#!/usr/bin/env python
"""Collection of functions for the manipulation of time series."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import mando
from mando.rst_text_formatter import RSTHelpFormatter

import pandas as pd

from .. import tsutils


@mando.command('rank', formatter_class=RSTHelpFormatter, doctype='numpy')
@tsutils.doc(tsutils.docstrings)
def rank_cli(input_ts='-',
             columns=None,
             start_date=None,
             end_date=None,
             dropna='no',
             skiprows=None,
             index_type='datetime',
             names=None,
             clean=False,
             axis=0,
             method='average',
             numeric_only=None,
             na_option='keep',
             ascending=True,
             pct=False,
             print_input=False,
             float_format='%g',
             source_units=None,
             target_units=None,
             round_index=None):
    """Compute numerical data ranks (1 through n) along axis.

    Equal values are assigned a rank that is the average of the ranks of those
    values

    Parameters
    ----------
    axis
        [optional, default is 0]

        0 or 'index' for rows. 1 or 'columns' for columns.  Index to direct
        ranking.
    method : str
        [optional, default is 'average']

        +-----------------+--------------------------------+
        | method argument | Description                    |
        +=================+================================+
        | average         | average rank of group          |
        +-----------------+--------------------------------+
        | min             | lowest rank in group           |
        +-----------------+--------------------------------+
        | max             | highest rank in group          |
        +-----------------+--------------------------------+
        | first           | ranks assigned in order they   |
        |                 | appear in the array            |
        +-----------------+--------------------------------+
        | dense           | like 'min', but rank always    |
        |                 | increases by 1 between groups  |
        +-----------------+--------------------------------+

    numeric_only
        [optional, default is None]

        Include only float, int, boolean data. Valid only for DataFrame or
        Panel objects.
    na_option : str
        [optional, default is 'keep']

        +--------------------+--------------------------------+
        | na_option argument | Description                    |
        +====================+================================+
        | keep               | leave NA values where they are |
        +--------------------+--------------------------------+
        | top                | smallest rank if ascending     |
        +--------------------+--------------------------------+
        | bottom             | smallest rank if descending    |
        +--------------------+--------------------------------+

    ascending
        [optional, default is True]

        False ranks by high (1) to low (N)
    pct
        [optional, default is False]

        Computes percentage rank of data.
    {input_ts}
    {columns}
    {start_date}
    {end_date}
    {dropna}
    {skiprows}
    {index_type}
    {names}
    {clean}
    {print_input}
    {float_format}
    {source_units}
    {target_units}
    {round_index}

    """
    tsutils._printiso(rank(input_ts=input_ts,
                           columns=columns,
                           start_date=start_date,
                           end_date=end_date,
                           dropna=dropna,
                           skiprows=skiprows,
                           index_type=index_type,
                           names=names,
                           clean=clean,
                           axis=axis,
                           method=method,
                           numeric_only=numeric_only,
                           na_option=na_option,
                           ascending=ascending,
                           pct=pct,
                           print_input=print_input,
                           float_format=float_format,
                           source_units=source_units,
                           target_units=target_units,
                           round_index=round_index))


def rank(input_ts='-',
         columns=None,
         start_date=None,
         end_date=None,
         dropna='no',
         skiprows=None,
         index_type='datetime',
         names=None,
         clean=False,
         axis=0,
         method='average',
         numeric_only=None,
         na_option='keep',
         ascending=True,
         pct=False,
         print_input=False,
         float_format='%g',
         source_units=None,
         target_units=None,
         round_index=None):
    """Compute numerical data ranks (1 through n) along axis."""
    tsd = tsutils.common_kwds(tsutils.read_iso_ts(input_ts,
                                                  skiprows=skiprows,
                                                  names=names,
                                                  index_type=index_type),
                              start_date=start_date,
                              end_date=end_date,
                              pick=columns,
                              round_index=round_index,
                              dropna=dropna,
                              source_units=source_units,
                              target_units=target_units,
                              clean=clean)

    # Trying to save some memory
    if print_input:
        otsd = tsd.copy()
    else:
        otsd = pd.DataFrame()

    return tsutils.return_input(print_input,
                                otsd,
                                tsd.rank(axis=axis,
                                         method=method,
                                         numeric_only=numeric_only,
                                         na_option=na_option,
                                         ascending=ascending,
                                         pct=pct),
                                'rank',
                                float_format=float_format)
