that of other dynamic languages, and even rivals that of sta�cally-compiled languages. For large scale numerical problems, speed always has been, con�nues to be, and probably always will be crucial: the input A, instead of crea�ng a copy. LinearAlgebra.eigvals – Func�on. eigvals(A; permute::Bool=true, scale::Bool=true, sortby) -> values Return the eigenvalues of A. For general non-symmetric matrices it is possible to specify how the matrix is balanced before the eigenvalue calcula�on. The permute, scale, and sortby keywords are the same as for eigen!. Examples 3J R Bunch and L Kaufman, Some stable

that of other dynamic languages, and even rivals that of sta�cally-compiled languages. For large scale numerical problems, speed always has been, con�nues to be, and probably always will be crucial: the input A, instead of crea�ng a copy. LinearAlgebra.eigvals – Func�on. eigvals(A; permute::Bool=true, scale::Bool=true, sortby) -> values Return the eigenvalues of A. For general non-symmetric matrices it is possible to specify how the matrix is balanced before the eigenvalue calcula�on. The permute, scale, and sortby keywords are the same as for eigen!. Examples 3J R Bunch and L Kaufman, Some stable

that of other dynamic languages, and even rivals that of statically-compiled languages. For large scale numerical problems, speed always has been, continues to be, and probably always will be crucial: explain and understand. Fair point. Second, and arguably worse, is that it's bad for programming "at scale." When you see a small piece of code in one place like this, it's quite clear what's going on: s to the existing global variable. This addresses both issues while preserving the "programming at scale" benefits of the 1.0 behavior: global variables have no spooky effect on the meaning of code that

that of other dynamic languages, and even rivals that of statically-compiled languages. For large scale numerical problems, speed always has been, continues to be, and probably always will be crucial: explain and understand. Fair point. Second, and arguably worse, is that it's bad for programming "at scale." When you see a small piece of code in one place like this, it's quite clear what's going on: s to the existing global variable. This addresses both issues while preserving the "programming at scale" benefits of the 1.0 behavior: global variables have no spooky effect on the meaning of code that

that of other dynamic languages, and even rivals that of statically-compiled languages. For large scale numerical problems, speed always has been, continues to be, and probably always will be crucial: explain and understand. Fair point. Second, and arguably worse, is that it's bad for programming "at scale." When you see a small piece of code in one place like this, it's quite clear what's going on: s to the existing global variable. This addresses both issues while preserving the "programming at scale" benefits of the 1.0 behavior: global variables have no spooky effect on the meaning of code that

that of other dynamic languages, and even rivals that of statically-compiled languages. For large scale numerical problems, speed always has been, continues to be, and probably always will be crucial: explain and understand. Fair point. Second, and arguably worse, is that it's bad for programming "at scale." When you see a small piece of code in one place like this, it's quite clear what's going on: s to the existing global variable. This addresses both issues while preserving the "programming at scale" benefits of the 1.0 behavior: global variables have no spooky effect on the meaning of code that

that of other dynamic languages, and even rivals that of statically-compiled languages. For large scale numerical problems, speed always has been, continues to be, and probably always will be crucial: explain and understand. Fair point. Second, and arguably worse, is that it's bad for programming "at scale." When you see a small piece of code in one place like this, it's quite clear what's going on: s to the existing global variable. This addresses both issues while preserving the "programming at scale" benefits of the 1.0 behavior: global variables have no spooky effect on the meaning of code that

that of other dynamic languages, and even rivals that of statically-compiled languages. For large scale numerical problems, speed always has been, continues to be, and probably always will be crucial: explain and understand. Fair point. Second, and arguably worse, is that it's bad for programming "at scale." When you see a small piece of code in one place like this, it's quite clear what's going on: s to the existing global variable. This addresses both issues while preserving the "programming at scale" benefits of the 1.0 behavior: global variables have no spooky effect on the meaning of code that

that of other dynamic languages, and even rivals that of statically-compiled languages. For large scale numerical problems, speed always has been, continues to be, and probably always will be crucial: explain and understand. Fair point. Second, and arguably worse, is that it's bad for programming "at scale." When you see a small piece of code in one place like this, it's quite clear what's going on: s to the existing global variable. This addresses both issues while preserving the "programming at scale" benefits of the 1.0 behavior: global variables have no spooky effect on the meaning of code that

that of other dynamic languages, and even rivals that of statically-compiled languages. For large scale numerical problems, speed always has been, continues to be, and probably always will be crucial: explain and understand. Fair point. Second, and arguably worse, is that it's bad for programming "at scale." When you see a small piece of code in one place like this, it's quite clear what's going on: s to the existing global variable. This addresses both issues while preserving the "programming at scale" benefits of the 1.0 behavior: global variables have no spooky effect on the meaning of code that