Fix memory bug (#46)

Univariate problems were assumed to be small. When this wasn't the case, the resulting static arrays were too big, causing an error. This fixes the problem.

Author: ojwoodford

Project.toml

@@ -1,7 +1,7 @@
 name = "NLLSsolver"
 uuid = "50b5cf9e-bf7a-4e29-8981-4280cbba70cb"
 authors = ["Oliver Woodford"]
-version = "4.0.0"
+version = "4.0.1"
 
 [deps]
 DiffResults = "163ba53b-c6d8-5494-b064-1a9d43ac40c5"

src/structs.jl

@@ -102,7 +102,7 @@ mutable struct NLLSInternal{LSType}
         return new{LSType}(0., 0., starttimens, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, linsystem)
     end
 end
-NLLSInternal(unfixed::UInt, varlen, starttimens) = NLLSInternal(ifelse(is_static(varlen), UniVariateLSstatic{dynamic(varlen), dynamic(varlen*varlen)}(unfixed), UniVariateLSdynamic(unfixed, dynamic(varlen))), starttimens)
+NLLSInternal(unfixed::UInt, varlen, starttimens) = NLLSInternal(dynamic(is_static(varlen)) && varlen <= 16 ? UniVariateLSstatic{dynamic(varlen), dynamic(varlen*varlen)}(unfixed) : UniVariateLSdynamic(unfixed, dynamic(varlen)), starttimens)
 
 getresult(data::NLLSInternal) = NLLSResult(data.startcost, data.bestcost, data.timetotal*1.e-9, data.timeinit*1.e-9, data.timecost*1.e-9, data.timegradient*1.e-9, data.timesolver*1.e-9, data.converged, data.iternum, data.costcomputations, data.gradientcomputations, data.linearsolvers)