imports + strict & fixing Docs (#5)

* absolute imports
* rise Sphinx warnings
* fixing docs & config
* docs: fix links & API folder
* move figures
* pandas: fix as_matrix
* update CI
* pep8

Author: Borda

.pep8speaks.yml

@@ -0,0 +1,28 @@
+# File : .pep8speaks.yml
+
+scanner:
+    diff_only: True  # If False, the entire file touched by the Pull Request is scanned for errors. If True, only the diff is scanned.
+    linter: pycodestyle  # Other option is flake8
+
+pycodestyle:  # Same as scanner.linter value. Other option is flake8
+    max-line-length: 110  # Default is 79 in PEP 8
+    ignore:  # Errors and warnings to ignore
+        - W504  # line break after binary operator
+        - E402  # module level import not at top of file
+        - E731  # do not assign a lambda expression, use a def
+        - C406  # Unnecessary list literal - rewrite as a dict literal.
+        - E741  # ambiguous variable name
+
+no_blank_comment: True  # If True, no comment is made on PR without any errors.
+descending_issues_order: False  # If True, PEP 8 issues in message will be displayed in descending order of line numbers in the file
+
+message:  # Customize the comment made by the bot,
+    opened:  # Messages when a new PR is submitted
+        header: "Hello @{name}! Thanks for opening this PR. "
+                # The keyword {name} is converted into the author's username
+        footer: "Do see the [Hitchhiker's guide to code style](https://goo.gl/hqbW4r)"
+                # The messages can be written as they would over GitHub
+    updated:  # Messages when new commits are added to the PR
+        header: "Hello @{name}! Thanks for updating this PR. "
+        footer: ""  # Why to comment the link to the style guide everytime? :)
+    no_errors: "There are currently no PEP 8 issues detected in this Pull Request. Cheers! :beers: "

.travis.yml

@@ -18,9 +18,9 @@ sudo: false
 python:
   - 2.7
   # - 3.4  # will be deprecated for pandas
-  - 3.5
   - 3.6
   - 3.7
+  - 3.8
 
 # See http://docs.travis-ci.com/user/caching/#pip-cache
 cache: pip

MANIFEST.in

@@ -32,6 +32,8 @@ recursive-include figures *.png
 # Include the sample data
 recursive-include data_images *.yml *.yaml
 
+recursive-include assets *.png
+
 prune .git
 prune venv
 prune build

README.md

@@ -14,7 +14,7 @@
 
 We present a final step of image processing pipeline which accepts a large number of images, containing spatial expression information for thousands of genes in Drosophila imaginal discs. We assume that the gene activations are binary and can be expressed as a union of a small set of non-overlapping spatial patterns, yielding a compact representation of the spatial activation of each gene. This lends itself well to further automatic analysis, with the hope of discovering new biological relationships. Traditionally, the images were labelled manually, which was very time-consuming. The key part of our work is a binary pattern dictionary learning algorithm, that takes a set of binary images and determines a set of patterns, which can be used to represent the input images with a small error.
 
-![schema](figures/pipeline_schema.png)
+![schema](assets/pipeline_schema.png)
 
 For the image segmentation and individual object detection, we used [Image segmentation toolbox](https://borda.github.io/pyImSegm/).
 
@@ -86,13 +86,13 @@ python experiments/run_dataset_generate.py \
 ```
 
 **Sample atlases**
-![atlases](figures/synth_atlases.png)
+![atlases](assets/synth_atlases.png)
 
 **Sample binary images**
-![binary samples](figures/synth_samples_binary.png)
+![binary samples](assets/synth_samples_binary.png)
 
 **Sample fuzzy images**
-![fuzzy samples](figures/synth_samples_fuzzy.png)
+![fuzzy samples](assets/synth_samples_fuzzy.png)
 
 For adding Gaussian noise with given sigmas use following script:
 ```bash
@@ -101,7 +101,7 @@ python experiments/run_dataset_add_noise.py \
     -d apdDataset_vX --sigma 0.01 0.1 0.2
 ```
 
-![gauss noise](figures/synth_gauss-noise.png)
+![gauss noise](assets/synth_gauss-noise.png)
 
 ### Real images
 
@@ -226,7 +226,7 @@ python experiments/run_reconstruction.py \
     --nb_workers 1 --visual
 ```
 
-![reconstruction](figures/reconst_imag-disc.png)
+![reconstruction](assets/reconst_imag-disc.png)
 
 ### Aggregating results