on 12-May-2018 (Sat)

continuous integration (CI) is the practice of merging all developer working copies to a shared mainline several times a day

Travis CI is a hosted, distributed^[2] continuous integration service used to build and test software projects hosted at GitHub

Travis CI is configured by adding a file named .travis.yml, which is a YAML format text file, to the root directory of the repository.^[5] This file specifies the programming language used, the desired building and testing environment (including dependencies which must be installed before the software can be built and tested), and various other parameters.

cookiecutters is a command-line utility that creates projects from project templates

To use ReciPy simply add the import line to the very top of your Python script:

To find out the details of a run which created a file test.npy you can recipy search test.npy

With ReciPy to view a run with GUI just run recipy gui and a browser window will open with an interface that you can use to search all of your recipy 'runs':

nbdime provides tools for diffing and merging of Jupyter Notebooks.

nbdiff compare notebooks in a terminal-friendly way

nbmerge three-way merge of notebooks with automatic conflict resolution

nbdiff-web shows you a rich rendered diff of notebooks

nbmerge-web gives you a web-based three-way merge tool for notebooks

• nbshow present a single notebook in a terminal-friendly way

nbval is a pytest plugin adds functionality to recognise and collect Jupyter notebooks. The intended purpose of nbval tests is to determine whether execution of the stored inputs match the stored outputs of the .ipynb file. Whilst also ensuring that the notebooks are running without errors.

For example, the fundamental differences between discrete and continuous spaces arise from their different topologies. In particular, all of the common spaces, such as the integers and the real numbers, have unique topologies from which many of their more-intuitive properties arise.

Although superficially similar, a topology is distinct from a σ σ \sigma -algebra. For example, the topologically open sets are not closed under the complement operation. If we combine all of the topologically open sets and topologically closed sets defined by a topology, however, then we get a proper σ σ \sigma -algebra. σ σ \sigma -algebras constructed from the topology of a space are denoted Borel σ σ \sigma -algebras (Folland 1999) . Because common spaces have natural topologies they consequently also have natural Borel σ σ \sigma -algebras that exclude pathological sets that can cause problems.

Once the philosophy has been stripped away, probability theory is simply the study of probability distributions, and the transformations of distributions between different spaces.
a probability distribution assigns real values between 0 and 1 to suitable sets of measurable spaces,

In particular, this countable additivity property allows us to cover complex neighborhoods, such as that enclosed by a smooth surface, with an infinite collection of sets and then calculate the probability allocated to that neighborhood.

A probability distribution is then completely specified by the probability triplet ( X ,  , π ) (X,X,π) (X, \mathcal{X}, \pi) which is often denoted more compactly as x ∼ π x∼π x \sim \pi where x ∈ X x∈X x \in X denotes the space, π π \pi denotes the probability distribution, and a valid σ σ \sigma -algebra is assumed.

This weighting process emphasizes how the function behaves in neighborhoods of high probability while diminishing its behavior in neighborhoods of low probability.

doubly measurable transformations

This algorithm generates a path \({\displaystyle X=(x_{1},x_{2},\ldots ,x_{T})}\), which is a sequence of states \({\displaystyle x_{n}\in S=\{s_{1},s_{2},\dots ,s_{K}\}}\) that generate the observations \({\displaystyle Y=(y_{1},y_{2},\ldots ,y_{T})}\) with \({\displaystyle y_{n}\in O=\{o_{1},o_{2},\dots ,o_{N}\}}\) (\(N\) being the count of observations (observation space, see below)).