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Data access and Vizualisation

Data access

Here is the overall high level interface of Lima2. Client such as Flint control the acquisition and access the data using the Client API that manages the distributed nature of data receivers. The Client API knows where to get the data for a given frame.

flowchart BT
    flint(FLINT)
    api(Client API) --- flint
    cds(Control DS) --- api
    rds1(Receiver DS #1) --- api
    rdsn(Receiver DS #n) --- api

Data in the processing graph are made available using a circular buffer node that can be inserted anywhere in the processing graph:

flowchart LR
    src(Source) --> proc1(OpenCL - Energy Reconstruction + pyFAI) --> buf1{{Circular buffer for sparse data}}
    src --> proc2(CPU - Image reconstruction) --> buf2{{Circular buffer for dense data}} --> proc3(ROI counters) --> buf3{{Circular buffer for ROI counters}}

The receiver API gives read access to the cyclic buffer -which size is configurable. A Tango DS is used to serve this data.

Tango

Reusing the same DevEncoded for images called DATA_ARRAY:

    # The DATA_ARRAY definition
    #struct {
    #unsigned int Magic= 0x44544159;
    #unsigned short Version;
    #unsigned  short HeaderLength;
    #DataArrayCategory Category;
    #DataArrayType DataType;
    #unsigned short DataEndianness;
    #unsigned short NbDim;
    #unsigned short Dim[8]
    #unsigned int DimStep[8]
    #} DataArrayHeaderStruct;

    # With
    DataArrayVersion = 3
    DataArrayPackStr = '<IHHIIHHHHHHHHIIIIIIII'
    DataArrayMagic = struct.unpack('>I', b'DTAY')[0]	# 0x44544159
    DataArrayHeaderLen = 64
    DataArrayMaxNbDim = 6

DATA_ARRAY v3.0

New catergories for sparse images are introduced:

Category NbDim
ScalarStack 1
Spectrum 1
Image 2
SparseImage 3
SpectrumStack 2
ImageStack 3
SparseImageStack 4

For SparseImageStack , the dimensions are:

   dims[0] = nb pixels
   dims[1] = width
   dims[2] = height
   dims[3] = nb images (for stacks)

The data block (or bytes) is the concatenation of

Category Type Size
Pixel value ImageType2DataArrayType nb pixels
Padding to 32 bits
Pixel index Int32 nb pixels
Frame index Int32 nb frames

Vizualisation

GUI - Flint

Live display of BLISS scans

Flint listens to scan data source to know if there’s something to display.

Poll the image counter of Lima. Call read_image according to the refresh rate.

Users data plotting

New user plotting are introduced:

  • Image plot of the reduced data (without background). The Lima Client API would do the densification.
  • Time curve plot with the number of peaks over time.

Specific options

Display images with a number of peaks higher than a given threshold.

GUI - Web beam viewer

Lima web server used to display camera image with beam position (bpm) statistics built on top of the Tango DS.