issparse

gistfile1.txt

ArrayFire/generate/generate.jl:                     "is_sparse" => "issparse", "sparse_to_dense" => "full",
ArrayFire/src/array.jl:import Base: Array, SparseMatrixCSC, copy, deepcopy_internal, issparse, sparse, full, complex, conj
ArrayFire/src/util.jl:    @assert issparse(a) "AFArray is not sparse"
ArrayFire/src/util.jl:    if issparse(a)
ArrayFire/src/util.jl:toa(a) = issparse(a) ?  SparseMatrixCSC(a) : Array(a)
ArrayFire/src/wrap.jl:export is_row, is_scalar, is_single, is_vector, is_window_closed, isinf, isnan, issparse, iszero, le, lgamma
ArrayFire/src/wrap.jl:function issparse(arr::AFArray)
ArrayFire/test/sparse.jl:@test !issparse(A)
ArrayFire/test/sparse.jl:@test issparse(a1)
ArrayFire/test/sparse.jl:@test issparse(Aid)
ArrayFire/test/sparse.jl:@test !issparse(Ie2)
AxisAlgorithms/test/matmul.jl:        if !issparse(M)
BasisMatrices/src/basis.jl:_all_sparse(b::Basis{N,TP}) where {N,TP} = all(issparse, TP.parameters)
BasisMatrices/src/BasisMatrices.jl:Base.issparse(::Type{T}) where {T<:BasisParams} = false
BasisMatrices/src/BasisMatrices.jl:for f in [:family, :family_name, :(Base.issparse), :(Base.eltype)]
BasisMatrices/src/lin.jl:Base.issparse(::Type{T}) where {T<:LinParams} = true
BasisMatrices/src/spline.jl:Base.issparse(::Type{T}) where {T<:SplineParams} = true
BasisMatrices/src/util.jl:Base.issparse(rk::RowKron) = map(issparse, rk.B)
BasisMatrices/test/cheb.jl:    @test !issparse(ChebParams)
BasisMatrices/test/cheb.jl:    @test !issparse(params)
BasisMatrices/test/lin.jl:    @test issparse(bas1.params[1])
BasisMatrices/test/lin.jl:    @test issparse(LinParams)
BasisMatrices/test/spline.jl:    @test issparse(params)
BasisMatrices/test/spline.jl:    @test issparse(SplineParams)
BayesianNonparametrics/src/dpmm.jl:	if issparse(X)
Binary file Knet/ChangeLog matches
Boltzmann/src/rbm.jl:    if issparse(vis)
CoinOptServices/src/CoinOptServices.jl:    if issparse(A)
CSDP/src/blockmat.h.jl:    issparse::csdpshort
CSDP/src/blockmat.h.jl:    issparse = numentries <= blocksize / 4 || numentries <= 15 # FIXME also if category (which is in C...) is DIAG
CSDP/src/blockmat.jl:                        1)         # issparse
CSDP/src/debug-mat.jl:    println(io, " issparse      :  ",  b.issparse     )
CSDP/src/declarations.jl:                jblock.csdp.issparse = 0
CSDP/src/declarations.jl:                jblock.csdp.issparse = 1
CSDP/src/declarations.jl:                jblock.csdp.issparse = 1
CVXOPT/src/CVXOPT.jl:  if issparse(A)
Erdos/src/distances/distance.jl:#     issparse(distmx)? (nnz(distmx) > 0) : !isempty(distmx)
Knet/deprecated/src7/data/ItemTensor.jl:# itembatch(x,n)=(issparse(x)?SparseArrayCPU:DynamicArrayCPU)(eltype(x),csize(x,n))
Knet/deprecated/src7/data/ItemTensor.jl:itembatch(x,n)=(issparse(x) ? spzeros(eltype(x),csize(x,n)...) : Array(eltype(x),csize(x,n)))
Knet/deprecated/src7/deprecated/mlp.jl:xbatch(x,b)=(issparse(x) ?
Knet/deprecated/src7/deprecated/netinit.jl:# #         if !dense && issparse(x)
Knet/deprecated/src7/deprecated/netinit.jl:#         issparse(r.dif[i]) == nsparse || continue
Knet/deprecated/src7/deprecated/netinit.jl:            issparse(r.out0[r.inputs[i][2]]))
Knet/deprecated/src7/deprecated/netinit.jl:            issparse(r.tmp[i]) == nsparse)
Knet/deprecated/src7/deprecated/netinit.jl:    n == length(r.op) && return issparse(dy)
Knet/deprecated/src7/deprecated/util.jl:#     #         if issparse(x)      # todo: is this the right thing for all ops?
Knet/deprecated/src7/deprecated/util.jl:issimilar3(i,o)=(eltype(i) == eltype(o) && size(i) == size(o) && issparse(i) == issparse(o))
Knet/deprecated/src7/net/initback.jl:#         @assert (issimilar2(f.dif0[n], f.out0[n]) ) #todo: && issparse(f.dif0[n])==(f.sparse[n]!=nothing)
Knet/deprecated/src7/net/initback.jl:#             @assert (issimilar2(f.tmp[n], f.out0[n]) && issparse(f.tmp[n])==(f.sparse[n]!=nothing))
Knet/deprecated/src7/net/initback.jl:        elseif issparse(a.out0) && getp(b,:grad) # rw = r * w  with sparse r in nce
Knet/deprecated/src7/net/initback.jl:        elseif issparse(b.out0) && getp(a,:grad) # y = w * x  with sparse x in rnnlm
Knet/deprecated/src7/net/initback.jl:#             elseif issparse(f.out0[i])
Knet/deprecated/src7/net/initback.jl:#             elseif issparse(f.out0[j])
Knet/deprecated/src7/net/initback.jl:# #         if !dense && issparse(x)
Knet/deprecated/src7/net/initback.jl:# if isa(f.op[i], Input) && issparse(f.out0[i])
Knet/deprecated/src7/net/initback.jl:        if issparse(a.out0) && issparse(b.out0)
Knet/deprecated/src7/net/initback.jl:#             if issparse(f.out0[i]) && issparse(f.out0[j])
Knet/deprecated/src7/net/initback.jl:#         issparse(f.dif[i]) == nsparse || continue
Knet/deprecated/src7/net/initforw.jl:        if isa(p.op,Input) && issparse(inputs[lastinput+=1])
Knet/deprecated/src7/op/deprecated/mmul.jl:        if x != nothing && issparse(x)
Knet/deprecated/src7/util/cudart.jl:import Base: isequal, convert, reshape, resize!, copy!, isempty, fill!, pointer, issparse, deepcopy_internal
Knet/deprecated/src7/util/cudart.jl:issparse(::CudaArray)=false
Knet/deprecated/src7/util/cusparse.jl:Base.issparse(a::CudaSparseMatrix) = true
Knet/deprecated/src7/util/cusparse.jl:Base.issparse(x::CudaSparseMatrixCSCU)=true
Knet/deprecated/src7/util/cusparse.jl:Base.issparse(x::CudaSparseMatrixCSRU)=true
Knet/deprecated/src7/util/deprecated/dense.jl:import Base: isequal, similar, convert, copy, copy!, resize!, issparse
Knet/deprecated/src7/util/deprecated/dense.jl:issparse(a::KUdense)=false
Knet/deprecated/src7/util/deprecated/sparse.jl:import Base: isequal, convert, similar, copy, copy!, eltype, length, ndims, size, isempty, issparse, stride, strides, full
Knet/deprecated/src7/util/deprecated/sparse.jl:issparse(::KUsparse)=true
Knet/deprecated/src7/util/deprecated/sparse.jl:#         issparse(::$S)=true
Knet/examples/deprecated/ncelm.jl:    if issparse(d.x)
Knet/examples/deprecated/rnnlm.jl:    if issparse(d.x)
Knet/test/deprecated/testcolops.jl:        a = issparse(b) ? convert(KUsparse{A}, copy(a0)) : convert(KUdense{A}, copy(a0))
Knet/test/deprecated/testcolops.jl:        if !issparse(b)
LinearOperators/src/LinearOperators.jl:  if issparse(M)
MFCC/src/rasta.jl:    ## if issparse(c) && ispsparse(r)
ModelReduction/src/craig_bampton.jl:    if issparse(K) && issparse(M)
MultivariateStats/src/kpca.jl:    evl, evc = if solver == :eigs || issparse(K)
PlotRecipes/src/graphs.jl:    nosparse = !issparse(mat) # doesn't plot zeros from a sparse matrix
ProximalOperators/src/functions/indGraph.jl:  if issparse(A)
ProximalOperators/test/test_graph.jl:    B = ifelse(issparse(A), [A -speye(m)],  [A -eye(m)])
QuantEcon/test/test_ddp.jl:    @test issparse(ddp0_sa.Q)
RobustLeastSquares/src/RobustLeastSquares.jl:    if issparse(A)
SALSA/src/algorithms/adaptive_l1rda_alg.jl:    check = ~issparse(X)
SALSA/src/algorithms/dropout_alg.jl:    check = issparse(X)
SALSA/src/algorithms/l1rda_alg.jl:    check = ~issparse(X)
SALSA/src/algorithms/pegasos_alg.jl:    check = issparse(X)
SALSA/src/algorithms/reweighted_l1rda_alg.jl:    check = ~issparse(X)
SALSA/src/algorithms/reweighted_l2rda_alg.jl:    check = ~issparse(X)
SALSA/src/algorithms/sgd_alg.jl:    check = issparse(X)
SALSA/src/algorithms/stochastic_rk_means.jl:    check = issparse(X)
SALSA/src/SALSA.jl:import Base: size, getindex, issparse, sub, dot, show, isempty, At_mul_B!, readline
SALSA/src/support/data_wrapper.jl:issparse(f::DelimitedFile) = false
ScikitLearn/src/cross_validation.jl:##     if sp.issparse(v):
ScikitLearn/src/cross_validation.jl:    is_sparse = issparse(X)
ScikitLearn/src/dataframes.jl:Base.issparse(::DataFrame) = false
ScikitLearn/src/dataframes.jl:    ## if any(sparse.issparse(fea) for fea in extracted):
ScikitLearn/src/pipeline.jl:    if any(issparse, Xs)
ScikitLearn/src/pipeline.jl:    ##     if any(sparse.issparse(f) for f in Xs):
ScikitLearn/src/sk_utils.jl:    if issparse(y)
SCIP/src/mpb_interface.jl:    if issparse(A)
TimeModels/src/kalman_filter.jl:    Ksparse = issparse(model.A(1)) && issparse(model.V(1)) && issparse(model.C(1))
TimeModels/src/kalman_smooth.jl:    Ksparse = issparse(model.A(1)) && issparse(model.V(1)) && issparse(model.C(1))
VectorizedRoutines/src/matlab.jl:  function accumarray2(subs, val, fun=sum, fillval=0; sz=maximum(subs,1), issparse=false)
VectorizedRoutines/src/matlab.jl:     issparse ? sparse(A) : A