Metadata-Version: 2.1
Name: samplitude
Version: 0.0.9
Summary: Samplitude (s8e) is a statistical distributions command line tool
Home-page: https://github.com/pgdr/samplitude
Author: PG Drange
Author-email: pgdr@equinor.com
Maintainer: PG Drange <pgdr@equinor.com>
License: GNU GPL v3 or later
Project-URL: Bug Tracker, https://github.com/pgdr/samplitude/issues
Project-URL: Documentation, https://github.com/pgdr/samplitude/blob/master/README.md
Project-URL: Source Code, https://github.com/pgdr/samplitude
Description: # samplitude
        
        CLI generation and plotting of random variables:
        
        ```bash
        $ samplitude "sin(0.31415) | sample(6) | round | cli"
        0.0
        0.309
        0.588
        0.809
        0.951
        1.0
        ```
        
        The word _samplitude_ is a portmanteau of _sample_ and _amplitude_.  This
        project also started as an étude, hence should be pronounced _sampl-étude_.
        
        `samplitude` is a chain starting with a _generator_, followed by zero or more
        _filters_, followed by a consumer.  Most generators are infinite (with the
        exception of `range` and `lists` and possibly `stdin`).  Some of the filters can
        turn infinite generators into finite generators (like `sample` and `gobble`),
        and some filters can turn finite generators into infinite generators, such as
        `choice`.
        
        _Consumers_ are filters that necessarily flush the input; `list`, `cli`,
        `tojson`, `unique`, and the plotting tools, `hist`, `scatter` and `line` are
        examples of consumers.  The `list` consumer is a Jinja2 built-in, and other
        Jinja2 consumers are `sum`, `min`, and `max`:
        
        ```bash
        samplitude "sin(0.31415) | sample(5) | round | max | cli"
        0.951
        ```
        
        For simplicity, **s8e** is an alias for samplitude.
        
        
        ##  Generators
        
        In addition to the standard `range` function, we support infinite generators
        
        * `exponential(lambd)`: `lambd` is 1.0 divided by the desired mean.
        * `uniform(a, b)`: Get a random number in the range `[a, b)` or `[a, b]`
          depending on rounding.
        * `gauss(mu, sigma)`: `mu` is the mean, and `sigma` is the standard deviation.
        * `normal(mu, sigma)`: as above
        * `lognormal(mu, sigma)`: as above
        * `triangular(low, high)`: Continuous distribution bounded by given lower and
          upper limits, and having a given mode value in-between.
        * `beta(alpha, beta)`: Conditions on the parameters are `alpha > 0` and `beta >
          0`.  Returned values range between 0 and 1.
        * `gamma(alpha, beta)`: as above
        * `weibull(alpha, beta)`: `alpha` is the scale parameter and `beta` is the shape
          parameter.
        * `pareto(alpha)`: Pareto distribution.  `alpha` is the shape parameter.
        * `vonmises(mu, kappa)`: `mu` is the mean angle, expressed in radians between 0
          and `2*pi`, and `kappa` is the concentration parameter, which must be greater
          than or equal to zero.  If kappa is equal to zero, this distribution reduces
          to a uniform random angle over the range 0 to `2*pi`.
        
        
        We have a special infinite generator (filter) that works on finite generators:
        
        * `choice`,
        
        whose behaviour is explained below.
        
        For input from files, either use `words` with a specified environment variable
        `DICTIONARY`, or pipe through
        
        * `stdin()`
        
        which reads from `stdin`.
        
        If the file is a csv file, there is a `csv` generator that reads a csv file with
        Pandas and outputs the first column (if nothing else is specified).  Specify the
        column with either an integer index or a column name:
        
        ```bash
        >>> s8e "csv('iris.csv', 'virginica') | counter | cli"
        0 50
        1 50
        2 50
        ```
        
        ## A warning about infinity
        
        All generators are (potentially) infinite generators, and must be sampled with
        `sample(n)` before consuming!
        
        ## Usage and installation
        
        Install with
        ```bash
        pip install samplitude
        ```
        or to get bleeding release,
        ```bash
        pip install git+https://github.com/pgdr/samplitude
        ```
        
        
        ### Examples
        
        This is pure Jinja2:
        ```bash
        >>> samplitude "range(5) | list"
        [0, 1, 2, 3, 4]
        ```
        
        However, to get a more UNIXy output, we use `cli` instead of `list`:
        
        ```bash
        >>> s8e "range(5) | cli"
        0
        1
        2
        3
        4
        ```
        
        To limit the output, we use `sample(n)`:
        
        
        ```bash
        >>> s8e "range(1000) | sample(5) | cli"
        0
        1
        2
        3
        4
        ```
        
        That isn't very helpful on the `range` generator, but is much more helpful on an
        infinite generator, such as the `uniform` generator:
        
        ```bash
        >>> s8e "uniform(0, 5) | sample(5) | cli"
        3.3900198868059235
        1.2002767137709318
        0.40999391897569126
        1.9394585953696264
        4.37327472704115
        ```
        
        We can round the output in case we don't need as many digits (note that `round`
        is a generator as well and can be placed on either side of `sample`):
        ```bash
        >>> s8e "uniform(0, 5) | round(2) | sample(5) | cli"
        4.58
        4.33
        1.87
        2.09
        4.8
        ```
        
        
        
        ### Selection and modifications
        
        The `samplitude` behavior is equivalent to the `head` program, or from languages
        such as Haskell. The `head` alias is supported:
        ```bash
        >>> samplitude "uniform(0, 5) | round(2) | head(5) | cli"
        4.58
        4.33
        1.87
        2.09
        4.8
        ```
        
        `drop` is also available:
        ```bash
        >>> s8e "uniform(0, 5) | round(2) | drop(2) | head(3) | cli"
        1.87
        2.09
        4.8
        ```
        
        To **shift** and **scale** distributions, we can use the `shift(s)` and
        `scale(s)` filters.  To get a Poisson point process starting at 15, we can run
        
        ```bash
        >>> s8e "poisson(0.3) | shift(15)"  # equivalent to exponential(0.3)...
        ```
        
        
        ### Choices and other operations
        
        Using `choice` with a finite generator gives an infinite generator that chooses
        from the provided generator:
        
        ```bash
        >>> samplitude "range(0, 11, 2) | choice | sample(6) | cli"
        8
        0
        8
        10
        4
        6
        ```
        
        Jinja2 supports more generic lists, e.g., lists of strings.  Hence, we can write
        
        ```bash
        >>> s8e "['win', 'draw', 'loss'] | choice | sample(6) | sort | cli"
        draw
        draw
        draw
        loss
        win
        win
        ```
        
        ... and as in Python, strings are also iterable:
        
        ```bash
        >>> s8e "'HT' | cli"
        H
        T
        ```
        ... so we can flip six coins with
        ```bash
        >>> s8e "'HT' | choice | sample(6) | cli"
        H
        T
        T
        H
        H
        H
        ```
        
        We can flip 100 coins and count the output with `counter` (which is
        `collections.Counter`)
        ```bash
        >>> s8e "'HT' | choice | sample(100) | counter | cli"
        H 47
        T 53
        ```
        
        The `sort` functionality does not work as expected on a `Counter` object (a
        `dict` type), so if we want the output sorted, we pipe through `sort` from
        _coreutils_:
        
        ```bash
        >>> s8e "range(1,7) | choice | sample(100) | counter | cli" | sort -n
        1 24
        2 17
        3 18
        4 16
        5 14
        6 11
        ```
        
        Using `stdin()` as a generator, we can pipe into `samplitude`.  Beware that
        `stdin()` flushes the input, hence `stdin` (currently) does not work with
        infinite input streams.
        
        ```bash
        >>> ls | samplitude "stdin() | choice | sample(1) | cli"
        some_file
        ```
        
        
        Then, if we ever wanted to shuffle `ls` we can run
        
        ```bash
        >>> ls | samplitude "stdin() | shuffle | cli"
        some_file
        ```
        
        ```bash
        >>> cat FILE | samplitude "stdin() | cli"
        # NOOP; cats FILE
        ```
        
        
        
        ### The fun powder plot
        
        For fun, if you have installed `matplotlib`, we support plotting, `hist` being
        the most useful.
        
        ```bash
        >>> samplitude "normal(100, 5) | sample(1000) | hist"
        ```
        
        ![normal distribution](https://raw.githubusercontent.com/pgdr/samplitude/master/assets/hist_normal.png)
        
        An exponential distribution can be plotted with `exponential(lamba)`.  Note that
        the `cli` output must be the last filter in the chain, as that is a command-line
        utility only:
        
        ```bash
        >>> s8e "normal(100, 5) | sample(1000) | hist | cli"
        ```
        
        ![exponential distribution](https://raw.githubusercontent.com/pgdr/samplitude/master/assets/hist_exponential.png)
        
        
        To **repress output after plotting**, you can use the `gobble` filter to empty
        the pipe:
        
        ```bash
        >>> s8e "normal(100, 5) | sample(1000) | hist | gobble"
        ```
        
        Although `hist` is the most useful, one could imaging running `s8e` on
        timeseries, where a `line` plot makes most sense:
        
        ```bash
        >>> s8e "sin(22/700) | sample(200) | line"
        ```
        
        ![sine and line](https://raw.githubusercontent.com/pgdr/samplitude/master/assets/line_sine.png)
        
Keywords: jinja2 jinja random statistics sample distribution plot
Platform: UNKNOWN
Description-Content-Type: text/markdown
