correldata

Dataframe-like tables of data with correlated uncertainties

These data are stored in a dictionary, whose values are numpy arrays with elements which may be strings, floats, or floats with associated uncertainties as defined in the uncertainties library.

When reading data from a csv file, column names are interpreted in the following way:

Column names are interpreted in the following way:

• In most cases, each columns is converted to a dict value, with the corresponding dict key being the column's label.
• Columns whose label starts with SE are interpreted as specifying the standard error for the latest preceding data column.
• Columns whose label starts with correl are interpreted as specifying the correlation matrix for the latest preceding data column. In that case, column labels are ignored for the rest of the columns belonging to this matrix.
• Columns whose label starts with covar are interpreted as specifying the covariance matrix for the latest preceding data column. In that case, column labels are ignored for the rest of the columns belonging to this matrix.
• SE, correl, and covar may be specified for any arbitrary variable other than the latest preceding data column, by adding an underscore followed by the variable's label (ex: SE_foo, correl_bar, covar_baz).
• correl, and covar may also be specified for any pair of variable, by adding an underscore followed by the two variable labels, joined by a second underscore (ex: correl_foo_bar, covar_X_Y). The elements of the first and second variables correspond, respectively, to the lines and columns of this matrix.

Example

import correldata

data  = '''
Sample, Tacid,  D47,   SE,         correl,,,  D48, covar,,,          correl_D47_D48
   FOO,   90., .245, .005,      1, 0.5, 0.5, .145,  4e-4, 1e-4, 1e-4, 0.5,   0,   0
   BAR,   90., .246, .005,    0.5,   1, 0.5, .146,  1e-4, 4e-4, 1e-4,   0, 0.5,   0
   BAZ,   90., .247, .005,    0.5, 0.5,   1, .147,  1e-4, 1e-4, 4e-4,   0,   0, 0.5
'''[1:-1]

cdata = correldata.read_str(data)
print(cdata)

yields:

{
  'Sample': array(['FOO', 'BAR', 'BAZ'], dtype='<U3'),
  'Tacid':  array([90., 90., 90.]),
  'D47':    uarray([0.245+/-0.005, 0.246+/-0.005, 0.247+/-0.005], dtype=object),
  'D48':    uarray([0.145+/-0.02, 0.146+/-0.02, 0.147+/-0.02], dtype=object)
}

and

print(cdata.str(correl_format = '.2f'))

yields:

Sample, Tacid,   D47, SE_D47, correl_D47,     ,     ,   D48, SE_D48, correl_D48,     ,     , correl_D47_D48,      ,      
   FOO,    90, 0.245,  0.005,       1.00, 0.50, 0.50, 0.145,   0.02,       1.00, 0.25, 0.25,           0.50, -0.00, -0.00
   BAR,    90, 0.246,  0.005,       0.50, 1.00, 0.50, 0.146,   0.02,       0.25, 1.00, 0.25,           0.00,  0.50, -0.00
   BAZ,    90, 0.247,  0.005,       0.50, 0.50, 1.00, 0.147,   0.02,       0.25, 0.25, 1.00,          -0.00,  0.00,  0.50

Documentation

https://mdaeron.github.io/correldata