This magic command support two ways of activating debugger.One is to activate debugger before executing code. This way, youcan set a break point, to step through the code from the point.You can use this mode by giving statements to execute and optionallya breakpoint.
After executing your code, %edit will return as output the code youtyped in the editor (except when it was an existing file). This wayyou can reload the code in further invocations of %edit as a variable,via _ or Out[], where is the prompt number ofthe output.
-r : Specify lines or ranges of lines to load from the source.Ranges could be specified as x-y (x..y) or in python-style x:y(x..(y-1)). Both limits x and y can be left blank (meaning thebeginning and end of the file, respectively).
This magic command can either take a local filename, a URL, an historyrange (see %history) or a macro as argument, it will prompt forconfirmation before loading source with more than 200 000 characters, unless-y flag is passed or if the frontend does not support raw_input:
In cell mode, the additional code lines are appended to the (possiblyempty) statement in the first line. Cell mode allows you to easilyprofile multiline blocks without having to put them in a separatefunction.
If foo+bar can be evaluated in the user namespace, the result isplaced at the next input prompt. Otherwise, the history is searchedfor lines which contain that substring, and the most recent one isplaced at the next input prompt.
The filename argument should be either a pure Python script (withextension .py), or a file with custom IPython syntax (such asmagics). If the latter, the file can be either a script with .ipyextension, or a Jupyter notebook with .ipynb extension. When runninga Jupyter notebook, the output from print statements and otherdisplayed objects will appear in the terminal (even matplotlib figureswill open, if a terminal-compliant backend is being used). Note that,at the system command line, the jupyter run command offers similarfunctionality for executing notebooks (albeit currently with somedifferences in supported options).
In most cases you should not need to split as a list, because thereturned value is a special type of string which can automaticallyprovide its contents either as a list (split on newlines) or as aspace-separated string. These are convenient, respectively, eitherfor sequential processing or to be passed to a shell command.
In computing, a shebang (pronounced "shi-BANG") is the character sequence consisting of the characters number sign and exclamation mark (#!) at the beginning of a script. It is also called sharp-exclamation, sha-bang,[1][2] hashbang,[3][4] pound-bang,[5][6] or hash-pling.[7]
in which interpreter is a path to an executable program. The space between #! and interpreter is optional. There could be any number of spaces or tabs either before or after interpreter. The optional-arg will include any extra spaces up to the end-of-line.
Shebang lines may include specific options that are passed to the interpreter. However, implementations vary in the parsing behavior of options; for portability, only one option should be specified without any embedded whitespace.[citation needed] Further portability guidelines are found below.
If /bin/sh specifies the Bourne shell, then the end result is that all of the shell commands in the file some/path/to/foo are executed with the positional variables $1 and $2 having the values bar and baz, respectively. Also, because the initial number sign is the character used to introduce comments in the Bourne shell language (and in the languages understood by many other interpreters), the whole shebang line is ignored by the interpreter.
The shebang is actually a human-readable instance of a magic number in the executable file, the magic byte string being 0x23 0x21, the two-character encoding in ASCII of #!. This magic number is detected by the "exec" family of functions, which determine whether a file is a script or an executable binary. The presence of the shebang will result in the execution of the specified executable, usually an interpreter for the script's language. It has been claimed[19] that some old versions of Unix expect the normal shebang to be followed by a space and a slash (#! /), but this appears to be untrue;[20] rather, blanks after the shebang have traditionally been allowed, and sometimes documented with a space (see the 1980 email in history section below).[citation needed]
Note that, even in systems with full kernel support for the #! magic number, some scripts lacking interpreter directives (although usually still requiring execute permission) are still runnable by virtue of the legacy script handling of the Bourne shell, still present in many of its modern descendants. Scripts are then interpreted by the user's default shell.
We have surveyed the neutron separation energies (S(n)) and the interaction cross sections (sigma(I)) for the neutron-rich p-sd and the sd shell region. Very recently, both measurements reached up to the neutron drip line, or close to the drip line, for nuclei of Z/=3), which shows the creation of a new magic number. A neutron-number dependence of sigma(I) shows a large increase of sigma(I) for N = 15, which supports the new magic number. The origin of the new magic number is also discussed.
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Identifying natural allelic variation that underlies quantitative trait variation remains a fundamental problem in genetics. Most studies have employed either simple synthetic populations with restricted allelic variation or performed association mapping on a sample of naturally occurring haplotypes. Both of these approaches have some limitations, therefore alternative resources for the genetic dissection of complex traits continue to be sought. Here we describe one such alternative, the Multiparent Advanced Generation Inter-Cross (MAGIC). This approach is expected to improve the precision with which QTL can be mapped, improving the outlook for QTL cloning. Here, we present the first panel of MAGIC lines developed: a set of 527 recombinant inbred lines (RILs) descended from a heterogeneous stock of 19 intermated accessions of the plant Arabidopsis thaliana. These lines and the 19 founders were genotyped with 1,260 single nucleotide polymorphisms and phenotyped for development-related traits. Analytical methods were developed to fine-map quantitative trait loci (QTL) in the MAGIC lines by reconstructing the genome of each line as a mosaic of the founders. We show by simulation that QTL explaining 10% of the phenotypic variance will be detected in most situations with an average mapping error of about 300 kb, and that if the number of lines were doubled the mapping error would be under 200 kb. We also show how the power to detect a QTL and the mapping accuracy vary, depending on QTL location. We demonstrate the utility of this new mapping population by mapping several known QTL with high precision and by finding novel QTL for germination data and bolting time. Our results provide strong support for similar ongoing efforts to produce MAGIC lines in other organisms.
Most traits of economic and evolutionary interest vary quantitatively and have multiple genes affecting their expression. Dissecting the genetic basis of such traits is crucial for the improvement of crops and management of diseases. Here, we develop a new resource to identify genes underlying such quantitative traits in Arabidopsis thaliana, a genetic model organism in plants. We show that using a large population of inbred lines derived from intercrossing 19 parents, we can localize the genes underlying quantitative traits better than with existing methods. Using these lines, we were able to replicate the identification of previously known genes that affect developmental traits in A. thaliana and identify some new ones. This paper also presents all the necessary biological and computational material necessary for the scientific community to use these lines in their own research. Our results suggest that the use of lines derived from a multiparent advanced generation inter-cross (MAGIC lines) should be very useful in other organisms.
The use of heterogeneous stocks (HS) improves the power to detect and localise QTL, and model genetic architecture more realistically. HS are the result of repeated crosses between multiple parental lines over many generations to produce a highly recombinant heterozygous outbred population. This strategy has been successfully used for fine-mapping QTL using eight parental strains in mice [29],[30] and Drosophila [31]. A disadvantage with HS is that each individual's genome is unique and heterozygous, and therefore the population must be genotyped at high density each time it is phenotyped. A related strategy, that avoids the need to re-genotype, is to generate RILs from multiple parents [32],[33], where the genomes of the founders are first mixed by several rounds of mating and then inbred to generate a stable panel of inbred lines. The name MAGIC (for multiparent advanced generation intercross) has been suggested for this type of population [33]. The large number of parental accessions increases the allelic and phenotypic diversity over traditional RILs, potentially increasing the number of QTL that segregate in the cross. The larger number of accumulated recombination events increase the mapping accuracy of the detected QTL compared to an F2 cross [34]. Thus, MAGIC lines occupy an intermediate niche between naturally occurring accessions and existing synthetic populations.
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