In reality we are talking about the line termination sequence LTS that is specific to platform. Of course this is real pain when it comes to transferring files between platforms. Martin York Martin York k 80 80 gold badges silver badges bronze badges.
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You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reset failedjags stuff:. We may be passed some unevaluated function arguments so evaluate everything here:. Convert specified character to lists - or '' if none:. Try it again - sometimes this seems to clear it up:.
Use the testjags function for more detailed diagnostics. Find references to functions in the runjags module unless we have already been told to use the standalone runjags module :. Find any matching functions used not in comments, and definitely used as a function not a variable :. Get rid of commented lines and remove all spaces:. Find any matches and add runjags to the modules if rjags method:.
If the code creates any objects, R stores them in the active, that is, runtime environment. If the code calls any objects, R uses its scoping rules to look them up. R will search the runtime environment, then the parent of the runtime environment which will be the origin environment , then the parent of the origin environment, and so on.
Notice that the calling environment might not be on the search path. Usually, a function will only call its arguments, which R can find in the active runtime environment.
Finally, R finishes running the function. It switches the active environment back to the calling environment. Now R executes any other commands in the line of code that called the function. To recap, R stores its objects in an environment system. At any moment of time, R is working closely with a single active environment. It stores new objects in this environment, and it uses the environment as a starting point when it searches for existing objects. Suppose I redefine deal at the command line like this:.
Notice that deal no longer takes an argument, and it calls the deck object, which lives in the global environment. When deal calls deck , R will need to look up the deck object.
Here, R finds the copy of deck. Recall that deal returns the top card of deck but does not remove the card from the deck. As a result, deal always returns the same card:. You know enough R syntax to remove the top card of deck. The following code will save a prisitine copy of deck and then remove the top card:. Here deal saves and then returns the top card of deck. In between, it removes the card from deck …or does it?
Instead of overwriting the global copy of deck with deck[-1, ] , deal will just create a slightly altered copy of deck in its runtime environment, as in Figure 8.
Now deal will finally clean up the global copy of deck , and we can deal cards just as we would in real life:. This behavior is now undesirable in two ways. First, shuffle fails to shuffle deck. Second, shuffle returns a copy of deck , which may be missing the cards that have been dealt away. It would be better if shuffle returned the dealt cards to the deck and then shuffled. This is what happens when you shuffle a deck of cards in real life. The second line of shuffle will create a reordered copy of DECK and save it as deck in the global environment.
This will overwrite the previous, nonshuffled version of deck. Our system finally works. For example, you can shuffle the cards and then deal a hand of blackjack:.
But the system requires deck and DECK to exist in the global environment. Lots of things happen in this environment, and it is possible that deck may get modified or erased by accident. It would be better if we could store deck in a safe, out-of-the-way place, like one of those safe, out-of-the-way environments that R creates to run functions in.
In fact, storing deck in a runtime environment is not such a bad idea. You could create a function that takes deck as an argument and saves a copy of deck as DECK. The function could also save its own copies of deal and shuffle :. When you run setup , R will create a runtime environment to store these objects in.
The environment will look like Figure 8. Now all of these things are safely out of the way in a child of the global environment. That makes them safe but hard to use. The best way to do this is to return the functions as a list:.
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