Admin: Created page with "ViSUSpy is a library that allows the user to use the ViSUS framework from python. In the following sections we provide some examples on how to use it. == Library imports ==..."

2019-03-05T00:31:20Z

Created page with "ViSUSpy is a library that allows the user to use the ViSUS framework from python. In the following sections we provide some examples on how to use it. == Library imports ==..."

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ViSUSpy is a library that allows the user to use the ViSUS framework from python.

In the following sections we provide some examples on how to use it.

== Library imports ==

To import and use the library in your python application you need to use the following imports:

<syntaxhighlight lang="python">
from visuspy import *
from VisusKernelPy import *
from VisusIdxPy import *
from VisusDbPy import *
</syntaxhighlight>

These modules allow the basic interactions with IDX datasets, which can be either local or remote (served by a [[ViSUS Server]]).

'''Important''': your code that interacts with IDX datasets has always to attach the ''IdxModule'' first, as following:

<syntaxhighlight lang="python">
IdxModule.attach()
# your program code
IdxModule.detach()
</syntaxhighlight>

=== NumPy utils ===

In order to facilitate interoperation with existing python scientific libraries as NumPy we provide two function to convert data arrays from/to ViSUS Array an NumPy array.

<syntaxhighlight lang="python">
import numpy

# convert our buffer to a numpy array.
# This is useful when we want to read data from
# and IDX dataset and use this array with other libraries
numpy_array=convertToNumPyArray(in_visus_array)

# convert a numpy array to a ViSUS array
visus_array = convertToVisusArray(numpy_array)

</syntaxhighlight>

== Write data in IDX format ==

<syntaxhighlight lang="python" line='line'>
IdxModule.attach()

# define a box which defines the bounding box
# of the grid where our data will be stored
# a box is defined by two points (p1 and p2)
# which define the two opposite corners of the box
# in this case the box has size 16x16x16
dataset_box=NdBox(NdPoint(0,0,0),NdPoint.one(16,16,16))

# create and IDX file where to to store the data
idxfile=IdxFile();

# set dataset box
idxfile.box=NdBox(dataset_box)

# add integer field to the dataset
idxfile.fields.push_back(Field("myfield",DType.fromString("uint32")))

# save the metadata on disk (no data are saved yet)
bSaved=idxfile.save(self.filename)
self.assertTrue(bSaved)

# load the dataset we just created
dataset=Dataset.loadDataset(self.filename)
self.assertIsNotNone(dataset)

# create access to write the data
access=dataset.get().createAccess()

# write data slice by slice
sampleid=0
for Z in range(0,16):
# create box to hold the Z slice of the data
slice_box=dataset.get().getBox().getZSlab(Z,Z+1)

# create write query
query=QueryPtr(Query(dataset.get(),ord('w')))
# set query box
query.get().position=Position(slice_box)

# initialize query
self.assertTrue(dataset.get().beginQuery(query))
# check if size of the query is equal to the dimension of our dataset
self.assertEqual(query.get().nsamples.innerProduct(),16*16)

# create a Visus Array to store the data
buffer=Array(query.get().nsamples,query.get().field.dtype)
# set the output buffer of the query to the array we just created
query.get().buffer=buffer

# convert our buffer to a numpy array
fill=convertToNumPyArray(buffer)

# fill up the array with some values
for Y in range(16):
for X in range(16):
fill[Y,X]=sampleid
sampleid+=1

# execute query
success = dataset.get().executeQuery(access,query)

IdxModule.detach()
</syntaxhighlight>

== Read from IDX file ==

<syntaxhighlight lang="python" line='line'>
IdxModule.attach()

# open an IDX dataset
dataset=Dataset_loadDataset(self.filename)
# check it is valid
self.assertIsNotNone(dataset)

# get the bounding box of the dataset
# the box is defined by a set of 2 points (p1 and p2)
# which define the two corners of a bounding box
box=dataset.get().getBox()

# get the default field of a dataset
field=dataset.get().getDefaultField()

#create access
access=dataset.get().createAccess()

# here we read the datasets slice by slice
# making box queries
sampleid=0
for Z in range(0,16):
slice_box=box.getZSlab(Z,Z+1)

# define a read query
query=QueryPtr(Query(dataset.get(),ord('r')))
# set the box for the query
query.get().position=Position(slice_box)

self.assertTrue(dataset.get().beginQuery(query))
# check the size of the output of the query
print("query size", query.get().nsamples.innerProduct())
# execute query
self.assertTrue(dataset.get().executeQuery(access,query))

# convert output buffer to a numpy array
my_numpy_array=convertToNumPyArray(query.get().buffer)

IdxModule.detach()
</syntaxhighlight>

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