Welcome to PyCRDS’s documentation!

PyCRDS

Documentation Status

PyCRDS is a library for CRDS (cavity ring-down spectroscopy) data processing.

Installation

NOTE: This library is not available on PyPI yet. Install documentation is included as a standard element. Stay tuned for PyPI availability!

pip install pycrds

Or you can clone the repository and install it locally:

pip install -e .

License

BSD 3-Clause License

Copyright (c) 2021, Marcia Marques All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

  1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

  2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

  3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

PyCRDS

Datafile

Flags

flags.insert_manual_flags(df, df_logbook)

Return the dataframe with a column flag for manual control quality. Use regex to remove duplicated characters for simultaneous events.

Parameters

  • df (pandas DataFrame) – data dataframe

  • df_logbook (pandas DataFrame) – logbook dataframe

flags.read_logbook(path)

Return a dataframe with the logbook data. Read events from the logbook file (.csv). Drop incorrect timestamp. Drop empty lines.

Logbook columns: Initial_date | Final_date | Flags

Parameters

path (str) – path of .csv logbook

Graphs

graphs.bokeh_graph(df, start_time, end_time, var)

Returns a bokeh graph of one variable for the selected period.

Parameters

  • df (pandas DataFrame) – dataframe

  • start_time (str) – ‘yyyy-mm-dd hh:mm:ss’

  • end_time (str) – ‘yyyy-mm-dd hh:mm:ss’

  • var (str) – selected variable

Indices and tables