Metadata-Version: 2.1
Name: metrolopy
Version: 0.6.0
Summary: tools for dealing with measured quantities: uncertainty propagation and unit conversion
Home-page: http://nrc-cnrc.github.io/MetroloPy/
Author: Harold Parks, National Research Council Canada
Author-email: parksh@nrc.ca
License: UNKNOWN
Description: # MetroloPy
        
        tools for dealing with physical quantities:  uncertainty propagation and unit conversion
        
        ---
        
        MetroloPy is a pure python package and requires Python 3.5 or later and the SciPy stack (NumPy, SciPy and Pandas).  It looks best in a Jupyter Notebook.
        
        Install MetroloPy with `pip install metrolopy`  or 
        `conda install -c conda-forge metrolopy`.
        
        Physical quantities can then be represented in Python as `gummy` objects with an uncertainty and (or) a unit:
        
        <pre><code>&gt;&gt;&gt; import metrolopy as uc
        &gt;&gt;&gt; a = uc.gummy(1.2345,u=0.0234,unit='cm')
        &gt;&gt;&gt; a
        1.234(23) cm
        
        &gt;&gt;&gt; b = uc.gummy(3.034,u=0.174,unit='mm')
        &gt;&gt;&gt; f = uc.gummy(uc.UniformDist(center=0.9345,half_width=0.096),unit='N')
        &gt;&gt;&gt; p = f/(a*b)
        &gt;&gt;&gt; p
        2.50(21) N/cm<sup>2</sup>
        
        &gt;&gt;&gt; p.unit = 'kPa'
        &gt;&gt;&gt; p.uunit = '%'
        &gt;&gt;&gt; p
        25.0 kPa &plusmn; 8.5%
        </code></pre>
        
        MetroloPy can do much more including Monte-Carlo uncertainty propagation, generating uncertainty budget tables, and curve fitting.  It can also handle expanded uncertainties, degrees of freedom, correlated quantities, and complex valued quantities. See:
        
        * [a tutorial](https://nrc-cnrc.github.io/MetroloPy/_build/html/_static/tutorial.html) (or  <a href="https://nrc-cnrc.github.io/MetroloPy/_build/html/_downloads/tutorial.ipynb" download> download the tutorial as Jupyter notebook</a>)
        * [the documentation](https://nrc-cnrc.github.io/MetroloPy/)
        * [the issues page on GitHub](https://github.com/nrc-cnrc/Metrolopy/issues)
        * [a list of the units built into MetroloPy](https://nrc-cnrc.github.io/MetroloPy/_static/units.html)
        * [a list of the physical constants built into MetroloPy](https://nrc-cnrc.github.io/MetroloPy/_static/constants.html)
        
        ## new in version 0.6.0
        
        * A constant library has been added with physical constants that can be accessed
          by name or alias with the `constant` function.  The `search_constants` function 
          with no argument gives a listing of all built-in constants.  Each constant 
          definition includes any correlations with other constants.
        
        * The `Quantity` class has been added to represent a general numerical value
          multiplied by a unit and the `unit` function has been added to retrieve
          `Unit` instances from the unit library by name or alias.  `Unit` instances 
          can now be multiplied and divided by other `Unit` instances to produce
          composite units, can be multiplied and divided by numbers to produce 
          `Quantity` instances or multiply or divide `Quantity` instances.  The 
          `gummy` class is now a subclass of `Quantity` with a `nummy` value rather 
          than a subclass of `nummy`.  A `QuantityArray` class has been introduced
          to represent an array of values all with the same unit.  Multiplying a `Unit`
          instance by a list, tuple, or numpy array produces a `QuantityArray` instance.
        
        * The `immy` class has been introduced as an `ummy` valued counterpart of the 
          `jummy` class for representing complex values with uncertainties.  `immy` 
          and `jummy` values can now be displayed in a polar representation in addition 
          to a cartesian representation.  `immy` and `jummy` .r and .phi properties 
          have been added to access the magnitude and argument of the values as a 
          complement to the .real and .imag properties.
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Framework :: Jupyter
Classifier: Framework :: IPython
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Provides-Extra: pretty
