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PHP uses argc as a count of arguments and argv as an array containing the values of the arguments. [ 4 ] [ 5 ] To create an array from command-line arguments in the -foo:bar format, the following might be used:
Functions can be defined inside code blocks, permitting a run-time decision as to whether or not a function should be defined. There is no concept of local functions. Function calls must use parentheses with the exception of zero argument class constructor functions called with the PHP new operator, where parentheses are optional.
A bar graph shows comparisons among discrete categories. One axis of the chart shows the specific categories being compared, and the other axis represents a measured value. Some bar graphs present bars clustered in groups of more than one, showing the values of more than one measured variable. These clustered groups can be differentiated using ...
The syntax generally follows the pattern of one-letter code of the variable type, followed by a colon and the length of the data, followed by the variable value, and ending with a semicolon. For the associative array, the format is <serialised key> ; <serialised value>, repeated for each association/pair in the array.
Microsoft Excel is a spreadsheet editor developed by Microsoft for Windows, macOS, Android, iOS and iPadOS.It features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA).
Before Lisp had macros, it had so-called FEXPRs, function-like operators whose inputs were not the values computed by the arguments but rather the syntactic forms of the arguments, and whose output were values to be used in the computation. In other words, FEXPRs were implemented at the same level as EVAL, and provided a window into the meta ...
In the mathematical discipline of graph theory, the line graph of an undirected graph G is another graph L(G) that represents the adjacencies between edges of G. L(G) is constructed in the following way: for each edge in G, make a vertex in L(G); for every two edges in G that have a vertex in common, make an edge between their corresponding vertices in L(G).
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]