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New format for persistence #925

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14 changes: 14 additions & 0 deletions src/Persistent_cohomology/include/gudhi/Persistent_cohomology.h
Original file line number Diff line number Diff line change
Expand Up @@ -690,6 +690,20 @@ class Persistent_cohomology {
return result;
}

/** @brief Returns persistence intervals for each dimension.
* @return A vector of diagrams, one per dimension starting from 0, where each diagram is a vector of persistence intervals (birth and death).
*/
std::vector<std::vector<std::pair<Filtration_value, Filtration_value>>>
intervals_by_dimension() {
std::vector<std::vector<std::pair<Filtration_value, Filtration_value>>> result;
result.resize(dim_max_);
for (auto && pair : persistent_pairs_) {
auto b = get<0>(pair);
result[cpx_->dimension(b)].emplace_back(cpx_->filtration(b), cpx_->filtration(get<1>(pair)));
}
return result;
}

private:
/*
* Structure representing a cocycle.
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1 change: 1 addition & 0 deletions src/python/gudhi/simplex_tree.pxd
Original file line number Diff line number Diff line change
Expand Up @@ -95,6 +95,7 @@ cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi":
vector[int] betti_numbers() nogil
vector[int] persistent_betti_numbers(double from_value, double to_value) nogil
vector[pair[double,double]] intervals_in_dimension(int dimension) nogil
vector[vector[pair[double,double]]] intervals_by_dimension() nogil
void write_output_diagram(string diagram_file_name) nogil except +
vector[pair[vector[int], vector[int]]] persistence_pairs() nogil
pair[vector[vector[int]], vector[vector[int]]] lower_star_generators() nogil
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11 changes: 9 additions & 2 deletions src/python/gudhi/simplex_tree.pyx
Original file line number Diff line number Diff line change
Expand Up @@ -612,7 +612,7 @@ cdef class SimplexTree:
"""
self.get_ptr().expansion_with_blockers_callback(max_dim, callback, <void*>blocker_func)

def persistence(self, homology_coeff_field=11, min_persistence=0, persistence_dim_max = False):
def persistence(self, homology_coeff_field=11, min_persistence=0, persistence_dim_max = False, output_type = 'old'):
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-- Not completely related to this PR, but I think we should do type annotations here, i.e.,

from typing import Optional,Literal, Union
def persistence(self, homology_coeff_field:int=11, min_persistence:float=0., persistence_dim_max:Optional[int] = None, output_type:Literal['old','array by dimension'] = 'old') -> list:
    pass

especially to have auto-completion for long arguments such as "array by dimension".
I also changed the False to a None.

"""This function computes and returns the persistence of the simplicial complex.

:param homology_coeff_field: The homology coefficient field. Must be a
Expand All @@ -627,11 +627,18 @@ cdef class SimplexTree:
maximal dimension in the complex is computed. If false, it is
ignored. Default is false.
:type persistence_dim_max: bool
:param output_type: Format of the output. 'old' for the legacy list of (dim,(birth,death)),
'array by dimension' for a list of nx2 numpy arrays (one per dimension).
:type output_type: str
:returns: The persistence of the simplicial complex.
:rtype: list of pairs(dimension, pair(birth, death))
"""
self.compute_persistence(homology_coeff_field, min_persistence, persistence_dim_max)
return self.pcohptr.get_persistence()
if output_type == 'array by dimension':
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"array by dimension" seems a bit long to me, is "arrays" ok ? and 'old' isn't very telling : "tuples" ?
Also, should we raise a DeprecationWarning to change the default to the array one afterward ?

v = self.pcohptr.intervals_by_dimension()
return [ np.asarray(dgm) for dgm in v ] # std::move(dgm)?
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We should probably do the usual workaround for empty dgm to get a shape (0,2).

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Tuples are slightly faster than lists in python, but that's negligible here.

else:
return self.pcohptr.get_persistence()

def compute_persistence(self, homology_coeff_field=11, min_persistence=0, persistence_dim_max = False):
"""This function computes the persistence of the simplicial complex, so it can be accessed through
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