IsotopeModel
- class pyopenms.IsotopeModel
Bases:
objectCython implementation of _IsotopeModel
Documentation is available at http://www.openms.de/current_doxygen/html/classOpenMS_1_1IsotopeModel.html
This models a smoothed (widened) distribution, i.e. can be used to sample actual raw peaks (depending on the points you query) If you only want the distribution (no widening), use either EmpiricalFormula::getIsotopeDistribution() // for a certain sum formula or IsotopeDistribution::estimateFromPeptideWeight (double average_weight) // for averagine —– Peak widening is achieved by either a Gaussian or Lorentzian shape
- __init__()
Cython signature: void IsotopeModel()
Cython signature: void IsotopeModel(IsotopeModel &)
Methods
Cython signature: void IsotopeModel()
Cython signature: double getCenter()
Cython signature: unsigned int getCharge()
Cython signature: EmpiricalFormula getFormula() Return the Averagine peptide formula (mass calculated from mean mass and charge -- use .setParameters() to set them)
Cython signature: IsotopeDistribution getIsotopeDistribution()
Cython signature: double getOffset() Get the offset of the model
Cython signature: String getProductName() Name of the model (needed by Factory)
Cython signature: void setOffset(double offset)
Cython signature: void setSamples(EmpiricalFormula & formula) Set sample/supporting points of interpolation
- Averagines
alias of
pyopenms.pyopenms_3.__Averagines
- getCenter()
Cython signature: double getCenter()
This is a m/z-value not necessarily the monoisotopic mass
- getCharge()
Cython signature: unsigned int getCharge()
- getFormula()
Cython signature: EmpiricalFormula getFormula() Return the Averagine peptide formula (mass calculated from mean mass and charge – use .setParameters() to set them)
- getIsotopeDistribution()
Cython signature: IsotopeDistribution getIsotopeDistribution()
Useful to determine the number of isotopes that the model contains and their position
- getOffset()
Cython signature: double getOffset() Get the offset of the model
- getProductName()
Cython signature: String getProductName() Name of the model (needed by Factory)
- setOffset()
Cython signature: void setOffset(double offset)
The whole model will be shifted to the new offset without being computing all over This leaves a discrepancy which is minor in small shifts (i.e. shifting by one or two standard deviations) but can get significant otherwise. In that case use setParameters() which enforces a recomputation of the model
- setSamples()
Cython signature: void setSamples(EmpiricalFormula & formula) Set sample/supporting points of interpolation