade --no-binary ":all:" numpy coveralls h5py pytest-xdist
   - which python${pymajor}
   - python${pymajor} --version
 
@@ -68,9 +77,9 @@ install:
 
 script:
   - if [[ "${coveralls}" == 1 ]]; then
-      coverage run --source=nixio setup.py test --addopts "--force-compat -s" && coverage report -m;
+      coverage run --source=nixio setup.py test --addopts "--nix-compat -s" && coverage report -m;
     else
-      python${pymajor} setup.py test --addopts "--force-compat -s -nauto";
+      python${pymajor} setup.py test --addopts "--nix-compat -s -nauto";
     fi
 
 after_success:

conftest.py

@@ -1,6 +1,30 @@
+import pytest
+import tempfile
+from nixio.test.xcompat.compile import maketests
+
+
+BINDIR = tempfile.mkdtemp(prefix="nixpy-tests-")
+
+
 def pytest_addoption(parser):
-    parser.addoption("--force-compat",
-                     action="store_true",
-                     default=False,
-                     help=("Force cross-compatibility tests. "
-                           "Raise error instead of skipping."))
+    parser.addoption("--nix-compat", action="store_true", default=False,
+                     help=("Run nix compatibility tests "
+                           "(requires NIX library)"))
+
+
+@pytest.fixture
+def bindir(request):
+    return BINDIR
+
+
+def pytest_collection_modifyitems(config, items):
+    if config.getoption("--nix-compat"):
+        print("Compiling NIX compatibility tests")
+        maketests(BINDIR)
+        return
+    skip_compat = pytest.mark.skip(
+        reason="Use --nix-compat option to run compatibility tests"
+    )
+    for item in items:
+        if "compatibility" in item.keywords:
+            item.add_marker(skip_compat)

docs/source/examples/fileCreate.py

@@ -9,27 +9,31 @@
 file_name = 'file_create_example.h5'
 
 # create a new file overwriting any existing content
-file = nix.File.open(file_name, nix.FileMode.Overwrite)
-print(file.format, file.version, file.created_at)
+nixfile = nix.File.open(file_name, nix.FileMode.Overwrite)
+print(nixfile.format, nixfile.version, nixfile.created_at)
 
 # close file
-file.close()
+nixfile.close()
 
 # re-open file for read-only access
-file  = nix.File.open(file_name, nix.FileMode.ReadOnly)
+nixfile = nix.File.open(file_name, nix.FileMode.ReadOnly)
 
 # this command will fail putting out HDF5 Errors
-file.create_block("test block", "test")
+try:
+    nixfile.create_block("test block", "test")
+except ValueError:
+    print("Error caught: cannot create a new group in nix.FileMode.ReadOnly mode")
 
-file.close()
+
+nixfile.close()
 
 # re-open for read-write access
-file = nix.File.open(file_name, nix.FileMode.ReadWrite)
+nixfile = nix.File.open(file_name, nix.FileMode.ReadWrite)
 
 # the following command now works fine
-file.create_block("test block", "test")
+nixfile.create_block("test block", "test")
 
-file.close()
+nixfile.close()
 
 
 

docs/source/examples/imageData.py

@@ -1,7 +1,8 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
-"""Copyright © 2014 German Neuroinformatics Node (G-Node)
+"""
+ Copyright © 2014 German Neuroinformatics Node (G-Node)
 
  All rights reserved.
 
@@ -13,8 +14,8 @@
 
  This tutorial shows how to store image data in nix-files.
  See https://github.com/G-node/nix/wiki for more information.
- 
- We use the "Lenna" image in this tutorial.  
+
+ We use the "Lenna" image in this tutorial.
 
  "Lenna" by Original full portrait: "Playmate of the Month". Playboy
  Magazine. November 1972, photographed by Dwight Hooker.This 512x512
@@ -27,7 +28,7 @@
 
 import nixio as nix
 import numpy as np
-import Image as img
+from PIL import Image as img
 
 
 def load_image():
@@ -43,7 +44,7 @@ def plot_data(data_array):
     img_data = np.array(img_data, dtype='uint8')
     new_img = img.fromarray(img_data)
     new_img.show()
-        
+
 
 if __name__ == '__main__':
     img_data, channels = load_image()
@@ -52,7 +53,7 @@ def plot_data(data_array):
     file = nix.File.open(file_name, nix.FileMode.Overwrite)
 
     # create a 'Block' that represents a grouping object. Here, the recording session.
-    # it gets a name and a type 
+    # it gets a name and a type
     block = file.create_block("block name", "nix.session")
 
     # create a 'DataArray' to take the sinewave, add some information about the signal
@@ -64,7 +65,7 @@ def plot_data(data_array):
     width_dim.label = "width"
     color_dim = data.append_set_dimension()
     color_dim.labels = channels
-    
+
     # let's plot the data from the stored information
     plot_data(data)
     file.close()

docs/source/examples/imageWithMetadata.py

@@ -13,8 +13,8 @@
 
  This tutorial shows how to store image data in nix-files.
  See https://github.com/G-node/nix/wiki for more information.
- 
- We use the "Lenna" image in this tutorial.  
+
+ We use the "Lenna" image in this tutorial.
 
  "Lenna" by Original full portrait: "Playmate of the Month". Playboy
  Magazine. November 1972, photographed by Dwight Hooker.This 512x512
@@ -27,7 +27,7 @@
 
 import nixio as nix
 import numpy as np
-import Image as img
+from PIL import Image as img
 import matplotlib.pyplot as plt
 
 
@@ -49,7 +49,7 @@ def print_metadata_table(section, ax):
         nrows, ncols = len(cell_text)+1, len(columns)
         ax.axis('off')
         the_table = ax.table(cellText=cell_text,
-                               colLabels=columns, 
+                               colLabels=columns,
                                loc='center')
         for cell in the_table.get_children():
             cell.set_height(.075)
@@ -72,13 +72,13 @@ def plot_data(data_array):
     fig = plt.figure()
     img_axis = fig.add_subplot(121)
     img_axis.imshow(new_img)
-    
+
     info_axis = fig.add_subplot(122)
     print_metadata_table(data.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()
-        
+
 
 def add_image_information(nix_file):
     section = nix_file.create_section('Image metadata', 'image_source')

docs/source/examples/irregularlySampledData.py

@@ -21,7 +21,7 @@
 
 
 def create_data(duration, interval):
-    times = np.around(np.cumsum(np.random.poisson(interval*1000, 1.5*duration/interval))/1000., 3)
+    times = np.around(np.cumsum(np.random.poisson(interval*1000, int(1.5*duration/interval)))/1000., 3)
     times = times[times <= duration]
     x = np.arange(0, times[-1] * 2 * np.pi, 0.001)
     y = np.sin(5 * x)
@@ -31,7 +31,7 @@ def create_data(duration, interval):
 def plot_data(data_array):
     x_axis = data_array.dimensions[0]
     x = list(x_axis.ticks)
-    y = data_array.data
+    y = data_array[:]
     plt.plot(x, y, marker='o', color='dodgerblue')
     plt.xlabel(x_axis.label + " [" + x_axis.unit + "]")
     plt.ylabel(data_array.label + " [" + data_array.unit + "]")

docs/source/examples/multipleROIs.py

@@ -27,7 +27,7 @@
 
 import nixio as nix
 import numpy as np
-import Image as img
+from PIL import Image as img
 import matplotlib.pyplot as plt
 
 
@@ -64,7 +64,7 @@ def plot_roi_data(tag):
     for p in range(position_count):
         roi_data = tag.retrieve_data(p, 0)[:]
         roi_data = np.array(roi_data, dtype='uint8')
-        ax = plt.gcf().add_subplot(position_count, 1, p)
+        ax = plt.gcf().add_subplot(position_count, 1, p+1)
         image = img.fromarray(roi_data)
         ax.imshow(image)
     plt.savefig('retrieved_rois.png')
@@ -93,12 +93,12 @@ def plot_roi_data(tag):
     color_dim.labels = channels
 
     # some space for three regions-of-interest
-    roi_starts = np.zeros((3, 3))
+    roi_starts = np.zeros((3, 3), dtype=int)
     roi_starts[0, :] = [250, 245, 0]
     roi_starts[1, :] = [250, 315, 0]
     roi_starts[2, :] = [340, 260, 0]
 
-    roi_extents = np.zeros((3, 3))
+    roi_extents = np.zeros((3, 3), dtype=int)
     roi_extents[0, :] = [30, 45, 3]
     roi_extents[1, :] = [30, 40, 3]
     roi_extents[2, :] = [25, 65, 3]

docs/source/examples/singleROI.py

@@ -27,7 +27,7 @@
 
 import nixio as nix
 import numpy as np
-import Image as img
+from PIL import Image as img
 
 
 def load_image():
@@ -49,8 +49,9 @@ def plot_data(tag):
     img_data = np.zeros(data_array.data.shape)
     data_array.data.read_direct(img_data)
     img_data = np.array(img_data, dtype='uint8')
-    pos = tag.position
-    ext = tag.extent
+    # positions and extents are double by default, need to convert to int
+    pos = tuple(map(int, tag.position))
+    ext = tuple(map(int, tag.extent))
     draw_rect(img_data, pos, ext)
     new_img = img.fromarray(img_data)
     new_img.show()
@@ -60,11 +61,11 @@ def plot_data(tag):
     img_data, channels = load_image()
     # create a new file overwriting any existing content
     file_name = 'single_roi.h5'
-    file = nix.File.open(file_name, nix.FileMode.Overwrite)
+    f = nix.File.open(file_name, nix.FileMode.Overwrite)
 
     # create a 'Block' that represents a grouping object. Here, the recording session.
     # it gets a name and a type
-    block = file.create_block("block name", "nix.session")
+    block = f.create_block("block name", "nix.session")
 
     # create a 'DataArray' to take the sinewave, add some information about the signal
     data = block.create_data_array("lenna", "nix.image.rgb", data=img_data)
@@ -85,4 +86,4 @@ def plot_data(tag):
 
     # let's plot the data from the stored information
     plot_data(tag)
-    file.close()
+    f.close()

docs/source/examples/spikeFeatures.py

@@ -30,20 +30,20 @@ def fake_neuron(stepsize=0.001, offset=.8, sta_offset=100):
     stimulus = np.random.randn(100000) * 2.5
     b, a = signal.butter(8, 0.25)
     stimulus = signal.filtfilt(b, a, stimulus)
-    lif_model = lif.lif(stepsize=stepsize, offset=offset)
+    lif_model = lif.LIF(stepsize=stepsize, offset=offset)
     time, v, spike_times = lif_model.run_stimulus(stimulus)
     snippets = np.zeros((len(spike_times), 2 * sta_offset))
 
-    for i,t in enumerate(spike_times):
-        index = round(t/stepsize)
+    for i, t in enumerate(spike_times):
+        index = int(round(t/stepsize))
         if index < sta_offset:
             snip = stimulus[0:index + sta_offset]
             snippets[i, -len(snip):] = snip
         elif (index + sta_offset) > len(stimulus):
             snip = stimulus[index-sta_offset:]
             snippets[i, 0:len(snip)] = snip
         else:
-            snippets[i,:] = stimulus[index - sta_offset:index + sta_offset]
+            snippets[i, :] = stimulus[index - sta_offset:index + sta_offset]
     return time, v, spike_times, snippets
 
 

docs/source/examples/spikeTagging.py

@@ -25,7 +25,7 @@
 
 
 def fake_neuron():
-    lif_model = lif.lif()
+    lif_model = lif.LIF()
     t, v, spike_times = lif_model.run_const_stim(10000, 0.005)
     return t, v, spike_times
 

docs/source/examples/untaggedFeature.py

@@ -28,13 +28,17 @@
 
 def fake_neuron(stepsize=0.001, offset=.8):
     stimulus = np.random.randn(80000) * 2.5
+
     b, a = signal.butter(8, 0.125)
-    stimulus = signal.filtfilt(b, a, stimulus)
+    stimulus = signal.filtfilt(b, a, stimulus[:])
+
     s = np.hstack((np.zeros(10000), stimulus, np.zeros(10000)))
-    lif_model = lif.lif(stepsize=stepsize, offset=offset)
+    lif_model = lif.LIF(stepsize=stepsize, offset=offset)
     time, v, spike_times = lif_model.run_stimulus(s)
+
     stimulus_onset = 10000*stepsize
     stimulus_duration = len(stimulus)*stepsize
+
     return time, v, stimulus, stimulus_onset, stimulus_duration
 
 
@@ -77,7 +81,7 @@ def plot_data(tag):
                        stim_onset, color='silver', alpha=0.25, zorder=0, label="stimulus epoch")
     response_axis.legend()
 
-    stimulus_axis.plot(stimulus_time, stimulus, color="slategray", label="stimulus")
+    stimulus_axis.plot(stimulus_time, stimulus[:], color="slategray", label="stimulus")
     stimulus_axis.set_xlabel(stim_time_dim.label + ((" [" + stim_time_dim.unit + "]") if stim_time_dim.unit else ""))
     stimulus_axis.set_ylabel(stimulus_array.label + ((" [" + stimulus_array.unit + "]") if stimulus_array.unit else ""))
     stimulus_axis.set_xlim(np.min(stimulus_time), np.max(stimulus_time))