The results of statements are not automatically printed (except at the interactive prompt), and lines of code do not need to end with semicolons. Julia discourages the use of semicolons to end statements.In Julia, parentheses must be used to call a function with zero arguments, like in rand().In Julia, reductions such as sum, prod, and max are performed over every element of an array when called with a single argument, as in sum(A), even if A has more than one dimension.Function definitions can be loaded from files outside the current working directory.
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This pattern of creating specialized objects instead of full arrays is used frequently, and is also seen in functions such as range, or with iterators such as enumerate, and zip. An AbstractRange object will act like a normal array in most cases but is more efficient because it lazily computes its values. Generally, there is no need to call collect though. To construct a full vector like in MATLAB, use collect(a:b). In Julia, a:b and a:b:c construct AbstractRange objects.To construct block matrices (concatenating in the first two dimensions), use either hvcat or combine spaces and semicolons ( ).To concatenate in the second ("horizontal") dimension use either hcat(x,y,z) or separate with spaces ( ).To concatenate in the first ("vertical") dimension use either vcat(x,y,z) or separate with semicolons ( ).In Julia, will always construct a 3-element array containing x, y and z.For example, rand(N) makes a 1-dimensional array. Julia has true one-dimensional arrays.Instead, users can use optional and keyword arguments to achieve similar capabilities. MATLAB's nargout, which is often used in MATLAB to do optional work based on the number of returned values, does not exist in Julia. In Julia, multiple values are returned and assigned as tuples, e.g.As a result, some operations can throw a domain error if they expect a float for example, julia> a = -1 2^a throws a domain error, as the result is not an integer (see the FAQ entry on domain errors for details). In Julia, literal numbers without a decimal point (such as 42) create integers instead of floating point numbers.The imaginary unit sqrt(-1) is represented in Julia as im, not i or j as in MATLAB.Julia has push! and append!, which grow Vectors much more efficiently than MATLAB's a(end+1) = val. Whereas in MATLAB a(4) = 3.2 can create the array a = and a(5) = 7 can grow it into a =, the corresponding Julia statement a = 7 throws an error if the length of a is less than 5 or if this statement is the first use of the identifier a. Julia does not automatically grow arrays in an assignment statement.If a function modifies an array, the changes will be visible in the caller. Julia values are not copied when passed to a function.After A = B, changing elements of B will modify A as well. Julia arrays are not copied when assigned to another variable.Julia arrays are indexed with square brackets, A.The following are some noteworthy differences that may trip up Julia users accustomed to MATLAB: There are major syntactic and functional differences. Edit on GitHub Noteworthy Differences from other Languages Noteworthy differences from MATLABĪlthough MATLAB users may find Julia's syntax familiar, Julia is not a MATLAB clone. Instrumenting Julia with DTrace, and bpftrace.Reporting and analyzing crashes (segfaults).Static analyzer annotations for GC correctness in C code.Proper maintenance and care of multi-threading locks.printf() and stdio in the Julia runtime.Talking to the compiler (the :meta mechanism).High-level Overview of the Native-Code Generation Process.Noteworthy differences from Common Lisp.Noteworthy Differences from other Languages.Multi-processing and Distributed Computing.Mathematical Operations and Elementary Functions.
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