Miscellaneous

class pyhmmer.plan7.Cutoffs

A mutable view over the score cutoffs of a HMM or a Profile.

Added in version 0.4.6.

as_vector()

Return a view over the score cutoffs as a VectorF.

gathering_available()

Check whether the gathering thresholds are available.

noise_available()

Check whether the noise cutoffs are available.

trusted_available()

Check whether the trusted cutoffs are available.

gathering

The gathering thresholds, if any.

Example

This property can be used to set the gathering cutoffs by passing it an iterable of two float:

>>> thioesterase.cutoffs.gathering = (180.0, 120.0)
>>> thioesterase.cutoffs.gathering_available()
True
>>> thioesterase.cutoffs.gathering
(180.0, 120.0)

Set the attribute to None or delete it with del to clear the gathering thresholds:

>>> thioesterase.cutoffs.gathering = None
>>> thioesterase.cutoffs.gathering_available()
False

Added in version 0.4.8.

Type:

tuple of float, or None

gathering1

The first gathering threshold, if any.

Type:

float or None

gathering2

The second gathering threshold, if any.

Type:

float or None

noise

The noise cutoffs, if available.

Added in version 0.4.8.

Type:

tuple of float, or None

noise1

The first noise cutoff, if any.

Type:

float or None

noise2

The second noise cutoff, if any.

Type:

float or None

trusted

The trusted cutoffs, if available.

Added in version 0.4.8.

Type:

tuple of float, or None

trusted1

The first trusted score cutoff, if any.

Type:

float or None

trusted2

The second trusted score cutoff, if any.

Type:

float or None

class pyhmmer.plan7.EvalueParameters

A mutable view over the e-value parameters of a HMM or a Profile.

The e-value for each filter is estimated based off a maximum likelihood distribution fitted for each profile HMM, either a Gumbel distribution for the MSV and Viterbi filters, or an exponential distribution for the Forward filter.

Added in version 0.4.6.

as_vector()

Return a view over the e-value parameters as a VectorF.

f_lambda

The \(\lambda\) parameter for the Forward filter distribution.

Type:

float or None

f_tau

The \(\tau\) parameter for the Forward filter distribution.

Type:

float or None

m_lambda

The \(\lambda\) parameter for the MSV filter distribution.

Type:

float or None

m_mu

The \(\mu\) parameter for the MSV filter distribution.

Type:

float or None

v_lambda

The \(\lambda\) parameter for the Viterbi filter distribution.

Type:

float or None

v_mu

The \(\mu\) parameter for the Viterbi filter distribution.

Type:

float or None

class pyhmmer.plan7.Offsets

A mutable view over the disk offsets of a profile.

class pyhmmer.plan7.Transitions(enum.IntEnum)

A helper enum for indices of the HMM transition probability matrix.

The Plan 7 model architecture used in HMMER describes a HMM which has 3 states and 7 transitions (hence the name) for every node of the model. The HMM can transition from a match state (\(M_n\)) to the next match stage (\(M_{n+1}\)), to an insertion state (\(I_n\)) or a deletion state (\(D_{n+1}\)). However, there are no transitions between a deletion and insertion state.

Added in version 0.8.1.

MM = 0

\(M_{i} \to M_{i+1}\).

MI = 1

\(M_{i} \to I_{i+1}\).

MD = 2

\(M_{i} \to D_{i+1}\).

IM = 3

\(I_{i} \to M_{i+1}\).

II = 4

\(I_{i} \to I_{i+1}\).

DM = 5

\(D_{i} \to M_{i+1}\).

DD = 6

\(D_{i} \to D_{i+1}\).