diff --git a/CONTRIBUTING.txt b/CONTRIBUTING.txt
index fcb36547..58b83296 100644
--- a/CONTRIBUTING.txt
+++ b/CONTRIBUTING.txt
@@ -123,9 +123,7 @@ Guidelines
* All code should have tests (see `test coverage`_ below for more details).
* All code should be documented, to the same
- `standard
-<://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt#docstring-standard>`_
- as NumPy and SciPy.
+ `standard <://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt#docstring-standard>`_ as NumPy and SciPy.
* For new functionality, always add an example to the
gallery.
* No changes are ever committed without review. Ask on the
@@ -195,8 +193,8 @@ successfully passes all tests. To do so,
* Go to `Travis-CI `__ and follow the Sign In link at the top
- * Go to your `profile page `__ and switch on your
- scikit-image fork
+ * Go to your `profile page `__ and switch
+ on your scikit-image fork
It corresponds to steps one and two in
`Travis-CI documentation `__
diff --git a/DEPENDS.txt b/DEPENDS.txt
index 02ee007f..5cf37564 100644
--- a/DEPENDS.txt
+++ b/DEPENDS.txt
@@ -45,12 +45,12 @@ functionality is only available with the following installed:
* `Astropy `__ provides FITS io capability.
-*`SimpleITK `
- Optional io plugin providing a wide variety of `formats `__.
- including specialized formats using in medical imaging.
+* `SimpleITK `
+ Optional io plugin providing a wide variety of `formats `__.
+ including specialized formats using in medical imaging.
-*`imread `
- Optional io plugin providing most standard `formats `__.
+* `imread `
+ Optional io plugin providing most standard `formats `__.
Testing requirements
diff --git a/Makefile b/Makefile
index 2ace534e..270aee98 100644
--- a/Makefile
+++ b/Makefile
@@ -14,3 +14,7 @@ doctest:
coverage:
nosetests skimage --with-coverage --cover-package=skimage
+
+html:
+ pip install sphinx
+ make -C docs html
diff --git a/skimage/draw/draw.py b/skimage/draw/draw.py
index be59e268..dbeb6ba0 100644
--- a/skimage/draw/draw.py
+++ b/skimage/draw/draw.py
@@ -95,6 +95,7 @@ def circle(cy, cx, radius, shape=None):
Pixel coordinates of circle.
May be used to directly index into an array, e.g.
``img[rr, cc] = 1``.
+
Notes
-----
This function is a wrapper for skimage.draw.ellipse()
diff --git a/skimage/filters/thresholding.py b/skimage/filters/thresholding.py
index 74c5fc14..00e3763c 100644
--- a/skimage/filters/thresholding.py
+++ b/skimage/filters/thresholding.py
@@ -200,8 +200,10 @@ def threshold_isodata(image, nbins=256, return_all=False):
Histogram-based threshold, known as Ridler-Calvard method or inter-means.
Threshold values returned satisfy the following equality:
- threshold = (image[image <= threshold].mean() +
- image[image > threshold].mean()) / 2.0
+
+ ``threshold = (image[image <= threshold].mean() +``
+ ``image[image > threshold].mean()) / 2.0``
+
That is, returned thresholds are intensities that separate the image into
two groups of pixels, where the threshold intensity is midway between the
mean intensities of these groups.
diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index b0fd9240..11441800 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -220,7 +220,7 @@ def rag_mean_color(image, labels, connectivity=2, mode='distance',
labels : ndarray, shape(M, N, [..., P,])
The labelled image. This should have one dimension less than
`image`. If `image` has dimensions `(M, N, 3)` `labels` should have
- dimensions `(M, N)`.
+ dimensions `(M, N)`.
connectivity : int, optional
Pixels with a squared distance less than `connectivity` from each other
are considered adjacent. It can range from 1 to `labels.ndim`. Its
diff --git a/skimage/measure/_ccomp.pyx b/skimage/measure/_ccomp.pyx
index 56b31a9f..a3b27593 100644
--- a/skimage/measure/_ccomp.pyx
+++ b/skimage/measure/_ccomp.pyx
@@ -368,7 +368,7 @@ def label(input, neighbors=None, background=None, return_num=False,
Two pixels are connected when they are neighbors and have the same value.
In 2D, they can be neighbors either in a 1- or 2-connected sense.
The value refers to the maximum number of orthogonal hops to consider a
- pixel/voxel a neighbor.
+ pixel/voxel a neighbor::
1-connectivity 2-connectivity diagonal connection close-up
diff --git a/skimage/segmentation/boundaries.py b/skimage/segmentation/boundaries.py
index 1975d879..9400e306 100644
--- a/skimage/segmentation/boundaries.py
+++ b/skimage/segmentation/boundaries.py
@@ -65,15 +65,15 @@ def find_boundaries(label_img, connectivity=1, mode='thick', background=0):
How to mark the boundaries:
- thick: any pixel not completely surrounded by pixels of the
- same label (defined by `connectivity`) is marked as a boundary.
- This results in boundaries that are 2 pixels thick.
+ same label (defined by `connectivity`) is marked as a boundary.
+ This results in boundaries that are 2 pixels thick.
- inner: outline the pixels *just inside* of objects, leaving
- background pixels untouched.
+ background pixels untouched.
- outer: outline pixels in the background around object
- boundaries. When two objects touch, their boundary is also
- marked.
+ boundaries. When two objects touch, their boundary is also
+ marked.
- subpixel: return a doubled image, with pixels *between* the
- original pixels marked as boundary where appropriate.
+ original pixels marked as boundary where appropriate.
background: int, optional
For modes 'inner' and 'outer', a definition of a background
label is required. See `mode` for descriptions of these two.
@@ -197,7 +197,7 @@ def mark_boundaries(image, label_img, color=(1, 1, 0),
See Also
--------
- ``find_boundaries``.
+ find_boundaries
"""
marked = img_as_float(image, force_copy=True)
if marked.ndim == 2:
diff --git a/skimage/util/noise.py b/skimage/util/noise.py
index 9283f537..ff20084a 100644
--- a/skimage/util/noise.py
+++ b/skimage/util/noise.py
@@ -16,15 +16,15 @@ def random_noise(image, mode='gaussian', seed=None, clip=True, **kwargs):
mode : str
One of the following strings, selecting the type of noise to add:
- 'gaussian' Gaussian-distributed additive noise.
- 'localvar' Gaussian-distributed additive noise, with specified
- local variance at each point of `image`
- 'poisson' Poisson-distributed noise generated from the data.
- 'salt' Replaces random pixels with 1.
- 'pepper' Replaces random pixels with 0.
- 's&p' Replaces random pixels with 0 or 1.
- 'speckle' Multiplicative noise using out = image + n*image, where
- n is uniform noise with specified mean & variance.
+ - 'gaussian' Gaussian-distributed additive noise.
+ - 'localvar' Gaussian-distributed additive noise, with specified
+ local variance at each point of `image`
+ - 'poisson' Poisson-distributed noise generated from the data.
+ - 'salt' Replaces random pixels with 1.
+ - 'pepper' Replaces random pixels with 0.
+ - 's&p' Replaces random pixels with 0 or 1.
+ - 'speckle' Multiplicative noise using out = image + n*image, where
+ n is uniform noise with specified mean & variance.
seed : int
If provided, this will set the random seed before generating noise,
for valid pseudo-random comparisons.
diff --git a/tools/travis_script.sh b/tools/travis_script.sh
index f76467bb..38e2f72a 100755
--- a/tools/travis_script.sh
+++ b/tools/travis_script.sh
@@ -5,6 +5,9 @@ section "Test.with.min.requirements"
nosetests $TEST_ARGS skimage
section_end "Test.with.min.requirements"
+section "Build.docs"
+make html
+section_end "Build.docs"
section "Flake8.test"
flake8 --exit-zero --exclude=test_*,six.py skimage doc/examples viewer_examples