ViSUSpy - Revision history

Admin: /* NumPy utils */

2020-01-28T21:06:02Z

‎NumPy utils

Admin at 21:05, 28 January 2020

2020-01-28T21:05:17Z

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Admin: /* Read from IDX file */

2019-03-06T17:41:38Z

‎Read from IDX file

Admin: /* Write data in IDX format */

2019-03-06T17:40:16Z

‎Write data in IDX format

Admin: /* Write data to an IDX file */

2018-03-09T17:41:05Z

‎Write data to an IDX file

Admin: /* NumPy utils */

2018-03-09T17:40:08Z

‎NumPy utils

Admin: /* Library imports */

2018-03-09T17:35:28Z

‎Library imports

Admin: /* Library imports */

2018-03-09T17:32:20Z

‎Library imports

Admin: /* Write data to an IDX file */

2018-03-09T17:26:36Z

‎Write data to an IDX file

Admin: /* Read from IDX file */

2018-03-09T17:16:44Z

‎Read from IDX file

@@ Line 27: / Line 27: @@
 </syntaxhighlight>
-=== NumPy utils ===
+=== Read data into a NumPy array ===
 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.

@@ Line 122: / Line 122: @@
 # 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()
+box=dataset.getBox()
 # get the default field of a dataset
-field=dataset.get().getDefaultField()
+field=dataset.getDefaultField()
 #create access
-access=dataset.get().createAccess()
+access=dataset.createAccess()
 # here we read the datasets slice by slice
@@ Line 137: / Line 137: @@
    # define a read query
-   query=QueryPtr(Query(dataset.get(),ord('r')))
+   query=Query(dataset,ord('r'))
    # set the box for the query
-   query.get().position=Position(slice_box)
+   query.position=Position(slice_box)
-   self.assertTrue(dataset.get().beginQuery(query))
+   self.assertTrue(dataset.beginQuery(query))
    # check the size of the output of the query
-   print("query size", query.get().nsamples.innerProduct())
+   print("query size", query.nsamples.innerProduct())
    # execute query
-   self.assertTrue(dataset.get().executeQuery(access,query))
+   self.assertTrue(dataset.executeQuery(access,query))
    # convert output buffer to a numpy array
-   my_numpy_array=convertToNumPyArray(query.get().buffer)
+   my_numpy_array=toNumPy(query.buffer)
 IdxModule.detach()
 </syntaxhighlight>

@@ Line 71: / Line 71: @@
 # create access to write the data
-access=dataset.get().createAccess()
+access=dataset.createAccess()
 # write data slice by slice
@@ Line 77: / Line 77: @@
 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)
+   slice_box=dataset.getBox().getZSlab(Z,Z+1)
    # create write query
-   query=QueryPtr(Query(dataset.get(),ord('w')))
+   query=Query(dataset,ord('w'))
    # set query box
-   query.get().position=Position(slice_box)
+   query.position=Position(slice_box)
    # initialize query
-   self.assertTrue(dataset.get().beginQuery(query))
+   self.assertTrue(dataset.beginQuery(query))
    # check if size of the query is equal to the dimension of our dataset
-   self.assertEqual(query.get().nsamples.innerProduct(),16*16)
+   self.assertEqual(query.nsamples.innerProduct(),16*16)
    # create a Visus Array to store the data
-   buffer=Array(query.get().nsamples,query.get().field.dtype)
+   buffer=Array(query.nsamples,query.field.dtype)
    # set the output buffer of the query to the array we just created
-   query.get().buffer=buffer
+   query.buffer=buffer
    # convert our buffer to a numpy array
-   fill=convertToNumPyArray(buffer)
+   fill=toNumPy(buffer)
    # fill up the array with some values
@@ Line 104: / Line 104: @@
 # execute query
-success = dataset.get().executeQuery(access,query)
+success = dataset.executeQuery(access,query)
 IdxModule.detach()

@@ Line 41: / Line 41: @@
 </syntaxhighlight>
-== Write data to an IDX file ==
+== Write data in IDX format ==
 <syntaxhighlight lang="python" line='line'>

@@ Line 30: / Line 30: @@
 <syntaxhighlight lang="python">
 import numpy
 </syntaxhighlight>