microcalorimetry.export
=======================

.. py:module:: microcalorimetry.export

.. autoapi-nested-parse::

   
   This module contains functions for exporting HDF5 datasets into different formats that
   aren't the preffered format for the microcaloriemetry program.
















   ..
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Functions
---------

.. autoapisummary::

   microcalorimetry.export.as_doteff
   microcalorimetry.export.as_dotdut_s11


Package Contents
----------------

.. py:function:: as_doteff(output_path: microcalorimetry._tkquick.gui_dtypes.SaveAsPath, eta: microcalorimetry.configs.EtaLike, s11: microcalorimetry.configs.S11Like, sensor_name: str = None, connect_number: int = None, expansion_factor: float = 2, frequency_decimals: int = 2, eta_decimals: int = 4, s11_abs_decimals: int = 4, s11_angle_decimals: int = 2, columns: int = 7)

   
   Generate a .eff file from an effective efficiency measurement.

   These files contain an effective efficiency measurement, as well
   as a reflection coefficient and an expression of uncertainty. Type A and
   Type B uncertainties will be inferred from the objects covariance
   metadata.

   Exporting as a .eff file will lose
   covariance information about the measurement.

   :param output_path: File path to save to.
   :type output_path: SaveAsPath
   :param eta: Effective efficiency of the sensor.
   :type eta: configs.EtaLike
   :param s11: S11 data of the sensor.
   :type s11: configs.S11Like
   :param sensor_name: Name of the sensor. If not provided, won't be included
                       in the output file.
   :type sensor_name: str
   :param connect_number: Connect number of the sensor. If not provided, won't be included
                          in the comment line.
   :type connect_number: int
   :param expansion_factor: Expansion factor of the total uncertainty. If >= 1, will use that
                            as the expansion factor. If < 1, then will calculate the confidence
                            interval of the provided fraction (e.g 0.95 will calculate the
                            95% confidence interval) using metadata of the uncertainty mechanisms.
   :type expansion_factor: int, optional
   :param frequency_decimals: Decimals for reporting frequency, by default 2
   :type frequency_decimals: int, optional
   :param eta_decimals: Decimals for reporting the eta parameters, by default 4.
   :type eta_decimals: int, optional
   :param s11_abs_decimals: Decimals for reporting the S11 absolute value, by default 4.
   :type s11_abs_decimals: int, optional
   :param s11_angle_decimals: Decimals for reporting the S11 angle vakule, by default 2.
   :type s11_angle_decimals: int, optional
   :param columns: Number of columns in the eff file. By default 7.
   :type columns: int, optional















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.. py:function:: as_dotdut_s11(s11: microcalorimetry.configs.S11Like, path: microcalorimetry._tkquick.gui_dtypes.SaveAsPath, device: str, expansion_factor: float = 2.0)

   
   Export a device to a .dut file for 1 port s-parameters.

   This is a cal services

   :param s11: Path to output file.
   :type s11: configs.S11Like
   :param path: RMEMeas measurement s1p_c data.
   :type path: SaveAsPath
   :param device: Name of device.
   :type device: str
   :param expansion_factor: If >1 will use the provided expansion factor.
                            If < 1, will calculate the confidence interval
                            (i,e 0.95 will calculate the 95% confidence interval.
   :type expansion_factor: float, optional

   :returns: Path to exported DUT file.
   :rtype: Path















   ..
       !! processed by numpydoc !!