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Revert invokelatest hack for FileIO
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@jtackm
jtackm committed Jul 26, 2018
1 parent d812c04 commit dbbe189
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Showing 5 changed files with 64 additions and 32 deletions.
14 changes: 7 additions & 7 deletions src/FlashWeave.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ using LightGraphs, SimpleWeightedGraphs
using StatsBase, Distributions, Combinatorics

# io
using JSON, HDF5
using JSON, HDF5, FileIO

# utilities
import Base.show
Expand All @@ -37,11 +37,11 @@ export learn_network,
show,
graph

function __init__()
warn_items = [(:FileIO, "JLD/JLD2")]
for (mod_symbol, format) in warn_items
isdefined(mod_symbol) && warn("Package $mod_symbol was loaded before importing FlashWeave. $format will not be available for FlashWeave's IO functions.")
end
end
# function __init__()
# warn_items = [(:FileIO, "JLD/JLD2")]
# for (mod_symbol, format) in warn_items
# isdefined(mod_symbol) && warn("Package $mod_symbol was loaded before importing FlashWeave. $format will not be available for FlashWeave's IO functions.")
# end
# end

end
31 changes: 18 additions & 13 deletions src/io.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -62,8 +62,9 @@ function save_network(net_path::AbstractString, net_result::FWResult; detailed::
if isedgelist(file_ext)
write_edgelist(net_path, graph(net_result))
elseif isjld(file_ext)
isdefined(:FileIO) || @eval using FileIO: save, load
Base.invokelatest(save, net_path, "results", net_result)
# isdefined(:FileIO) || @eval using FileIO: save, load
# Base.invokelatest(save, net_path, "results", net_result)
save(net_path, "results", net_result)
else
error("$(file_ext) not a valid output format. Choose one of $(valid_net_formats)")
end
Expand All @@ -88,10 +89,13 @@ function load_network(net_path::AbstractString)
if isedgelist(file_ext)
G = read_edgelist(net_path)
net_result = FWResult(G)

elseif isjld(file_ext)
isdefined(:FileIO) || @eval using FileIO: save, load
d = Base.invokelatest(load, net_path)
net_result = d["results"]
# isdefined(:FileIO) || @eval using FileIO: save, load
# d = Base.invokelatest(load, net_path)
# net_result = d["results"]
net_result = load(net_path, "results")

else
error("$(file_ext) not a valid network format. Valid formats are $(valid_net_formats)")
end
Expand All @@ -102,16 +106,17 @@ end
## Helper functions ##
######################

function load_jld(data_path::AbstractString, data_key::AbstractString, header_key::AbstractString,
meta_key=nothing, meta_header_key=nothing; transposed::Bool=false)
isdefined(:FileIO) || @eval using FileIO: save, load
d = Base.invokelatest(load, data_path)
function load_jld(data_path::AbstractString, otu_data_key::AbstractString, otu_header_key::AbstractString,
meta_data_key=nothing, meta_header_key=nothing; transposed::Bool=false)
# isdefined(:FileIO) || @eval using FileIO: save, load
# d = Base.invokelatest(load, data_path)
d = load(data_path)

data = d[data_key]
header = d[header_key]
data = d[otu_data_key]
header = d[otu_header_key]

if meta_key != nothing
meta_data = d[meta_key]
if meta_data_key != nothing
meta_data = d[meta_data_key]
meta_header = d[meta_header_key]
else
meta_data = meta_header = nothing
Expand Down
22 changes: 13 additions & 9 deletions src/learning.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -345,14 +345,14 @@ meta data table as an input (instead of a data matrix).
"""
function learn_network(data_path::AbstractString, meta_data_path=nothing; otu_data_key::AbstractString="data",
otu_header_key::AbstractString="header", meta_data_key::AbstractString="meta_data",
function learn_network(data_path::AbstractString, meta_data_path=nothing; otu_data_key::AbstractString="otu_data",
otu_header_key::AbstractString="otu_header", meta_data_key::AbstractString="meta_data",
meta_header_key::AbstractString="meta_header", verbose::Bool=true,
transposed::Bool=false, kwargs...)

verbose && println("\n### Loading data ###\n")
data, header, meta_data, meta_header = load_data(data_path, meta_data_path, otu_data_key=otu_data_key,
otu_header_key=otu_header_key, meta_key=meta_data_key,
otu_header_key=otu_header_key, meta_data_key=meta_data_key,
meta_header_key=meta_header_key, transposed=transposed)


Expand All @@ -362,8 +362,8 @@ function learn_network(data_path::AbstractString, meta_data_path=nothing; otu_d
else
check_data(data, meta_data, header=header, meta_header=meta_header)
data = hcat(data, meta_data)
header = hcat(header, meta_header)
meta_mask = hcat(falses(length(header)), trues(length(meta_header)))
meta_mask = vcat(falses(length(header)), trues(length(meta_header)))
header = vcat(header, meta_header)
end

learn_network(data; header=header, meta_mask=meta_mask, verbose=verbose, kwargs...)
Expand Down Expand Up @@ -444,17 +444,21 @@ function learn_network(data::AbstractArray{ElType}; sensitive::Bool=true,
data = data'
end

if header == nothing
header = ["X" * string(i) for i in 1:size(data, 2)]
end

if meta_mask == nothing
meta_mask = falses(length(header))
end

check_data(data, header, meta_mask=meta_mask)

if !issparse(data) && make_sparse
verbose && println("\n### Converting data to sparse matrix ###\n")
data = sparse(data)
end

if header != nothing && meta_mask == nothing
meta_mask = falses(length(header))
end

n_mvs = sum(meta_mask)
if verbose
println("""Inferring network with $(mode_string(heterogeneous, sensitive, max_k))\n
Expand Down
2 changes: 1 addition & 1 deletion src/misc.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ end

function check_data(data::AbstractMatrix, header::AbstractVector; meta_mask=nothing)
@assert size(data, 2) == length(header) "header does not fit data: $(size(data, 2)) vs. $(length(header))"
meta_mask != nothing && @assert size(data, 2) == length(meta_mask) "meta_mask does not fit data: $(length(data, 2)) vs. $(length(meta_mask))"
meta_mask != nothing && @assert size(data, 2) == length(meta_mask) "meta_mask does not fit data: $(size(data, 2)) vs. $(length(meta_mask))"
end


Expand Down
27 changes: 25 additions & 2 deletions test/learning.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -6,8 +6,8 @@ nprocs() == 1 && addprocs(1)
using FlashWeave
using FileIO


data = Matrix{Float64}(readdlm(joinpath("data", "HMP_SRA_gut", "HMP_SRA_gut_small.tsv"), '\t')[2:end, 2:end])
data_path = joinpath("data", "HMP_SRA_gut", "HMP_SRA_gut_small.tsv")
data = Matrix{Float64}(readdlm(data_path, '\t')[2:end, 2:end])
data_sp = sparse(data)

adj_exp_dict = load(joinpath("data", "learning_expected.jld2"))
Expand Down Expand Up @@ -180,6 +180,29 @@ end
end
end
end

@testset "from file" begin
path_trunk = joinpath("data", "HMP_SRA_gut", "HMP_SRA_gut_tiny")
for (data_format, suff_pair, transp_suff_pair) in zip(["tsv", "jld"],
[(".tsv", "_ids_transposed.tsv"),
("_plus_meta.jld", "_plus_meta_transposed.jld")],
[("_meta.tsv", "_meta_transposed.tsv"),("","")])
@testset "$data_format" begin
path_pairs = [path_trunk * suff for suff in (suff_pair..., transp_suff_pair...)]
pred_graphs = [graph(learn_network(path_pairs[i], path_pairs[i_meta], sensitive=true,
heterogeneous=false, max_k=3, verbose=false, transposed=transp))
for (i, i_meta, transp) in [(1, 3, false), (2, 4, true)]]

for pred_graph in pred_graphs
@test compare_graph_results(pred_graphs...,
rtol=rtol, atol=atol,
approx=true,
approx_nbr_diff=approx_nbr_diff,
approx_weight_meandiff=approx_weight_meandiff)
end
end
end
end
end

# to create expected output
Expand Down

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