Is there any tool that enables me to input a list of tuples and that shows me a graph that represents the tuples?
Example:
(root,a), (root,b), (b,c), (b,d)
This would be a Tree that looks like that
root
/ \
a b
/ \
c d
I need this to verify that the topology of a network I created in mininet really looks like I want. It has about 1000 links and it is not possible to check that manually without a visualisation.
I does not matter if it is an online tool, a python script, a command line tool or something else.
I found a solution. Gephi works fine!
Related
This is related to this question on accesing the POD, but it goes further than that. You can easily access the Abstract Syntax Tree of a Perl 6 program using:
perl6 --target=ast -e '"Þor is mighty!".say'
This will print the whole Q abstract syntax tree. It's not too clear how to make this from your own program, or I haven't found how to do it. In fact, the CoreHackers::Q module runs that as an external script. But being able to access it from your own program, like
use QAST; # It does not exist
my $this-qast = QAST::Load("some-external-file.p6") # Would want something like this
would be great. I'm pretty sure it should be possible, at the NQP level and probably in a Rakudo-dependent way. Does someone know hot it goes?
Since QAST is not a part of the Perl 6 language specification, but an internal implementation detail of Rakudo, there's no official way to do this. Eventually there will be an AST form that is part of the language specification, but that doesn't yet exist (the 007 project which is working on exploring this area).
It is, however, possible to obtain the QAST tree by using:
use nqp;
my $ast = nqp::getcomp("perl6").eval("say 42", :target<ast>);
say $ast.dump();
In tensorflow the training from the scratch produced following 6 files:
events.out.tfevents.1503494436.06L7-BRM738
model.ckpt-22480.meta
checkpoint
model.ckpt-22480.data-00000-of-00001
model.ckpt-22480.index
graph.pbtxt
I would like to convert them (or only the needed ones) into one file graph.pb to be able to transfer it to my Android application.
I tried the script freeze_graph.py but it requires as an input already the input.pb file which I do not have. (I have only these 6 files mentioned before). How to proceed to get this one freezed_graph.pb file? I saw several threads but none was working for me.
You can use this simple script to do that. But you must specify the names of the output nodes.
import tensorflow as tf
meta_path = 'model.ckpt-22480.meta' # Your .meta file
output_node_names = ['output:0'] # Output nodes
with tf.Session() as sess:
# Restore the graph
saver = tf.train.import_meta_graph(meta_path)
# Load weights
saver.restore(sess,tf.train.latest_checkpoint('path/of/your/.meta/file'))
# Freeze the graph
frozen_graph_def = tf.graph_util.convert_variables_to_constants(
sess,
sess.graph_def,
output_node_names)
# Save the frozen graph
with open('output_graph.pb', 'wb') as f:
f.write(frozen_graph_def.SerializeToString())
If you don't know the name of the output node or nodes, there are two ways
You can explore the graph and find the name with Netron or with console summarize_graph utility.
You can use all the nodes as output ones as shown below.
output_node_names = [n.name for n in tf.get_default_graph().as_graph_def().node]
(Note that you have to put this line just before convert_variables_to_constants call.)
But I think it's unusual situation, because if you don't know the output node, you cannot use the graph actually.
As it may be helpful for others, I also answer here after the answer on github ;-).
I think you can try something like this (with the freeze_graph script in tensorflow/python/tools) :
python freeze_graph.py --input_graph=/path/to/graph.pbtxt --input_checkpoint=/path/to/model.ckpt-22480 --input_binary=false --output_graph=/path/to/frozen_graph.pb --output_node_names="the nodes that you want to output e.g. InceptionV3/Predictions/Reshape_1 for Inception V3 "
The important flag here is --input_binary=false as the file graph.pbtxt is in text format. I think it corresponds to the required graph.pb which is the equivalent in binary format.
Concerning the output_node_names, that's really confusing for me as I still have some problems on this part but you can use the summarize_graph script in tensorflow which can take the pb or the pbtxt as an input.
Regards,
Steph
I tried the freezed_graph.py script, but the output_node_name parameter is totally confusing. Job failed.
So I tried the other one: export_inference_graph.py.
And it worked as expected!
python -u /tfPath/models/object_detection/export_inference_graph.py \
--input_type=image_tensor \
--pipeline_config_path=/your/config/path/ssd_mobilenet_v1_pets.config \
--trained_checkpoint_prefix=/your/checkpoint/path/model.ckpt-50000 \
--output_directory=/output/path
The tensorflow installation package I used is from here:
https://github.com/tensorflow/models
First, use the following code to generate the graph.pb file.
with tf.Session() as sess:
# Restore the graph
_ = tf.train.import_meta_graph(args.input)
# save graph file
g = sess.graph
gdef = g.as_graph_def()
tf.train.write_graph(gdef, ".", args.output, True)
then, use summarize graph get the output node name.
Finally, use
python freeze_graph.py --input_graph=/path/to/graph.pbtxt --input_checkpoint=/path/to/model.ckpt-22480 --input_binary=false --output_graph=/path/to/frozen_graph.pb --output_node_names="the nodes that you want to output e.g. InceptionV3/Predictions/Reshape_1 for Inception V3 "
to generate the freeze graph.
I have lots (millions) of small log files in s3 in with its name (date/time) helping to define it i.e. servername-yyyy-mm-dd-HH-MM. e.g.
s3://my_bucket/uk4039-2015-05-07-18-15.csv
s3://my_bucket/uk4039-2015-05-07-18-16.csv
s3://my_bucket/uk4039-2015-05-07-18-17.csv
s3://my_bucket/uk4039-2015-05-07-18-18.csv
...
s3://my_bucket/uk4339-2015-05-07-19-23.csv
s3://my_bucket/uk4339-2015-05-07-19-24.csv
...
etc
From EC2, using the AWS CLI, I would like to simultaneously download all files that are have the minute equal 16 for 2015, for all only server uk4339 and uk4338
Is there a clever way to do this?
Also if this is a terrible file structure in s3 to query data, I would be extremely grateful for any advice on how to set this up better.
I can put a relevant aws s3 cp ... command into a loop in a shell/bash script to sequentially download the relevant files but, was wondering if there was something more efficient.
As an added bonus I would like to row bind the results together too as one csv.
A quick example of a mock csv file can be generated in R using this line of R code
R> write.csv(data.frame(cbind(a1=rnorm(100),b1=rnorm(100),c1=rnorm(100))),file='uk4339-2015-05-07-19-24.csv',row.names=FALSE)
The csv that is created is uk4339-2015-05-07-19-24.csv. FYI, I will be importing the combined data into R at the end.
As you didn't answer my questions, nor indicate what OS you use, it is somewhat hard to make any concrete suggestions, so I will briefly suggest you use GNU Parallel to parallelise your S3 fetch requests to get around the latency.
Suppose you somehow generate a list of all the S3 files you want and put the resulting list in a file called GrabMe.txt like this
s3://my_bucket/uk4039-2015-05-07-18-15.csv
s3://my_bucket/uk4039-2015-05-07-18-16.csv
s3://my_bucket/uk4039-2015-05-07-18-17.csv
s3://my_bucket/uk4039-2015-05-07-18-18.csv
Then you can get them in parallel, say 32 at a time, like this:
parallel -j 32 echo aws s3 cp {} . < GrabMe.txt
or if you prefer reading left-to-right
cat GrabMe.txt | parallel -j 32 echo aws s3 cp {} .
You can obviously alter the number of parallel requests from 32 to any other number. At the moment, it just echoes the command it would run, but you can remove the word echo when you see how it works.
There is a good tutorial here, and Ole Tange (the author of GNU Parallel) is on SO, so we are in good company.
I'm trying to print a graph in Faunus (v0.4.0) where a node has any edges (incoming or outgoing). From the gremlin shell, I tried:
g = FaunusFactory.open('faunus.properties')
g.V.filter("{it.bothE.hasNext()}").sideEffect("{println it}")
When I do this, I get a printout of all the nodes as I expected
But without the println, I do not.
According to How do I write a for loop in gremlin?, the gremlin terminal should print this info out for me, but it does not seem to.
Is there something specific I need to do to enable the printing from the console?
Faunus and Gremlin are close to each other in terms of purpose and functionality but not identical. The filter isn't producing a side-effect, which will be written to HDFS. If you did:
g.V.filter("{it.bothE.hasNext()}").id
You could then view the list of ids matching that filter with something like:
hdfs.head('output',100)
to see the first 100 lines of the output. If you need more than just the element identifier you could do a transform to get some of the element properties in there as well. You might find these hdfs helper tips helpful.
For the AFP entry Dijkstra's Shortest Path Algorithm, both the proof outline and proof document were nonexistent *. Unfortunately, I did not find an IsaMakefile either to build those documents locally. What is the best way to get those documents?
Another question, as the Dijkstra.thy depends on a lot of other theories, is there a way to load everything faster?
*) It is fixed now.
(There seems to be something broken at AFP right now, please tell the editors about it.)
In general, you can download the sources of AFP entries and produce the documents yourself like this:
Get and unpack all AFP sources -- downloading separate entries is offered as well, but then you have to disentangle dependencies manually.
Invoke isabelle build like this:
isabelle build -d afp-2013-03-02 -o document=pdf -v Dijkstra_Shortest_Path
Here afp-2013-03-02 is the directory that was obtained by unpacking the current AFP sources.
See also the Isabelle System manual about "Isabelle sessions and build management", which is all new in Isabelle2013.
See isabelle build -b there to make things load faster, by producing persistent heap images from sessions.
The links in the AFP entry were indeed broken and should now be fixed again, sorry about that.
As Makarius writes, the AFP new uses Isabelle's new build system, i.e. has a ROOT file for each entry that can be used to check the associated theories and build the document.
Makarius' answer is pretty much the official way to do it, although I would additionally recommend setting up the AFP as a component. This gives you the following steps:
Download the AFP to e.g. ~/afp
Set it up as component e.g. by adding ~/afp to ~/.isabelle/Isabelle2013/components (see also AFP as a component)
build the entry with
isabelle afp_build Dijkstra_Shortest_Path
You can also have jEdit build the heap image for you. If the AFP is setup as a component (see the other answers for that), just start jEdit with
isabelle jedit -d '$AFP' -l Dijkstra_Shortest_Path
and jEdit will select Dijkstra_Shortest_Path as base logic and (re)build it if necessary.
If you make regular use of the AFP, it might be useful to add the AFP path by default. For this, create a file ROOTS in $ISABELLE_HOME_USER with the line $AFP in it (or add this line, if the file already exists).