Python IO.readMetaData方法代码示例

# 需要导入模块: from ClearMap import IO [as 别名]
# 或者: from ClearMap.IO import readMetaData [as 别名]
def readMetaData(source, info=all, sort=True):
    """Reads the meta data from the image files
  
  Arguments:
    source: the data source
    info (list or all): optional list of keywords
    sort (bool): if True use first file to infer meta data, otherwise arbitrary file
  
  Returns:
    object: an object with the meta data
  """

    firstfile = firstFile(source, sort=sort)

    mdata = io.readMetaData(firstfile, info=info)

    if "size" in mdata.keys():
        mdata["size"] = dataSize(source)

    return mdata

# 需要导入模块: from ClearMap import IO [as 别名]
# 或者: from ClearMap.IO import readMetaData [as 别名]
# -*- coding: utf-8 -*-
"""
Created on Thu Jul 14 17:21:40 2016

@author: ckirst
"""

import os

import ClearMap.Settings as settings
import ClearMap.IO as io


fn = os.path.join(settings.ClearMapPath, 'Test/Data/OME/16-17-27_0_8X-s3-20HF_UltraII_C00_xyz-Table Z1000.ome.tif')

io.readMetaData(fn, info = ['overlap', 'resolution', 'size'])

fn = os.path.join(settings.ClearMapPath, 'Test/Data/Tif/test.tif')

io.readMetaData(fn, info = ['overlap', 'resolution', 'size', 'description'])

io.readMetaData(fn)


fn = os.path.join(settings.ClearMapPath, 'Test/Data/OME/16-17-27_0_8X-s3-20HF_UltraII_C00_xyz-Table Z\d{4}.ome.tif')

io.readMetaData(fn, info = ['overlap', 'resolution', 'size'])


import tifffile as t;

# 需要导入模块: from ClearMap import IO [as 别名]
# 或者: from ClearMap.IO import readMetaData [as 别名]
def cropData(source, sink=None, x=all, y=all, z=all, adjustOverlap=False, verbose=True, processes=all):
    """Crop source from start to stop point
  
  Arguments:
    source (str or array): filename or data array of source
    sink (str or None): filename or sink
    x,y,z (tuple or all): the range to crop the data to
    adjustOverlap (bool): correct overlap meta data if exists
  
  Return:
    str or array: array or filename with cropped data
  """

    if sink is None:
        return readDataFiles(source, x=x, y=y, z=z)
    else:  # sink assumed to be file expression

        if not io.isFileExpression(sink):
            raise RuntimeError("cropping data to different format not supported!")

        fileheader, fileext, digitfrmt = splitFileExpression(sink)

        # read first image to get data size and type
        fp, fl = readFileList(source)
        nz = len(fl)
        rz = io.toDataRange(nz, r=z)

        if adjustOverlap:  # change overlap in first file
            try:
                fn = os.path.join(fp, fl[0])
                info = io.readMetaData(fn, info=["description", "overlap", "resolution"])
                description = str(info["description"])
                overlap = numpy.array(info["overlap"], dtype=float)
                resolution = numpy.array(info["resolution"], dtype=float)

            except:
                raise RuntimeWarning("could not modify overlap!")

            fullsize = io.dataSize(fn)
            data = io.readData(fn, x=x, y=y)

            # overlap in pixels
            poverlap = overlap[:2] / resolution[:2]
            print poverlap

            # cropped pixel
            xr = io.toDataRange(fullsize[0], r=x)
            yr = io.toDataRange(fullsize[1], r=y)

            print xr
            print yr
            print fullsize

            poverlap[0] = poverlap[0] - xr[0] - (fullsize[0] - xr[1])
            poverlap[1] = poverlap[1] - yr[0] - (fullsize[1] - yr[1])
            print poverlap

            # new overlap in microns
            overlap = poverlap * resolution[:2]

            # check for consistency
            if numpy.abs(fullsize[0] - xr[1] - xr[0]) > 1 or numpy.abs(fullsize[1] - yr[1] - yr[0]) > 1:
                raise RuntimeWarning("cropping is inconsistent with overlap )modification!")

            # change image description
            import ClearMap.IO.TIF as CMTIF

            description = CMTIF.changeOMEMetaDataString(description, {"overlap": overlap})
            print len(description)

            # write first file
            fnout = fileheader + (digitfrmt % 0) + fileext
            io.writeData(fnout, data, info=description)

            zr = range(rz[0] + 1, rz[1])
        else:
            zr = range(rz[0], rz[1])

        print zr
        nZ = len(zr)

        if processes is None:
            processes = 1
        if processes is all:
            processes = multiprocessing.cpu_count()

        if processes > 1:  # parallel processing
            pool = multiprocessing.Pool(processes=processes)
            argdata = []

            for i, z in enumerate(zr):
                if verbose:
                    argdata.append(
                        (os.path.join(fp, fl[z]), fileheader + (digitfrmt % (i + 1)) + fileext, x, y, (i + 1), (nZ + 1))
                    )
                else:
                    argdata.append(
                        (os.path.join(fp, fl[z]), fileheader + (digitfrmt % (i + 1)) + fileext, x, y, None, None)
                    )

#.........这里部分代码省略.........

# 需要导入模块: from ClearMap import IO [as 别名]
# 或者: from ClearMap.IO import readMetaData [as 别名]
fn = os.path.join(datadir, r'160412_mosaic_15-20-19/15-20-19_mosaic_UltraII\[(?P<row>\d{2}) x (?P<col>\d{2})\]_C00_xyz-Table Z(?P<z>\d{4}).ome.tif')

_, gr = st.findFileList(fn , sort = True, groups = ['row','col'], absolute = True)
groups = [];
for i in range(gr.shape[1]):
    groups.append(np.unique(gr[:,i]));

print groups

for i in groups[0]:
    for j in groups[1]:
        fileExpression = os.path.join(datadir, r'160412_mosaic_15-20-19/15-20-19_mosaic_UltraII\[%s x %s]_C00_xyz-Table Z\d{4}.ome.tif' % (i,j))

        io.dataSize(fileExpression)

        io.readMetaData(fileExpression, info = ['size', 'overlap', 'resolution'])


        import ClearMap.IO.FileList as fl;
        reload(fl)

        fncrop = os.path.join(datadir, r'cropped/15-20-19_mosaic_UltraII_%s_x_%s_C00_xyz-Table Z\d{4}.ome.tif' % (i,j))


        fc = fl.cropData(fileExpression, fncrop, x = (400, -400), y = (550, -550),  adjustOverlap = True, processes = all)
        #fc1 = fl.firstFile(fc)
        #io.readMetaData(fc1, info = ['overlap', 'resolution', 'size']);