Try `reinterpret(UInt8, x.chunks)`
On Monday, September 28, 2015 at 1:01:47 AM UTC-4, Sweta Yamini wrote:
>
>
>
> Hi,
>
> I am new to Julia. I have an N X N BitArray that I want to pack to Uint8
> of size N X ceil(N/8)
>
> I tried to reinterpret the array as
>
> packed = reinterpret(Uint8,
working on a Julia PLplot wrapper
https://github.com/wildart/PLplot.jl. PLplot is a powerful
cross-platform library that can be used to create standard x-y plots,
semi-log plots, log-log plots, contour plots, 3D surface plots, mesh plots,
bar and pie charts, dynamic plots, animation, etc. Library
PLplot cannot use new colors, except predefined before initialization,
during plotting. This makes usage of Compose (primitives drawing backend
package for Gadfly) somewhat hard because information about primitive
colors appear as as you parse plot structure. Moreover, PLplot has large
I quite agree with Tom, various data interfaces are could be easily
implemented it has nothing to do with underling plotting routines.
@Tom In light of RFC: unify plotting packages under a common organization
https://github.com/dcjones/Gadfly.jl/issues/658, it would be a good
effort to
Hi all,
I've started working on a Julia PLplot wrapper
https://github.com/wildart/PLplot.jl. PLplot is a powerful cross-platform
library
that can be used to create standard x-y plots, semi-log plots, log-log
plots, contour plots, 3D surface plots, mesh plots, bar and pie charts,
dynamic
map(e-replace(string(e), ',', '.'), x)
On Saturday, May 16, 2015 at 2:40:05 PM UTC-4, paul analyst wrote:
I have file with decimal separator lika ,
x=readdlm(x.txt,'\t')
julia x=x[2:end,:]
6390x772 Array{Any,2}:
some kolumns looks :
julia x[:,69]
6390-element Array{Any,1}:
0.0
0,33
Thanks.
On Saturday, May 2, 2015 at 4:27:39 PM UTC-4, Jameson wrote:
There's Base.keytype and Base.valuetype. I think this may be a reasonable
argument for making Tuple iterable. (
https://github.com/JuliaLang/julia/pull/10380#issuecomment-96837574)
On Sat, May 2, 2015 at 4:12 PM
In 0.3 it was possible to get type of key and value as a tuple using
*eltype* function as follow
julia d = Dict{Char,Int}(['a','b'], [1,2])
Dict{Char,Int64} with 2 entries:
'b' = 2
'a' = 1
julia K,V = eltype(d)
(Char,Int64)
julia K
Char
After adding a *Tuple* type in 0.4, *eltype* returns
Hi, I am a computational biologist and I do my majority of jobs using
Julia right now. So far biojulia is not so practical but you can using
BioPython package. It is quite convenient and painless to call python
package so far. R packages are also necessary for bioinformatics. However,
Unfortunately, Spark.jl is an incorrect RDD implementation. Instead of
creating transformations as independent abstraction operations with a lazy
evaluation, the package has all transformations immediately executed upon
their call. This is completely undermines whole purpose of RDD as
Of course, a Spark data access infrastructure is unbeatable, due to mature
JVM-based libraries for accessing various data sources and formats (avro,
parquet, hdfs). That includes SQL support as well. But, look at Python and
R bindings, these are just facades for JVM calls. MLLib is written in
However, I wonder, how hard it would be to implement RDD in Julia? It looks
straight forward from a RDD paper
https://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf how to
implement it. It is a robust abstraction that can be used in any parallel
computation.
On Thursday, April 16, 2015
1) simply wrap the Spark java API via JavaCall. This is the low level
approach. BTW I've experimented with javaCall and found it was unstable
also lacking functionality (e.g. there's no way to shutdown the jvm or
create a pool of JVM analogous to DB connections) so that might need some
It looks like program exits before STDOUT output is finished. That is
because worker's console output is redirected to master and processed
asynchronously. If you run your program in julia console, you'll get
correct output.
On Monday, April 13, 2015 at 6:07:41 PM UTC-4, Harry B wrote:
I
Is it possible to increase size of a created sparse matrix in a following
manner:
julia m = sparse([2,3], [1,1], [1,3])
3x1 sparse matrix with 2 Int64 entries:
[2, 1] = 1
[3, 1] = 3
julia m[4,1] = 1
ERROR: BoundsError
in setindex! at sparse/sparsematrix.jl:1493
julia m.m = 4
4
This could be DNS issue. Try add 'mycurrenthostname xxx.xxx.xxx.xxx' to the
'hosts' file.
On Monday, April 13, 2015 at 6:10:11 AM UTC-4, John wrote:
I'm unable to add a remote instance using addprocs (or a machine file).
This works (without prompt):
ssh xxx.xxx.xxx.xxx
This command hangs
Spark integration is a tricky thing. Python and R bindings go in a great
length to map language specific functions into Spark JVM library calls. I
guess same could be done with JavaCall.jl package in a manner similar to
SparkR. Look at slide 20 from here:
Hey all,
LMDB.jl https://github.com/wildart/LMDB.jl is a wrapper around Lightning
Memory-Mapped Database (aka LMDB) which is an ultra-fast, ultra-compact
key-value embedded data store developed by Symas for the OpenLDAP Project (
http://symas.com/mdb/).
Documentation and examples are available
Defining an RL-agent environment in RL-Glue API is a straightforward task.
Apart from (de)initialization calls, an environment respond for the agent
action must me defined. This respond should have an appropriate reward for
the agent (There are two separate placeholders for integer and real
Reinforcement learning (RL) isn't covered much in Julia packages. There is
a collection of RL algorithms over MDP in package:
https://github.com/cpritcha/MDP. There is a collection of IJulia notebooks
from a Stanford course that cover more RL algorithms:
Here is a good paper on initializing k-means with kd-trees:
http://www.sciencedirect.com/science/article/pii/S0167865507000165
You can use FLANN package for large data sets. Make sure to read FLANN
documentation
http://www.cs.ubc.ca/research/flann/uploads/FLANN/flann_manual-1.8.4.pdf
for
)
Github Address: https://github.com/wildart/ManifoldLearning.jl
Documentation:
http://manifoldlearningjl.readthedocs.org/en/latest/index.html
The package has been registered at METADATA.
-- Art
You should try to registered them, otherwise who needs the central package
repo if anybody can configure dependencies from various sources. Or, you
can write an install script that clones all dependencies for user.
On Saturday, July 26, 2014 12:37:17 PM UTC-4, S Wade wrote:
Hi all,
I have
(LLE)
Hessian Eigenmaps (HLLE)
Laplacian Eigenmaps (LEM)
Local tangent space alignment (LTSA)
Github Address: https://github.com/wildart/ManifoldLearning.jl
Documentation:
http://manifoldlearningjl.readthedocs.org/en/latest/index.html
The package has been registered at METADATA
Looks like I have to move manifold learning methods from
DimensionalityReduction to somewhere else.
-- Art
On Friday, July 18, 2014 10:13:16 PM UTC-4, Dahua Lin wrote:
John,
I guess what you intended to say is to deprecate DimensionalityReduction
(instead of deprecate MultivariateStats)
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