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Welcome to the Environment Modules open source project. The Environment Modules package provides for the dynamic modification of a user's environment via modulefiles.

What are Environment Modules?

Typically users initialize their environment when they log in by setting environment information for every application they will reference during the session. The Environment Modules package is a tool that simplify shell initialization and lets users easily modify their environment during the session with modulefiles.

Each modulefile contains the information needed to configure the shell for an application. Once the Modules package is initialized, the environment can be modified on a per-module basis using the module command which interprets modulefiles. Typically modulefiles instruct the module command to alter or set shell environment variables such as PATH, MANPATH, etc. modulefiles may be shared by many users on a system and users may have their own collection to supplement or replace the shared modulefiles.

Modules can be loaded and unloaded dynamically and atomically, in an clean fashion. All popular shells are supported, including bash , ksh , zsh , sh , csh , tcsh , fish , as well as some scripting languages such as perl , ruby , tcl and python .

Modules are useful in managing different versions of applications. Modules can also be bundled into metamodules that will load an entire suite of different applications.

Latest source release

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Here is an example of loading a module on a Linux machine under bash.

Now we'll switch to a different version of the module

And now we'll unload the module altogether

Now we'll log into a different machine, using a different shell (tcsh).

Note that the command line is exactly the same, but the path has automatically configured to the correct architecture.

Flavours is a wrapper built on top of Modules C-version to simplify the organization and presentation of software that requiring multiple builds against different compilers, MPI libraries, processor architectures, etc. This package is written and maintained by Mark Dixon.

fthTRIVis sortElt. endfth

The file prelude.maude includes many views out of TRIV that select the main sort of the built-in modules that we have already described in the previous sections. All these views are named in the same way: by the sort they select; for example, the standard view from TRIV into RAT selecting the sort Rat is also named Rat .

viewBoolfromTRIVtoBOOLis sortElttoBool. endv
viewNatfromTRIVtoNATis sortElttoNat. endv
viewIntfromTRIVtoINTis sortElttoInt. endv
viewRatfromTRIVtoRATis sortElttoRat. endv
viewFloatfromTRIVtoFLOATis sortElttoFloat. endv
viewStringfromTRIVtoSTRINGis sortElttoString. endv
viewQidfromTRIVtoQIDis sortElttoQid. endv

The theory DEFAULT is slightly more complex than TRIV , in that in addition to a sort it also requires that there be a distinguished “default” element in such a sort. Notice that DEFAULT imports TRIV in the following presentation:

fthDEFAULTis includingTRIV. op0:->Elt. endfth

The inclusion of the theory TRIV into the theory DEFAULT is made explicit by the following view, whose name coincides with the name of the target theory.


The Maude library also includes several views that map from DEFAULT to the various built-in data type modules by selecting the main sort and a distinguished element in it. In the case of the number sorts, this element is the zero, while for strings it is the empty string and for quoted identifiers is just the quote. Notice that operator mappings that are the identity (i.e., of the form op 0 to 0 ) do not appear explicitly in the following views but are left implicit. These views are named by appending “0” to the name of the selected sort; for example, the standard view from DEFAULT into RAT selecting the sort Rat and 0 as the default element is named Rat0 .

viewNat0fromDEFAULTtoNATis sortElttoNat. endv
viewInt0fromDEFAULTtoINTis sortElttoInt. endv
viewRat0fromDEFAULTtoRATis sortElttoRat. endv
viewFloat0fromDEFAULTtoFLOATis sortElttoFloat. op0toterm0.0. endv
viewString0fromDEFAULTtoSTRINGis sortElttoString. op0toterm"". endv
viewQid0fromDEFAULTtoQIDis sortElttoQid. op0toterm’. endv

Although in Section 6.3.6 we have defined the notion of sorted list as based on a totally ordered set of elements, we will see in Section 7.12.6 how to relax this requirement in two different ways. The first possibility is to consider a partially strictly ordered set where the incomparability relation is transitive, that is, if a is not comparable with b and b is not comparable with c with respect to the given order, then a and c are not comparable either. The predefined STRICT-WEAK-ORDER theory below specifies a strict partial order with this additional requirement, a concept known as strict weak order . The second possibility is to consider a total preorder , as specified in Section 7.11.4 below.

Either way, we obtain the following charts:

A few comments on the code above:

At the beginning of our code, we import a number of Python libraries that we will be using in different parts of our script. It’s good practice to keep all imports at the beginning of the file, as they are available globally throughout our script. All the libraries imported in this example are already present in your environment since they are prerequisites for the Catalyst installation.

Focus on the code that is inside that is where all the trading logic occurs. You can safely dismiss most of the code in the section, which is mostly to customize the visualization of the performance of our algorithm using the matplotlib library. You can copy and paste this whole section into other algorithms to obtain a similar display.

Inside the , we also used the function above. This and other functions like it can make order management and portfolio rebalancing much easier.

The asset was arbitrarily chosen. The values of 50 and 200 for the and parameters are fairly common for a dual moving average crossover strategy from the world of traditional stocks (but bear in mind that they are usually used with daily bars instead of minute bars). The and dates have been chosen so as to demonstrate how our strategy can both perform better (blue line above green line on the chart) and worse (green line above blue line towards the end) than the price of the asset we are trading.

You can change any of these parameters: , , , and and compare the results, and you will see that in most cases, the performance is either worse than the price of the asset, or you are overfitting to one specific case. As we said at the beginning of this section, this strategy is probably not used by any serious trader anymore, but its educational purpose.

Although it might not be directly apparent, the power of history() (pun intended) can not be under-estimated as most algorithms make use of prior market developments in one form or another. You could easily devise a strategy that trains a classifier with scikit-learn which tries to predict future market movements based on past prices (note, that most of the scikit-learn functions require numpy.ndarray s rather than pandas.DataFrame s, so you can simply pass the underlying ndarray of a DataFrame via .values ).

( This is actual Notebook referenced in the text below)

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is a very powerful browser-based interface to a Python interpreter. As it is already the de-facto interface for most quantitative researchers, catalyst provides an easy way to run your algorithm inside the Notebook without requiring you to use the CLI. We include this section here as an alternative to running algorithms through the command line.

I read this in its current form (and institutional subtexts) as a call for recognition of staff-status work alongside faculty-status work, and for that I think it’s great. I also know that increasing numbers of students– undergrad and grad– participate substantively in DH projects as part of coursework. Is this Bill of Rights calling on faculty to list their entire 20-person undergraduate DH seminar on the credits page? (I’m not saying that that would be a problem; I’m just pointing out one form of contribution which might be easily overlooked otherwise.)

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I want to jump in here in mid-game to add my Hancock to the bill of rights. In particular the last point, addressing “the inability of certain classes of employees to serve as PIs,” hits home to me. Several years ago, when I was still a middle of the road grad student, I tried to get a team of scholars from Europe, the US and the Caribbean to collaborate on an archive of Caribbean literature online. One of my main obstacles was that I couldn’t be PI for the project. This led me on a hunt for a friendly faculty member who was receptive to my idea. Although I owe much to the faculty member who eventually listened to what I had to say (and who helped get that monster at least 1/3 of the way to the promised land), trying to constantly translate the vision into analog slowed things down, and eventually led to the project being put on hold. I’m still waiting to get a faculty position just so that I can have the street credit to awaken the beast from its slumber. Even if I was a bit naive about some of the larger issues at stage, I would’ve been an ideal PI. Alas, if general faculty and alt-acs are getting no love, imagine a graduate student!

The problem, I want to point out, doesn’t seem to be only with our home institutions. It also seems to be coming from the granting agencies. I’m guessing institutions would back non-traditional PIs if the NEH or Mellon, wouldn’t think it’s bad joke for a graduate student to apply for a large grant. Take the NEH Startup Grant . For that grant, you can’t even apply as an individual, let alone a graduate student. Sometimes I feel that some of my DH ideas can have a large impact (I’m aware I may just be deluding myself), or at least fail with enough pedagogical detritus to justify them. Alas, in order to develop them, I have to put somebody in front of me. I’m reminded of a Coach Small Wristlet Coach FmtqKdKZMj
by @kfitz that really got me thinking on the topsy-turvy world we inhabit, where a large (perhaps the largest?) pool of talent is made to play behind the scenes, oftentimes at the expense of innovation and efficiency, just because.

So yes, let’s collaborate on a different key!

January 25, 2011 at 3:32 am

Oops, sorry for the massive typos and clunky idioms. Where’s the edit button?

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