Main module

burnman.main.velocities_from_rock(rock, pressures, temperatures, averaging_scheme=<burnman.averaging_schemes.VoigtReussHill object>)[source]

This function is deprecated. Use burnman.material.Material.evaluate() instead.

A function that rolls several steps into one: given a rock and a list of pressures and temperatures, it calculates the elastic moduli of the individual phases using calculate_moduli(), averages them using average_moduli(), and calculates the seismic velocities using compute_velocities().

Parameters:

rock : burnman.Material

this is the rock for which you are calculating velocities

pressures: list of float

list of pressures you want to evaluate the rock at. \([Pa]\)

temperatures: list of float

list of temperatures you want to evaluate the rock at. \([K]\)

averaging_scheme: :class:`burnman.averaging_schemes.AveragingScheme`

Averaging scheme to use.

Returns:

rho, V_p, V_s, V_phi, K, G : lists of floats

Lists of density [kg/m^3], P-wave velocity [m/s], shear-wave velocity [m/s], bulk sound velocity [m/s], bulk modulus [Pa], and shear modulus [Pa] for each P,T point.

burnman.main.compare_l2(depth, calc, obs)[source]

PUT IN TOOLS Computes the L2 norm for N profiles at a time (assumed to be linear between points).

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Parameters:
  • depths (array of float) – depths. \([m]\)
  • calc (list of arrays of float) – N arrays calculated values, e.g. [mat_vs,mat_vphi]
  • obs (list of arrays of float) – N arrays of values (observed or calculated) to compare to , e.g. [seis_vs, seis_vphi]
Returns:

array of L2 norms of length N

Return type:

array of floats

burnman.main.compare_chifactor(calc, obs)[source]

PUT IN TOOLS Computes the chi factor for N profiles at a time. Assumes a 1% a priori uncertainty on the seismic model.

Parameters:
  • calc (list of arrays of float) – N arrays calculated values, e.g. [mat_vs,mat_vphi]
  • obs (list of arrays of float) – N arrays of values (observed or calculated) to compare to , e.g. [seis_vs, seis_vphi]
Returns:

error array of length N

Return type:

array of floats

burnman.main.l2(x, funca, funcb)[source]

PUT IN TOOLS Computes the L2 norm for one profile(assumed to be linear between points).

Parameters:
  • x (array of float) – depths \([m]\).
  • funca (list of arrays of float) – array calculated values
  • funcb (list of arrays of float) – array of values (observed or calculated) to compare to
Returns:

L2 norm

Return type:

array of floats

burnman.main.nrmse(x, funca, funcb)[source]

PUT IN TOOLS Normalized root mean square error for one profile :type x: array of float :param x: depths in m. :type funca: list of arrays of float :param funca: array calculated values :type funcb: list of arrays of float :param funcb: array of values (observed or calculated) to compare to

Returns:RMS error
Return type:array of floats
burnman.main.chi_factor(calc, obs)[source]

PUT IN TOOLS \(\chi\) factor for one profile assuming 1% uncertainty on the reference model (obs) :type calc: list of arrays of float :param calc: array calculated values :type obs: list of arrays of float :param obs: array of reference values to compare to

Returns:\(\chi\) factor
Return type:array of floats