From f2b6185e3f85c1c5522ab62b7663a4ffcf499b73 Mon Sep 17 00:00:00 2001
From: Mirek Kratochvil <exa.exa@gmail.com>
Date: Wed, 31 Mar 2021 11:48:08 +0200
Subject: [PATCH] clean up all trailing whitespace
---
README.md | 8 ++++----
src/analysis/fba.jl | 2 +-
src/analysis/fluxes.jl | 6 +++---
src/analysis/fva.jl | 2 +-
src/analysis/pfba.jl | 2 +-
src/io/io.jl | 12 ++++++------
src/reconstruction/model_manipulations.jl | 2 +-
src/sampling/sampling_tools.jl | 20 ++++++++++----------
src/types/agene.jl | 6 +++---
src/types/ametabolite.jl | 8 ++++----
src/types/areaction.jl | 8 ++++----
src/types/metabolicModel.jl | 6 +++---
test/testing_functions.jl | 2 +-
13 files changed, 42 insertions(+), 42 deletions(-)
diff --git a/README.md b/README.md
index 36b6b282b..821255135 100644
--- a/README.md
+++ b/README.md
@@ -7,7 +7,7 @@
[docs-img]:https://img.shields.io/badge/docs-latest-blue.svg
[docs-url]: https://stelmo.github.io/CobraTools.jl/dev
-
+
[ci-img]: https://github.com/stelmo/CobraTools.jl/actions/workflows/ci.yml/badge.svg?branch=master&event=push
[ci-url]: https://github.com/stelmo/CobraTools.jl/actions/workflows/ci.yml
@@ -40,9 +40,9 @@ using JuMP
using Tulip # pick any solver supported by JuMP
# Import E. coli models (models have pretty printing)
-model_1 = read_model("iJO1366.json")
-model_2 = read_model("iJO1366.json")
-model_3 = read_model("iJO1366.json")
+model_1 = read_model("iJO1366.json")
+model_2 = read_model("iJO1366.json")
+model_3 = read_model("iJO1366.json")
# Build an exascale model
exascale_model = join(model_1, model_2, model_3,...)
diff --git a/src/analysis/fba.jl b/src/analysis/fba.jl
index b51d16548..69041d35a 100644
--- a/src/analysis/fba.jl
+++ b/src/analysis/fba.jl
@@ -18,7 +18,7 @@ flux_balance_analysis(model::M, optimizer) where {M<:MetabolicModel} =
Run flux balance analysis (FBA) on the `model` optionally specifying `objective_rxn(s)` and their `weights` (empty `weights` mean equal weighting per reaction).
Optionally also specify any additional flux constraints with `constraints`, a dictionary mapping reaction `id`s to tuples of (lb, ub) flux constraints.
-Note, the `optimizer` must be set to perform the analysis, any JuMP solver will work.
+Note, the `optimizer` must be set to perform the analysis, any JuMP solver will work.
The `solver_attributes` can also be specified in the form of a dictionary where each (key, value) pair will be passed to `set_optimizer_attribute(cbmodel, key, value)`.
This function builds the optimization problem from the model, and hence uses the constraints implied by the model object.
Returns a dictionary of reaction `id`s mapped to fluxes if solved successfully, otherwise an empty dictionary.
diff --git a/src/analysis/fluxes.jl b/src/analysis/fluxes.jl
index 4befdd959..4d9db2f15 100644
--- a/src/analysis/fluxes.jl
+++ b/src/analysis/fluxes.jl
@@ -1,7 +1,7 @@
"""
map_fluxes(v, model::CobraModel)
-Map fluxes from an optimization problem (`v`) to rxns in a model.
+Map fluxes from an optimization problem (`v`) to rxns in a model.
`v` can be a JuMP object (fluxes) or an array of Float64 fluxes.
Assumes they are in order of `model.reactions`, which they should be since the optimization problem is constructed from the model.
"""
@@ -24,7 +24,7 @@ end
"""
atom_exchange(flux_dict::Dict{String, Float64}, model::CobraModel)
-Return a dictionary mapping the flux of atoms across the boundary of the model given `flux_dict` of reactions in `model`.
+Return a dictionary mapping the flux of atoms across the boundary of the model given `flux_dict` of reactions in `model`.
Here `flux_dict` is a mapping of reaction `id`s to fluxes, e.g. from FBA.
"""
function atom_exchange(flux_dict::Dict{String,Float64}, model::CobraModel)
@@ -45,7 +45,7 @@ end
"""
get_exchanges(rxndict::Dict{String, Float64}; top_n=8, ignorebound=1000.0, verbose=true)
-Display the top_n producing and consuming exchange fluxes.
+Display the top_n producing and consuming exchange fluxes.
Set top_n to a large number to get all the consuming/producing fluxes.
Ignores infinite (problem upper/lower bound) fluxes (set with ignorebound).
When `verbose` is false, the output is not printed out.
diff --git a/src/analysis/fva.jl b/src/analysis/fva.jl
index eceae4a34..9c33be1af 100644
--- a/src/analysis/fva.jl
+++ b/src/analysis/fva.jl
@@ -116,7 +116,7 @@ Run flux variability analysis (FVA) on the `model` with `objective_rxn(s)` and o
It runs fba on the model once to determine the optimum of the objective.
Optionally also specify any additional flux constraints with `constraints`, a dictionary mapping reaction `id`s to tuples of (ub, lb) flux constraints.
The model is then constrained to produce objective flux bounded by `optimum_bound` from below (set to slightly less than 1.0 for stability) and each flux in the model sequentially minimized and maximized.
-Note, the `optimizer` must be set to perform the analysis, any JuMP solver will work.
+Note, the `optimizer` must be set to perform the analysis, any JuMP solver will work.
The `solver_attributes` can also be specified in the form of a dictionary where each (key, value) pair will be passed to `set_optimizer_attribute(cbmodel, key, value)`.
This function builds the optimization problem from the model, and hence uses the constraints implied by the model object.
Returns two dictionaries (`fva_max` and `fva_min`) that each reaction `id`s to dictionaries of the resultant flux distributions (if solved successfully) when that `id` is optimized.
diff --git a/src/analysis/pfba.jl b/src/analysis/pfba.jl
index a142d68eb..29bde931e 100644
--- a/src/analysis/pfba.jl
+++ b/src/analysis/pfba.jl
@@ -117,7 +117,7 @@ function pfba(
for lbconval in [0.999999, 0.99999, 0.9999, 0.999, 0.99] # relax bound for stability
if termination_status(cbm) == MOI.OPTIMAL ||
- termination_status(cbm) == MOI.LOCALLY_SOLVED # try to relax bound if failed optimization
+ termination_status(cbm) == MOI.LOCALLY_SOLVED # try to relax bound if failed optimization
break
else
JuMP.delete(cbm, pfbacon)
diff --git a/src/io/io.jl b/src/io/io.jl
index 5f8e3ea3d..843d42dde 100644
--- a/src/io/io.jl
+++ b/src/io/io.jl
@@ -7,17 +7,17 @@ The model format is inferred from the `file_location` extension.
Note, some meta-information may be lost when importing a model. Importantly, only information regarding the
reactions, metabolites and genes are imported. Currently reading JSON models captures the most meta-information
-regarding reactions, metabolites and genes (e.g. the notes and annotation fields).
+regarding reactions, metabolites and genes (e.g. the notes and annotation fields).
When importing Matlab models some annotation and notes may not be imported because of non-standard field names used by some models.
-Gene reaction rules are successfully imported only if they adhere to this format: `"(YIL010W and YLR043C) or (YIL010W and YGR209C)"`,
+Gene reaction rules are successfully imported only if they adhere to this format: `"(YIL010W and YLR043C) or (YIL010W and YGR209C)"`,
where `or` can be interchanged with `OR, |, ||` and `and` can be interchanged with `AND, &, &&`.
-Other gene reaction rules formats are not supported yet, but file an issue if your format is standard and needs to be included.
+Other gene reaction rules formats are not supported yet, but file an issue if your format is standard and needs to be included.
-However, in all cases the basic information needed to perform constraint based analysis should be imported successfully,
+However, in all cases the basic information needed to perform constraint based analysis should be imported successfully,
e.g. stoichiometrix matrix, constraints etc..
Advanced tools that require, e.g. metabolite formulas, gene reaction rules, and KEGG or BIGG IDs, will not function if these are improperly imported.
-Always inspect the imported model before running analysis (garbage in -> garbage out).
+Always inspect the imported model before running analysis (garbage in -> garbage out).
"""
function read_model(file_location::String)
if endswith(file_location, ".json")
@@ -73,7 +73,7 @@ end
"""
parsegrr(string_rule, genes::Array{Gene, 1})
-Parse a gene reaction rule string `string_rule` into a nested `gene` array `Array{Array{Gene, 1}, 1}`.
+Parse a gene reaction rule string `string_rule` into a nested `gene` array `Array{Array{Gene, 1}, 1}`.
Format: (YIL010W and YLR043C) or (YIL010W and YGR209C) where `or` can also be `OR, |, ||` and where `and` can also be `AND, &, &&`.
"""
diff --git a/src/reconstruction/model_manipulations.jl b/src/reconstruction/model_manipulations.jl
index 2eea56d80..d6b6c3ed9 100644
--- a/src/reconstruction/model_manipulations.jl
+++ b/src/reconstruction/model_manipulations.jl
@@ -129,7 +129,7 @@ end
Inspect metabolites and genes of `model` relative to the reactions of `model`.
Remove genes or metabolites that are not used in the reactions.
-Add genes or metabolites that are not present in `model.genes` or `model.metabolites` but are used in `model.reactions`.
+Add genes or metabolites that are not present in `model.genes` or `model.metabolites` but are used in `model.reactions`.
Everything is based on the `id` of metabolites and genes, thus is it possible for a metabolite or gene to be duplicated but using
a different `id`. Other functions are provided to help identify these cases.
diff --git a/src/sampling/sampling_tools.jl b/src/sampling/sampling_tools.jl
index b08b2eeda..0762c4cf5 100644
--- a/src/sampling/sampling_tools.jl
+++ b/src/sampling/sampling_tools.jl
@@ -1,7 +1,7 @@
"""
get_warmup_points(cbmodel, v, mb, lbs, ubs; random_objective=false, numstop=1e10)
-Generate warmup points for all the reactions on the model that
+Generate warmup points for all the reactions on the model that
are not fixed. Assumes you feed in a JuMP model that is already
constrained i.e. the constrains are already applied into cbmodel.
Note, extra constraints applied to ubs and lbs will have no effect.
@@ -77,14 +77,14 @@ end
"""
hit_and_run(N::Int64, model::CobraModel, optimizer; constraints=Dict{String, Tuple{Float64,Float64}}(), keepevery=100, samplesize=1000, solver_attributes=Dict{Any, Any}(), random_objective=false)
-Perform basic hit and run sampling for `N` iterations using `model` with `optimizer` from `JuMP`.
+Perform basic hit and run sampling for `N` iterations using `model` with `optimizer` from `JuMP`.
Additional constraints supplied by `constraints` as a dictionary of reaction `id`s mapped to a tuple of `(lb, ub)` of fluxes.
Every `keepevery` iteration is logged as a sample, where the sample size matrix has `samplesize` columns.
Solver specific settings can be set using `solver_attributes`.
Warm up points are generated in a flux variability sense, unless `random_objective` is true, in which case a randomly weighted objective is used 2*number of reactions to define the warmup points.
-Note that N needs to be >> samplesize.
-Sample size is the size of the samples kept in memory.
+Note that N needs to be >> samplesize.
+Sample size is the size of the samples kept in memory.
The larger samplesize is the better the approximation becomes, but the more memory the sampler requires.
See also: [`achr`](@ref)
@@ -126,13 +126,13 @@ function hit_and_run(
current_point = zeros(size(wpoints, 1))
current_point .= wpoints[:, rand(1:nwpts)] # pick random initial point
- δdirtol = 1e-6 # too small directions get ignored ≈ 0 (solver precision issue)
+ δdirtol = 1e-6 # too small directions get ignored ≈ 0 (solver precision issue)
sample_num = 0
samplelength = 0
updatesamplesizelength = true
for n = 1:N
- # direction = random point - current point
+ # direction = random point - current point
if updatesamplesizelength
direction_point = (@view wpoints[:, rand(1:nwpts)]) - (@view current_point[:]) # use warmup points to find direction in warmup phase
else
@@ -157,7 +157,7 @@ function hit_and_run(
upper = 1e10
end
lower > λmin && (λmin = lower) # max min step size that satisfies all bounds
- upper < λmax && (λmax = upper) # min max step size that satisfies all bounds
+ upper < λmax && (λmax = upper) # min max step size that satisfies all bounds
end
if λmax <= λmin || λmin == -1e10 || λmax == 1e10 # this sometimes can happen
@@ -260,12 +260,12 @@ function achr(
shat = mean(wpoints, dims = 2)[:] # mean point
- δdirtol = 1e-6 # too small directions get ignored ≈ 0 (solver precision issue)
+ δdirtol = 1e-6 # too small directions get ignored ≈ 0 (solver precision issue)
sample_num = 0
samplelength = 0
updatesamplesizelength = true
for n = 1:N
- if updatesamplesizelength # switch to samples
+ if updatesamplesizelength # switch to samples
direction_point = (@view wpoints[:, rand(1:nwpts)]) - (@view current_point[:]) # use warmup points to find direction in warmup phase
else
direction_point = (@view samples[:, rand(1:(samplelength))]) - (@view shat[:]) # after warmup phase, only find directions in sampled space
@@ -287,7 +287,7 @@ function achr(
upper = 1e10
end
lower > λmin && (λmin = lower) # max min step size that satisfies all bounds
- upper < λmax && (λmax = upper) # min max step size that satisfies all bounds
+ upper < λmax && (λmax = upper) # min max step size that satisfies all bounds
end
if λmax <= λmin || λmin == -1e10 || λmax == 1e10 # this sometimes can happen
diff --git a/src/types/agene.jl b/src/types/agene.jl
index d4a72c037..8c0f5c3ca 100644
--- a/src/types/agene.jl
+++ b/src/types/agene.jl
@@ -7,7 +7,7 @@ id :: String
name :: String
notes :: Dict{String, Array{String, 1}}
annotation :: Dict{String, Union{Array{String, 1}, String}}
-````
+````
"""
mutable struct Gene
id::String
@@ -74,7 +74,7 @@ end
"""
getindex(genes::Array{Gene, 1}, gene::Gene)
-Get the index of a `gene` in an array of `genes` based on `id` field.
+Get the index of a `gene` in an array of `genes` based on `id` field.
Return -1 if no matches found.
Typically used `index = genes[gene]`.
@@ -92,7 +92,7 @@ end
findfirst(genes::Array{Gene, 1}, geneid::String)
Return the gene with `geneid` in `genes` or else `nothing`.
-Based on matching `id` fields.
+Based on matching `id` fields.
Typically used: `gene = findfirst(model.genes, geneid)`.
"""
diff --git a/src/types/ametabolite.jl b/src/types/ametabolite.jl
index ce9bffb44..d8cda6441 100644
--- a/src/types/ametabolite.jl
+++ b/src/types/ametabolite.jl
@@ -83,11 +83,11 @@ end
"""
getindex(mets::Array{Metabolite, 1}, met::Metabolite)
-Get the index of a `met` in an array of `mets`, based on `id` equality.
+Get the index of a `met` in an array of `mets`, based on `id` equality.
Return -1 if no matches found.
This function overrides the `[]` notation from Base.
-Typically used: `index = mets[met]` works.
+Typically used: `index = mets[met]` works.
"""
function Base.getindex(mets::Array{Metabolite,1}, met::Metabolite)
for i in eachindex(mets)
@@ -101,8 +101,8 @@ end
"""
findfirst(mets::Array{Metabolite, 1}, metid::String)
-Return the metabolite in `mets` with `metid`, based in `id` field.
-If nothing matches, return `nothing`.
+Return the metabolite in `mets` with `metid`, based in `id` field.
+If nothing matches, return `nothing`.
Typically used: `met = findfirst(model.mets, metid)`.
"""
diff --git a/src/types/areaction.jl b/src/types/areaction.jl
index 542d56d84..ec72ec8a3 100644
--- a/src/types/areaction.jl
+++ b/src/types/areaction.jl
@@ -125,7 +125,7 @@ end
Reaction(id::String, metabolites::Dict{Metabolite, Float64}, dir="bidir")
Assign the `id`, `metabolites` (and their associated stoichiometries), and the direcionality (`dir`) of a reaction to a `Reaction` struct.
-Directionality is specified using `"for"` (forward), `"rev"` (reverse), or any other string for bidirectional reactions.
+Directionality is specified using `"for"` (forward), `"rev"` (reverse), or any other string for bidirectional reactions.
All other fields are left unassigned.
See also: [`Reaction()`](@ref).
@@ -164,7 +164,7 @@ end
"""
getindex(rxns::Array{Reaction, 1}, rxn::Reaction)
-Get the index of a reaction `rxn` in an array of reactions `rxns`, based in `id`.
+Get the index of a reaction `rxn` in an array of reactions `rxns`, based in `id`.
Return -1 if no matches found.
Typically used, `index = rxns[rxn]`.
@@ -197,9 +197,9 @@ end
"""
check_duplicate_reaction(rxns::Array{Reaction, 1}, rxn::Reaction)
-Check if `rxn` already exists in `rxns` but has another id.
+Check if `rxn` already exists in `rxns` but has another id.
Looks through all the reaction equations of `rxns` and compares metabolite `id`s and their stoichiometric coefficients to those of `rxn`.
-If `rxn` has the same reaction equation as another reaction in `rxns`, the return true and the index of the first match.
+If `rxn` has the same reaction equation as another reaction in `rxns`, the return true and the index of the first match.
See also: [`is_mass_balanced`](@ref)
"""
diff --git a/src/types/metabolicModel.jl b/src/types/metabolicModel.jl
index efea47c43..f2c354d41 100644
--- a/src/types/metabolicModel.jl
+++ b/src/types/metabolicModel.jl
@@ -48,7 +48,7 @@ end
"""
getindex(model::CobraModel, rxn::Reaction)
-Get the index of `rxn` in `model`, based on reaction `id`.
+Get the index of `rxn` in `model`, based on reaction `id`.
Return -1 if not found.
Typical usage: ind = model[rxn]
@@ -60,7 +60,7 @@ end
"""
getindex(model::CobraModel, met::Metabolite)
-Get the index of `met` in `model`, based on metabolite `id`.
+Get the index of `met` in `model`, based on metabolite `id`.
Return -1 if not found.
Typical usage: ind = model[met]
@@ -72,7 +72,7 @@ end
"""
getindex(model::CobraModel, gene::Gene)
-Get the index of `gene` in `model`, based on gene `id`.
+Get the index of `gene` in `model`, based on gene `id`.
Return -1 if not found.
Typical usage: ind = model[gene]
diff --git a/test/testing_functions.jl b/test/testing_functions.jl
index a1cec140c..53ee2c0be 100644
--- a/test/testing_functions.jl
+++ b/test/testing_functions.jl
@@ -46,7 +46,7 @@ function model_comparison_test(model1, model2)
end
"""
-Test if model is the same after it was read in, saved, and then re-read.
+Test if model is the same after it was read in, saved, and then re-read.
"""
function read_write_read_test(model, format)
tmpfile = joinpath("data", "temp." * format)
--
GitLab