Ada + Machine Learning (Python Framework) - machine-learning

I'm trying to write a simple machine learning application in Ada, and also trying to find a good framework to use. My knowledge of one thing is extremely minimal, and of the other is somewhat minimal.
There are several nifty machine learning frameworks out there, and I'd like to leverage one for use with an Ada program, but I guess I'm just...at a loss. Can I use an existing framework written in Python, for instance and wrap (or I guess, bind?) the API calls in Ada? Should I just pass off the scripting capabilities? I'm trying to figure it out.
Case in point: Scikit (sklearn)
https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html#
This does some neat stuff, and I'd like to be able to leverage this, but with an Ada program. Does anyone have advice from a similar experience?
I am just researching, so I have tried finding information.
http://www.inspirel.com/articles/Ada_Python_Binding.html
https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html#

The inspirel solution is based on python2.7. If you're using anything from python3.5 onwards a few mods need to be made. On Linux, changing to say python 3.7, you'd just change
--for Default_Switches ("Ada") use ("-lpython2.7");
for Default_Switches ("Ada") use ("-lpython3.7");
but on windows, the libraries aren't dumped in a community lib so gnat doesn't know where to find them. All the packages are kept separately. The -L has to be added to tell the linker where to find the library. Alternatively, you can use for lib_dir. In my case, I did a non-admin install of python, so it looks something like
for Default_Switches ("Ada") use ("-L\Users\StdUser\AppData\Local\Programs\Python\Python37-32\libs", "-lpython37");
Note that on windows, the library is called python37: not python3.7. Use gprbuild instead of gnatmake -p, which has been deprecated. If you do all your mods correctly
gprbuild ada_main.gpr
should give you an executable in obj\ada_main.exe if it builds. If a later version of python is used, some edits need to be made
python_module.py
#print 'Hello from Python module'
print('Hello from Python module')
#print 'Python adding:', a, '+', b
print('Python adding:', a, '+', b)
ada_main.adb
-- Python.Execute_String("print 'Hello from Python!'");
Python.Execute_String("print('Hello from Python!')");
Some routines have been deprecated so the linkage has to change
python.adb
--pragma Import(C, PyInt_AsLong, "PyInt_AsLong");
pragma Import(C, PyInt_AsLong, "PyLong_AsLong");
--pragma Import(C, PyString_FromString, PyString_FromString");
pragma Import(C, PyString_FromString, "PyUnicode_FromString");
Running the build and executable should give
C:\Users\StdUser\My Documents\ada-python>gprbuild ada_main.gpr
Compile
[Ada] ada_main.adb
Bind
[gprbind] ada_main.bexch
[Ada] ada_main.ali
Link
[link] ada_main.adb
C:\Users\StdUser\My Documents\ada-python>obj\ada_main.exe
executing Python directly from Ada:
Hello from Python!
loading external Python module and calling functions from that module:
Hello from Python module!
asking Python to add two integers:
Python adding: 10 + 2
Ada got result from Python: 12
we can try other operations, too:
subtract: 8
multiply: 20
divide : 5
Remember to put the pythonxx.dll somewhere on your path otherwise it won't be able to find the library when it starts executing.

Related

DiagramBuilder: Cannot operate on ports of System plant until it has been registered using AddSystem

I have an issue working with DiagramBuilder and ManipulationStation classes.
It appears to me, that c++ API and the python bindings work differently in my case.
C++ API behaves as expected, while the python bindings result in the runtime error:
DiagramBuilder: Cannot operate on ports of System plant until it has been registered using AddSystem
How I use C++ API
In one of the ManipulationStation::Setup...() methods I inject a block of code, that adds an extra manipuland
const std::string sdf_path = FindResourceOrThrow("drake/examples/manipulation_station/models/bolt_n_nut.sdf");
RigidTransform<double> X_WC(RotationMatrix<double>::Identity(), Vector3d(0.0, -0.3, 0.1));
bolt_n_nut_ = internal::AddAndWeldModelFrom(sdf_path, "nut_and_bolt", lant_->world_frame(), "bolt", X_WC, plant_);
I inject another block of code into the method ManipulationStation::Finalize:
auto zero_torque = builder.template AddSystem<systems::ConstantVectorSource<double>>(Eigen::VectorXd::Zero(plant_->num_velocities(bolt_n_nut_)));
builder.Connect(zero_torque->get_output_port(), plant_->get_actuation_input_port(bolt_n_nut_));
With these changes, the simulation runs as expected.
How I use python bindings
plant = station.get_multibody_plant()
manipuland_path = get_manipuland_resource_path()
bolt_with_nut = Parser(plant=plant).AddModelFromFile(manipuland_path)
X_WC = RigidTransform(RotationMatrix.Identity(), [0.0, -0.3, 0.1])
plant.WeldFrames(plant.world_frame(), plant.GetFrameByName('bolt', bolt_with_nut), X_WC)
...
station.Finalize()
zero_torque = builder.AddSystem(ConstantValueSource(AbstractValue.Make([0.])))
builder.Connect(zero_torque.get_output_port(), plant.get_actuation_input_port(bolt_with_nut_model))
This triggers a RuntimeError with a message as above; The port, which causes this error is nut_and_bolt_actuation.
My vague understanding of the problem is the (in) visibility of nut_and_bolt System, due to having two distinct DiagramBuilders in a process: 1) a one is inside ManipulationStation 2) another is in the python code, that instantiates this ManipulationStation object.
Using ManipulationStation via python bindings is a preference for me, because that way I would've avoided depending on a custom build of drake library.
Thanks for your insight!
I agree with your assessment: you have two different DiagramBuilder objects here. This does not have anything to due with C++ or Python; the ManipulationStation is itself a Diagram (created using its own DiagramBuilder), and you have a second DiagramBuilder (in either c++ or python) that is connecting the ManipulationStation together with other elements. You are trying to connect a system that is in the external diagram to a port that is in the internal diagram, but is not exposed.
The solution would be to have the ManipulationStation diagram expose the extra nut and bolt actuation port so that you can connect to it from the second builder.
If you prefer Python, I've switched my course to using a completely python version of the manipulation station. I find this version is much easier to adapt to different student projects. (To be clear, the setup is in python, but at simulation time all of the elements are c++ and it doesn't call back to python; so the performance is almost identical.)

Pointcloud Visualization in Drake Visualizer in Python

I would like to visualize pointcloud in drake-visualizer using python binding.
I imitated how to publish images through lcm from here, and checked out these two issues (14985, 14991). The snippet is as follows :
point_cloud_to_lcm_point_cloud = builder.AddSystem(PointCloudToLcm())
point_cloud_to_lcm_point_cloud.set_name('pointcloud_converter')
builder.Connect(
station.GetOutputPort('camera0_point_cloud'),
point_cloud_to_lcm_point_cloud.get_input_port()
)
point_cloud_lcm_publisher = builder.AddSystem(
LcmPublisherSystem.Make(
channel="DRAKE_POINT_CLOUD_camera0",
lcm_type=lcmt_point_cloud,
lcm=None,
publish_period=0.2,
# use_cpp_serializer=True
)
)
point_cloud_lcm_publisher.set_name('point_cloud_publisher')
builder.Connect(
point_cloud_to_lcm_point_cloud.get_output_port(),
point_cloud_lcm_publisher.get_input_port()
)
However, I got the following runtime error:
RuntimeError: DiagramBuilder::Connect: Mismatched value types while connecting output port lcmt_point_cloud of System pointcloud_converter (type drake::lcmt_point_cloud) to input port lcm_message of System point_cloud_publisher (type drake::pydrake::Object)
When I set 'use_cpp_serializer=True', the error becomes
LcmPublisherSystem.Make(
File "/opt/drake/lib/python3.8/site-packages/pydrake/systems/_lcm_extra.py", line 71, in _make_lcm_publisher
serializer = _Serializer_[lcm_type]()
File "/opt/drake/lib/python3.8/site-packages/pydrake/common/cpp_template.py", line 90, in __getitem__
return self.get_instantiation(param)[0]
File "/opt/drake/lib/python3.8/site-packages/pydrake/common/cpp_template.py", line 159, in get_instantiation
raise RuntimeError("Invalid instantiation: {}".format(
RuntimeError: Invalid instantiation: _Serializer_[lcmt_point_cloud]
I saw the cpp example here, so maybe this issue is specific to python binding.
I also saw this python example, but thought using 'PointCloudToLcm' might be more convenient.
P.S.
I am aware of the development in recent commits on MeshcatVisualizerCpp and MeshcatPointCloudVisualizerCpp, but I am still on the drake-dev stable build 0.35.0-1 and want to stay on drake visualizer until the meshcat c++ is more mature.
The old version in pydrake.systems.meshcat_visualizer.MeshcatVisualizer is a bit too slow on my current use-case (multiple objects drop). I can visualize the pointcloud with this visualization setting, but it took too much machine resources.
Only the message types that are specifically bound in lcm_py_bind_cpp_serializers.cc can be used on an LCM message input/output port connection between C++ and Python. For all other LCM message types, the input/output port connection must be from a Python system to a Python system or a C++ System to a C++ System.
The lcmt_image_array is listed there, but not the lcmt_point_cloud.
If you're stuck using Drake's v0.35.0 capabilities, then I don't see any great solutions. Some options:
(1) Write your own PointCloudToLcm system in Python (by re-working the C++ code into Python, possibly with a narrower set of supported features / channels for simplicity).
(2) Write your own small C++ helper function MakePointCloudPublisherSystem(...) that calls LcmPublisherSystem::Make<lcmt_point_cloud> function in C++, and bind it into Python. Then your Python code can call MakePointCloudPublisherSystem() and successfully connect that to the existing C++ PointCloudToLcm.

PyCharm: Unresolved reference 'com'

I've been experimenting with PyCharm in conjunction with LO and UNO for some time (win10).
What I don't understand:
Why do I get the error Unresolved reference 'com' from PyCharm when I enter the code in editor, but everything seems to be OK, when I run the script with PyCharm or entered in console?
Example:
import uno
from com.sun.star.awt import Point
p = Point(100, 200)
print(p)
=> (com.sun.star.awt.Point){ X = (long)0x64, Y = (long)0xc8 }
What I would expect would be a relationship between the UNO interfaces com.sun.star.awt and Python so that I can use Intellisense/autocomplete (for example) when entering the code from com.sun.star.awt import Point in PyCharm'.
What I know is that all interfaces are described in the IDL files (SDK). I thought it must be possible to define a so-called stub/mock "package" that enables me to do this. Unfortunately, this request is beyond my capabilities at the moment. The attempt to integrate the idl structure from sdk is only inadequate (path structure only).
Are there any ready-made solutions? (which I doubt - intensively searched all sources)
Do I have to live with it now, or which approach would go in the right direction (I love intellisense)? - Maybe I think too complicated?

Is it possible to run a Python program within a Java "GraalVM" program?

From the GraalVM examples, they have code like this to run a single line of Python code:
context.eval("python", "\nprint('Hello polyglot world Python!');");
Yes that works fine in a Java program.
I can also run a Python program from the command line using the "graalpython" program.
My question is how do I run a python program from the Java example I mentioned above?
context.eval("python", "\nprint('Hello polyglot world Python!');");
I tried using the "file:" argument, but that didn't work or I'm doing something wrong.
For example, this did not work:
context.eval("python", "file: /path_to_python/test.py");
This line of code gives me:
Original Internal Error:
java.lang.RuntimeException: not implemented
So, maybe that answers my question, but I have to believe you can run a python script from a GRAAL program like you can a single line of code. Hence, this posting.
--
Is running a python program from within a Java program using graal "eval" supported? If so, I would very much appreciate an example of usage.
Thanks very much.
You need to build a Source object in order to eval a file:
File file = new File("/path_to_python/test.py");
Source source = Source.newBuilder("python", file).build();
context.eval(source);

is that possible to do igblast(Analyze immunoglobulin (Ig) sequences) with python/biopython

I'm fresh to python/biopython and tried blast using biopython like this:
from Bio.Blast import NCBIWWW
fasta_string = open("C:\\xxxx\\xxxx\\xxxx\\abc.fasta").read()
result_handle = NCBIWWW.qblast("blastp", "nr", fasta_string)
print result_handle.read()
I was wondering if it is possible to run igblast using biopython. I have searched for this but it seems no one is really doing this.
I haven't tried them, but I have found:
pyigblast.
PyIgBlast - Open source Parser to call IgBlast and parse results for
high-throughput sequencing. Uses Python multi-processing to get around
bottlenecks of IgBlast multi-threading. Parses blast output to
deliminated files (csv,json) for uploading to databases. Can connect
directly with mysql and mongo instances to insert directly.
The code uses Python 2.7 and BioPython.
PyIR
Immunoglobulin and T-Cell receptor rearrangement software. A Python wrapper for IgBLAST that scales to allow for the parallel processing of millions of reads on shared memory computers. All output is stored in a convenient JSON format.
The code uses Python 3.6 and BioPython.
Both tools use a locally installed igblastn executable. You can install igblastn locally with conda install igblast.

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