nd2 0.5.1

Yet another nd2 (Nikon NIS Elements) file reader

nd2

Yet another .nd2 (Nikon NIS Elements) file reader.

This reader provides a Cython wrapper for the official Nikon SDK. (The actual reading of image frames, however, uses a direct memmap approach, instead of the SDK, for performance reasons and to avoid occasional segfaults from the SDK.)

Features good metadata retrieval, and direct to_dask and to_xarray options for lazy and/or annotated arrays.

This library is tested against many nd2 files with the goal of maximizing compatibility and data extraction. (If you find an nd2 file that fails in some way, please open an issue with the file!)

install

pip install nd2

or from conda:

conda install -c conda-forge nd2

extras

Legacy nd2 (JPEG2000) files are also supported, but require imagecodecs. To install with support for these files use:

pip install nd2[legacy]

usage and API

import nd2
import numpy as np

my_array = nd2.imread('some_file.nd2')                          # read to numpy array
my_array = nd2.imread('some_file.nd2', dask=True)               # read to dask array
my_array = nd2.imread('some_file.nd2', xarray=True)             # read to xarray
my_array = nd2.imread('some_file.nd2', xarray=True, dask=True)  # read file to dask-xarray

# or open a file with nd2.ND2File
f = nd2.ND2File('some_file.nd2')

# (you can also use nd2.ND2File() as a context manager)
with nd2.ND2File('some_file.nd2') as ndfile:
    print(ndfile.metadata)
    ...


# ATTRIBUTES:   # example output
f.path          # 'some_file.nd2'
f.shape         # (10, 2, 256, 256)
f.ndim          # 4
f.dtype         # np.dtype('uint16')
f.size          # 1310720  (total voxel elements)
f.sizes         # {'T': 10, 'C': 2, 'Y': 256, 'X': 256}
f.is_rgb        # False (whether the file is rgb)
                # if the file is RGB, `f.sizes` will have
                # an additional {'S': 3} component

# ARRAY OUTPUTS
f.asarray()         # in-memory np.ndarray - or use np.asarray(f)
f.to_dask()         # delayed dask.array.Array
f.to_xarray()       # in-memory xarray.DataArray, with labeled axes/coords
f.to_xarray(delayed=True)   # delayed xarray.DataArray

                    # see below for examples of these structures
# METADATA          # returns instance of ...
f.attributes        # nd2.structures.Attributes
f.metadata          # nd2.structures.Metadata
f.frame_metadata(0) # nd2.structures.FrameMetadata (frame-specific meta)
f.experiment        # List[nd2.structures.ExpLoop]
f.rois              # Dict[int, nd2.structures.ROI]
f.voxel_size()      # VoxelSize(x=0.65, y=0.65, z=1.0)
f.text_info         # dict of misc info

f.binary_data       # any binary masks stored in the file.  See below.
f.custom_data       # bits of unstructured metadata that start with CustomData
f.recorded_data     # returns a dict of lists (passable to pandas.DataFrame) that
                    # the tabular "Recorded Data" view from in NIS Elements/Viewer
                    # with info for each frame in the experiment.

# allll the metadata we can find...
# no attempt made to standardize or parse it
# look in here if you're searching for metdata that isn't exposed in the above
f.unstructured_metadata()

f.close()           # don't forget to close when not using a contet manager!
f.closed            # boolean, whether the file is closed

Metadata structures

These follow the structure of the nikon SDK outputs (where relevant). Here are some example outputs

attributes

Attributes(
    bitsPerComponentInMemory=16,
    bitsPerComponentSignificant=16,
    componentCount=2,
    heightPx=32,
    pixelDataType='unsigned',
    sequenceCount=60,
    widthBytes=128,
    widthPx=32,
    compressionLevel=None,
    compressionType=None,
    tileHeightPx=None,
    tileWidthPx=None,
    channelCount=2
)

metadata

Note: the metadata for legacy (JPEG2000) files will be a plain unstructured dict.

Metadata(
    contents=Contents(channelCount=2, frameCount=60),
    channels=[
        Channel(
            channel=ChannelMeta(name='Widefield Green', index=0, colorRGB=65371, emissionLambdaNm=535.0, excitationLambdaNm=None),
            loops=LoopIndices(NETimeLoop=None, TimeLoop=0, XYPosLoop=1, ZStackLoop=2),
            microscope=Microscope(
                objectiveMagnification=10.0,
                objectiveName='Plan Fluor 10x Ph1 DLL',
                objectiveNumericalAperture=0.3,
                zoomMagnification=1.0,
                immersionRefractiveIndex=1.0,
                projectiveMagnification=None,
                pinholeDiameterUm=None,
                modalityFlags=['fluorescence']
            ),
            volume=Volume(
                axesCalibrated=[True, True, True],
                axesCalibration=[0.652452890023035, 0.652452890023035, 1.0],
                axesInterpretation=(
                    <AxisInterpretation.distance: 'distance'>,
                    <AxisInterpretation.distance: 'distance'>,
                    <AxisInterpretation.distance: 'distance'>
                ),
                bitsPerComponentInMemory=16,
                bitsPerComponentSignificant=16,
                cameraTransformationMatrix=[-0.9998932296054086, -0.014612644841559427, 0.014612644841559427, -0.9998932296054086],
                componentCount=1,
                componentDataType='unsigned',
                voxelCount=[32, 32, 5],
                componentMaxima=[0.0],
                componentMinima=[0.0],
                pixelToStageTransformationMatrix=None
            )
        ),
        Channel(
            channel=ChannelMeta(name='Widefield Red', index=1, colorRGB=22015, emissionLambdaNm=620.0, excitationLambdaNm=None),
            loops=LoopIndices(NETimeLoop=None, TimeLoop=0, XYPosLoop=1, ZStackLoop=2),
            microscope=Microscope(
                objectiveMagnification=10.0,
                objectiveName='Plan Fluor 10x Ph1 DLL',
                objectiveNumericalAperture=0.3,
                zoomMagnification=1.0,
                immersionRefractiveIndex=1.0,
                projectiveMagnification=None,
                pinholeDiameterUm=None,
                modalityFlags=['fluorescence']
            ),
            volume=Volume(
                axesCalibrated=[True, True, True],
                axesCalibration=[0.652452890023035, 0.652452890023035, 1.0],
                axesInterpretation=(
                    <AxisInterpretation.distance: 'distance'>,
                    <AxisInterpretation.distance: 'distance'>,
                    <AxisInterpretation.distance: 'distance'>
                ),
                bitsPerComponentInMemory=16,
                bitsPerComponentSignificant=16,
                cameraTransformationMatrix=[-0.9998932296054086, -0.014612644841559427, 0.014612644841559427, -0.9998932296054086],
                componentCount=1,
                componentDataType='unsigned',
                voxelCount=[32, 32, 5],
                componentMaxima=[0.0],
                componentMinima=[0.0],
                pixelToStageTransformationMatrix=None
            )
        )
    ]
)

experiment

[
    TimeLoop(
        count=3,
        nestingLevel=0,
        parameters=TimeLoopParams(
            startMs=0.0,
            periodMs=1.0,
            durationMs=0.0,
            periodDiff=PeriodDiff(avg=16278.339965820312, max=16411.849853515625, min=16144.830078125)
        ),
        type='TimeLoop'
    ),
    XYPosLoop(
        count=4,
        nestingLevel=1,
        parameters=XYPosLoopParams(
            isSettingZ=True,
            points=[
                Position(stagePositionUm=[26950.2, -1801.6000000000001, 498.46000000000004], pfsOffset=None, name=None),
                Position(stagePositionUm=[31452.2, -1801.6000000000001, 670.7], pfsOffset=None, name=None),
                Position(stagePositionUm=[35234.3, 2116.4, 664.08], pfsOffset=None, name=None),
                Position(stagePositionUm=[40642.9, -3585.1000000000004, 555.12], pfsOffset=None, name=None)
            ]
        ),
        type='XYPosLoop'
    ),
    ZStackLoop(count=5, nestingLevel=2, parameters=ZStackLoopParams(homeIndex=2, stepUm=1.0, bottomToTop=True, deviceName='Ti2 ZDrive'), type='ZStackLoop')
]

rois

ROIs found in the metadata are available at ND2File.rois, which is a dict of nd2.structures.ROI objects, keyed by the ROI ID:

{
    1: ROI(
        id=1,
        info=RoiInfo(
            shapeType=<RoiShapeType.Rectangle: 3>,
            interpType=<InterpType.StimulationROI: 4>,
            cookie=1,
            color=255,
            label='',
            stimulationGroup=0,
            scope=1,
            appData=0,
            multiFrame=False,
            locked=False,
            compCount=2,
            bpc=16,
            autodetected=False,
            gradientStimulation=False,
            gradientStimulationBitDepth=0,
            gradientStimulationLo=0.0,
            gradientStimulationHi=0.0
        ),
        guid='{87190352-9B32-46E4-8297-C46621C1E1EF}',
        animParams=[
            AnimParam(
                timeMs=0.0,
                enabled=1,
                centerX=-0.4228425369685782,
                centerY=-0.5194951478743071,
                centerZ=0.0,
                rotationZ=0.0,
                boxShape=BoxShape(
                    sizeX=0.21256931608133062,
                    sizeY=0.21441774491682075,
                    sizeZ=0.0
                ),
                extrudedShape=ExtrudedShape(sizeZ=0, basePoints=[])
            )
        ]
    ),
    ...
}

text_info

{
    'capturing': 'Flash4.0, SN:101412\r\nSample 1:\r\n  Exposure: 100 ms\r\n  Binning: 1x1\r\n  Scan Mode: Fast\r\nSample 2:\r\n  Exposure: 100 ms\r\n  Binning: 1x1\r\n  Scan Mode: Fast',
    'date': '9/28/2021  9:41:27 AM',
    'description': 'Metadata:\r\nDimensions: T(3) x XY(4) x λ(2) x Z(5)\r\nCamera Name: Flash4.0, SN:101412\r\nNumerical Aperture: 0.3\r\nRefractive Index: 1\r\nNumber of Picture Planes: 2\r\nPlane #1:\r\n Name: Widefield Green\r\n Component Count: 1\r\n Modality: Widefield Fluorescence\r\n Camera Settings:   Exposure: 100 ms\r\n  Binning: 1x1\r\n  Scan Mode: Fast\r\n Microscope Settings:   Nikon Ti2, FilterChanger(Turret-Lo): 3 (FITC)\r\n  Nikon Ti2, Shutter(FL-Lo): Open\r\n  Nikon Ti2, Shutter(DIA LED): Closed\r\n  Nikon Ti2, Illuminator(DIA): Off\r\n  Nikon Ti2, Illuminator(DIA) Iris intensity: 3.0\r\n  Analyzer Slider: Extracted\r\n  Analyzer Cube: Extracted\r\n  Condenser: 1 (Shutter)\r\n  PFS, state: On\r\n  PFS, offset: 7959\r\n  PFS, mirror: Inserted\r\n  PFS, Dish Type: Glass\r\n  Zoom: 1.00x\r\n  Sola, Shutter(Sola): Active\r\n  Sola, Illuminator(Sola) Voltage: 100.0\r\nPlane #2:\r\n Name: Widefield Red\r\n Component Count: 1\r\n Modality: Widefield Fluorescence\r\n Camera Settings:   Exposure: 100 ms\r\n  Binning: 1x1\r\n  Scan Mode: Fast\r\n Microscope Settings:   Nikon Ti2, FilterChanger(Turret-Lo): 4 (TRITC)\r\n  Nikon Ti2, Shutter(FL-Lo): Open\r\n  Nikon Ti2, Shutter(DIA LED): Closed\r\n  Nikon Ti2, Illuminator(DIA): Off\r\n  Nikon Ti2, Illuminator(DIA) Iris intensity: 1.5\r\n  Analyzer Slider: Extracted\r\n  Analyzer Cube: Extracted\r\n  Condenser: 1 (Shutter)\r\n  PFS, state: On\r\n  PFS, offset: 7959\r\n  PFS, mirror: Inserted\r\n  PFS, Dish Type: Glass\r\n  Zoom: 1.00x\r\n  Sola, Shutter(Sola): Active\r\n  Sola, Illuminator(Sola) Voltage: 100.0\r\nTime Loop: 3\r\n- Equidistant (Period 1 ms)\r\nZ Stack Loop: 5\r\n- Step: 1 µm\r\n- Device: Ti2 ZDrive',
    'optics': 'Plan Fluor 10x Ph1 DLL'
}

custom_data

No attempt is made to parse this data. It will vary from file to file, but you may find something useful here:

{
    'StreamDataV1_0': {
        'Vector_StreamAnalogIn': '',
        'Vector_StreamDigitalIn': '',
        'Vector_AnalogIn': '',
        'Vector_DigitalIn': '',
        'Vector_Other': '',
        'Vector_StreamAnalogOut': '',
        'Vector_StreamDigitalOut': '',
        'Vector_AnalogOut': '',
        'Vector_DigitalOut': ''
    },
    'NDControlV1_0': {
        'NDControl': {
            'LoopState': {'no_name': [529, 529, 529, 529, 529]},
            'PlayFPS': {'no_name': [20.0, 20.0, 0.0, 20.0, 0.0]},
            'LoopSize': {'no_name': [3, 4, 0, 5, 0]},
            'LoopPosition': {'no_name': [2, 3, 0, 4, 0]},
            'LoopSelection': {'no_name': [b'AAAA', b'AAAAAA==', b'', b'AAAAAAA=', b'']},
            'LoopRangeSelection': {'no_name': [b'AQEB', b'AQEBAQ==', b'', b'AQEBAQE=', b'']},
            'LoopEventSelection': {'no_name': [b'AAAA', b'AAAAAA==', b'', b'AAAAAAA=', b'']},
            'FramesInRange': '',
            'LoopStep': {'no_name': [0, 0, 0, 0, 0]},
            'UserEventType': 2,
            'SelectionStyle': 0,
            'FramesBefore': 2,
            'FramesAfter': 1,
            'TimeBefore': 1.0,
            'TimeAfter': 1.0
        }
    },
    'LUTDataV1_0': {
        'ViewLut': True,
        'LutParam': {
            'Gradient': 0,
            'GradientBrightField': 0,
            'MinSrc': 0,
            'MaxSrc': 65535,
            'GammaSrc': 1.0,
            'MinDst': 0,
            'MaxDst': 65535,
            'ColorSpace': 4,
            'Representation': 0,
            'LutComponentCount': 2,
            'GroupCount': 1,
            'CompLutParam': {
                '00': {'MinSrc': [82, 0.0], 'MaxSrc': [113, 1.0], 'GammaSrc': 1.0, 'MinDst': 0, 'MaxDst': 65535, 'Group': 0},
                '01': {'MinSrc': [82, 0.0], 'MaxSrc': [114, 1.0], 'GammaSrc': 1.0, 'MinDst': 0, 'MaxDst': 65535, 'Group': 0},
                '02': {'MinSrc': [0, 0.0], 'MaxSrc': [65535, 1.0], 'GammaSrc': 1.0, 'MinDst': 0, 'MaxDst': 65535, 'Group': 0}
            },
            'LutDataSpectral': {
                'GainTrueColor': 1.0,
                'OffsetTrueColor': 0.0,
                'GainGrayScale': 1.0,
                'OffsetGrayScal': 0.0,
                'SpectralColorMode': 0,
                'Group00': {
                    'ColorGroup': 16711680,
                    'ColorCustom': 16711680,
                    'GainCustom': 1.0,
                    'OffsetCustom': 0.0,
                    'GainGrouped': 1.0,
                    'OffsetGrouped': 0.0
                }
            }
        },
        'EnableAutoContrast': True,
        'EnableAutoWhite': True,
        'AutoWhiteColor': 16777215,
        'RatioDesc': {
            'Numer': 0,
            'Denom': 1,
            'NumOffset': 0,
            'DenOffset': 0,
            'Min': 0.0,
            'Max': 2.0,
            'BkgndSize': 0,
            'Calibrated': True,
            'Cal.dKd': 224.0,
            'Cal.dVisc': 1.0,
            'Cal.dFmin': 255.0,
            'Cal.dFmax': 1.0,
            'Cal.dRmin': 0.0,
            'Cal.dRmax': 2.0,
            'Cal.dTMeasCalMin': 0.0,
            'Cal.dTMeasCalMax': 0.0,
            'PickFromGraph': True,
            'RatioViewEnabled': True
        },
        'GraphSelected': -1,
        'GraphVerticalSplit': True,
        'GrayGraph': True,
        'ShowAllComp': True,
        'ShowSpectralGraph': True,
        'GraphScale': 0,
        'GraphZoom00': 1.0,
        'GraphOffset00': 0.0,
        'GraphZoom01': 1.0,
        'GraphOffset01': 0.0,
        'GraphZoom02': 1.0,
        'GraphOffset02': 0.0
    },
    'GrabberCameraSettingsV1_0': {
        'GrabberCameraSettings': {
            'CameraUniqueName': 'Hamamatsu C11440-22C SN:101412',
            'CameraUserName': 'Flash4.0, SN:101412',
            'CameraFamilyName': 'ecmC11440_22C',
            'OverloadedUniqueName': '',
            'ModifiedAtJDN': 2459486.07103009,
            'FormatFast': {
                'Desc': {
                    'UniqueName': 'FMT 1x1 16',
                    'Interpretation': 1,
                    'FQModeUsage': 15,
                    'CanExecAsyncSampleGet': True,
                    'Fps': 30.00300030003,
                    'Sensitivity': 1.0,
                    'SensorPixels': {'cx': 2048, 'cy': 2044},
                    'SensorMicrons': {'cx': 13312, 'cy': 13286},
                    'SensorMin': {'cx': 4, 'cy': 4},
                    'SensorStep': {'cx': 2, 'cy': 2},
                    'BinningX': 1.0,
                    'BinningY': 1.0,
                    'SensorSource': {'left': 0, 'top': 0, 'right': 2048, 'bottom': 2044},
                    'FormatText': '16-bit - No Binning',
                    'FormatDesc': '16-bit - No Binning (30.0 FPS)',
                    'CamCorrReq': True,
                    'Comp': 1,
                    'Bpc': 16,
                    'UsageFlags': 1
                },
                'SensorUser': {'left': 512, 'top': 512, 'right': 544, 'bottom': 544}
            },
            'FormatQuality': {
                'Desc': {
                    'UniqueName': 'FMT 1x1 16',
                    'Interpretation': 1,
                    'FQModeUsage': 15,
                    'CanExecAsyncSampleGet': True,
                    'Fps': 30.00300030003,
                    'Sensitivity': 1.0,
                    'SensorPixels': {'cx': 2048, 'cy': 2044},
                    'SensorMicrons': {'cx': 13312, 'cy': 13286},
                    'SensorMin': {'cx': 4, 'cy': 4},
                    'SensorStep': {'cx': 2, 'cy': 2},
                    'BinningX': 1.0,
                    'BinningY': 1.0,
                    'SensorSource': {'left': 0, 'top': 0, 'right': 2048, 'bottom': 2044},
                    'FormatText': '16-bit - No Binning',
                    'FormatDesc': '16-bit - No Binning (30.0 FPS)',
                    'CamCorrReq': True,
                    'Comp': 1,
                    'Bpc': 16,
                    'UsageFlags': 1
                },
                'SensorUser': {'left': 512, 'top': 512, 'right': 544, 'bottom': 544}
            },
            'PropertiesFast': {
                'Exposure': 100.0,
                'LiveSpeedUp': 1,
                'CaptureQuality': 75,
                'CaptureMaxExposure': 10000.0,
                'QuantilRelative': True,
                'QuantilPromile': 0.1,
                'QuantilPixels': 100,
                'EnableAutoExposure': True,
                'ScanMode': 2,
                'Average': 1,
                'Integrate': 1,
                'AverageToQuality': 0.0,
                'AverageCH': '',
                'IntegrateCH': '',
                'AverageToQualityCH': '',
                'IntegrateToQualityCH': '',
                'FlexibleHeight': -1,
                'Negate': 0,
                'MultiExcitation': ''
            },
            'PropertiesFast_Extra': {'PropGroupCount': 0, 'PropGroupUsageArray': {}, 'PropGroupNameArray': {}},
            'PropertiesQuality': {
                'Exposure': 100.0,
                'LiveSpeedUp': 1,
                'CaptureQuality': 75,
                'CaptureMaxExposure': 10000.0,
                'QuantilRelative': True,
                'QuantilPromile': 0.1,
                'QuantilPixels': 100,
                'EnableAutoExposure': True,
                'ScanMode': 2,
                'Average': 1,
                'Integrate': 1,
                'AverageToQuality': 0.0,
                'AverageCH': '',
                'IntegrateCH': '',
                'AverageToQualityCH': '',
                'IntegrateToQualityCH': '',
                'FlexibleHeight': -1,
                'Negate': 0,
                'MultiExcitation': ''
            },
            'PropertiesQuality_Extra': {
                'PropGroupCount': 1,
                'PropGroupUsageArray': {'0': 0},
                'PropGroupNameArray': {'0': 'Use Stored ROI'}
            },
            'Metadata': {
                'Key': 'MV=0,TA=0,CH=1',
                'ChannelCount': 1,
                'Channels': {
                    'Channel_0': {
                        'Color': 22015,
                        'Name': 'Widefield Red',
                        'EmWavelength': 620.0,
                        'ChannelIsActive': True,
                        'ExWavelength': 540.5,
                        'MaxSaturatedValue': 4294967295
                    }
                }
            },
            'LightPath': {
                'TypeID': 0,
                'ExcitationSourceKey': 'LIGHT-EPI',
                'ExcitationSourceName': '',
                'EPIAdditionalFilterKey': '',
                'EPIAdditionalFilterName': '',
                'DIAAdditionalFilterKey': '',
                'DIAAdditionalFilterName': '',
                'LastEmissionFilterKey1': 'Turret-Lo',
                'LastEmissionFilterName1': 'Nikon Ti2, FilterChanger(Turret-Lo)',
                'SetColorManually': True,
                'MultiViewEnabled': True,
                'UpdateLPAutomatically': True
            },
            'ROI': {'Left': 512, 'Top': 512, 'Right': 544, 'Bottom': 544}
        },
        'GrabberCameraSettingsFQMode': 1
    },
    'CustomDataV2_0': {
        'CustomTagDescription_v1.0': {
            'Tag0': {'ID': 'Camera_ExposureTime1', 'Type': 3, 'Group': 2, 'Size': 60, 'Desc': 'Exposure Time', 'Unit': 'ms'},
            'Tag1': {'ID': 'PFS_OFFSET', 'Type': 2, 'Group': 1, 'Size': 60, 'Desc': 'PFS Offset', 'Unit': ''},
            'Tag2': {'ID': 'PFS_STATUS', 'Type': 2, 'Group': 1, 'Size': 60, 'Desc': 'PFS Status', 'Unit': ''},
            'Tag3': {'ID': 'X', 'Type': 3, 'Group': 1, 'Size': 60, 'Desc': 'X Coord', 'Unit': 'µm'},
            'Tag4': {'ID': 'Y', 'Type': 3, 'Group': 1, 'Size': 60, 'Desc': 'Y Coord', 'Unit': 'µm'},
            'Tag5': {'ID': 'Z', 'Type': 3, 'Group': 1, 'Size': 60, 'Desc': 'Z Coord', 'Unit': 'µm'},
            'Tag6': {'ID': 'Z1', 'Type': 3, 'Group': 1, 'Size': 60, 'Desc': 'Ti2 ZDrive', 'Unit': 'µm'}
        }
    },
    'AppInfo_V1_0': {
        'SWNameString': 'NIS-Elements AR',
        'GrabberString': 'Hamamatsu',
        'VersionString': '5.20.02 (Build 1453)',
        'CopyrightString': 'Copyright © 1991-2019  Laboratory Imaging,  http://www.lim.cz',
        'CompanyString': 'NIKON Corporation',
        'NFRString': ''
    },
    'AcqTimeV1_0': 2459486.07044662
}

recorded_data

This property returns a dict of equal-length sequences. It matches the tabular data reported in the Image Properties > Recorded Data tab of the NIS Viewer.

(There will be a column for each tag in the CustomDataV2_0 section of custom_data above.)

{
    'Time [s]': array([ 1.32686654,  1.69089657,  2.04194662,  2.38194662,  2.63795663,
        8.7022286 ,  9.03626864,  9.33031869,  9.63934872,  9.90636874,
       11.48143856, 11.7964786 , 12.0894786 , 12.37153866, 12.66546859]),
    'Z-Series': array([-2., -1.,  0.,  1.,  2., -2., -1.,  0.,  1.,  2., -2., -1.,  0.,
        1.,  2.]),
    'Exposure Time [ms]': array([100., 100., 100., 100., 100., 100., 100., 100., 100., 100., 100.,
       100., 100., 100., 100.]),
    'PFS Offset []': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=int32),
    'PFS Status []': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=int32),
    'X Coord [µm]': array([31452.2, 31452.2, 31452.2, 31452.2, 31452.2, 31452.2, 31452.2,
       31452.2, 31452.2, 31452.2, 31452.2, 31452.2, 31452.2, 31452.2,
       31452.2]),
    'Y Coord [µm]': array([-1801.6, -1801.6, -1801.6, -1801.6, -1801.6, -1801.6, -1801.6,
       -1801.6, -1801.6, -1801.6, -1801.6, -1801.6, -1801.6, -1801.6,
       -1801.6]),
    'Z Coord [µm]': array([552.74, 553.74, 554.74, 555.74, 556.74, 552.7 , 553.7 , 554.68,
       555.7 , 556.64, 552.68, 553.68, 554.68, 555.68, 556.68]),
    'Ti2 ZDrive [µm]': array([552.74, 553.74, 554.74, 555.74, 556.74, 552.7 , 553.7 , 554.68,
       555.7 , 556.64, 552.68, 553.68, 554.68, 555.68, 556.68])
}

You can pass the output of recorded_data to pandas.DataFrame:

In [13]: pd.DataFrame(nd2file.recorded_data)
Out[13]:
     Time [s]  Z-Series  Exposure Time [ms]  PFS Offset []  PFS Status []  X Coord [µm]  Y Coord [µm]  Z Coord [µm]  Ti2 ZDrive [µm]
0    1.326867      -2.0               100.0              0              0       31452.2       -1801.6        552.74           552.74
1    1.690897      -1.0               100.0              0              0       31452.2       -1801.6        553.74           553.74
2    2.041947       0.0               100.0              0              0       31452.2       -1801.6        554.74           554.74
3    2.381947       1.0               100.0              0              0       31452.2       -1801.6        555.74           555.74
4    2.637957       2.0               100.0              0              0       31452.2       -1801.6        556.74           556.74
5    8.702229      -2.0               100.0              0              0       31452.2       -1801.6        552.70           552.70
6    9.036269      -1.0               100.0              0              0       31452.2       -1801.6        553.70           553.70
7    9.330319       0.0               100.0              0              0       31452.2       -1801.6        554.68           554.68
8    9.639349       1.0               100.0              0              0       31452.2       -1801.6        555.70           555.70
9    9.906369       2.0               100.0              0              0       31452.2       -1801.6        556.64           556.64
10  11.481439      -2.0               100.0              0              0       31452.2       -1801.6        552.68           552.68
11  11.796479      -1.0               100.0              0              0       31452.2       -1801.6        553.68           553.68
12  12.089479       0.0               100.0              0              0       31452.2       -1801.6        554.68           554.68
13  12.371539       1.0               100.0              0              0       31452.2       -1801.6        555.68           555.68
14  12.665469       2.0               100.0              0              0       31452.2       -1801.6        556.68           556.68

binary_data

This property returns an nd2.BinaryLayers object representing all of the binary masks in the nd2 file.

A nd2.BinaryLayers object is a sequence of individual nd2.BinaryLayer objects (one for each binary layer found in the file). Each BinaryLayer in the sequence is a named tuple that has, among other things, a name attribute, and a data attribute that is list of numpy arrays (one for each frame in the experiment) or None if the binary layer had no data in that frame.

The most common use case will be to cast either the entire BinaryLayers object or an individual BinaryLayer to a numpy.ndarray:

>>> import nd2
>>> nd2file = nd2.ND2File('path/to/file.nd2')
>>> binary_layers = nd2file.binary_data

# The output array will have shape
# (n_binary_layers, *coord_shape, *frame_shape).
>>> np.asarray(binary_layers)

For example, if the data in the nd2 file has shape (nT, nZ, nC, nY, nX), and there are 4 binary layers, then the output of np.asarray(nd2file.binary_data) will have shape (4, nT, nZ, nY, nX). (Note that the nC dimension is not present in the output array, and the binary layers are always in the first axis).

You can also cast an individual BinaryLayer to a numpy array:

>>> binary_layer = binary_layers[0]
>>> np.asarray(binary_layer)

Contributing / Development

To test locally and contribute. Clone this repo, then:

pip install -e .[dev]

To download sample data:

pip install requests
python scripts/download_samples.py

then run tests:

pytest

(and feel free to open an issue if that doesn't work!)

alternatives

• pims_nd2 - pims-based reader. ctypes wrapper around the v9.00 (2015) SDK
• nd2reader - pims-based reader, using reverse-engineered file headers. mostly tested on NIS Elements 4.30.02
• nd2file - another pure-python, chunk map reader, unmaintained?
• pyND2SDK - windows-only cython wrapper around the v9.00 (2015) SDK. not on PyPI

The motivating factors for this library were:

• support for as many nd2 files as possible, with a large test suite
• pims-independent delayed reader based on dask
• axis-associated metadata via xarray
• combined approach of SDK and direct binary reads