Python Data.metadata方法代码示例

# 需要导入模块: from Stoner import Data [as 别名]
# 或者: from Stoner.Data import metadata [as 别名]
def norm_group(pos,_,**kargs):
    """Takes the drain current for each file in group and builds an analysis file and works out the mean drain"""
    if "signal" in kargs:
        signal=kargs["signal"]
    else:
        signal="fluo"
    lfit=kargs["lfit"]
    rfit=kargs["rfit"]

    posfile=Data()
    posfile.metadata=pos[0].metadata
    posfile=posfile&pos[0].column(0)
    posfile.column_headers=['Energy']
    for f in pos:
        print(str(f["run"])+str(f.find_col(signal)))
        posfile=posfile&f.column(signal)
    posfile.add_column(lambda r:np.mean(r[1:]),"mean drain")
    ec=posfile.find_col('Energy')
    md=posfile.find_col('mean drain')
    linearfit=scipy.poly1d(posfile.polyfit(ec,md,1,lambda x,y:lfit[0]<=x<=lfit[1]))
    posfile.add_column(lambda r:r[md]-linearfit(r[ec]),'minus linear')
    highend=posfile.mean('minus',lambda r:rfit[0]<=r[ec]<=rfit[1])
    ml=posfile.find_col('minus linear')
    posfile.add_column(lambda r:r[ml]/highend,"normalised")
    if "group_key" in kargs:
        posfile[kargs["group_key"]]=pos.key
    return posfile

# 需要导入模块: from Stoner import Data [as 别名]
# 或者: from Stoner.Data import metadata [as 别名]
def profile_line(img, src=None, dst=None, linewidth=1, order=1, mode="constant", cval=0.0, constrain=True, **kargs):
    """Wrapper for sckit-image method of the same name to get a line_profile.

    Parameters:
        img(ImageArray): Image data to take line section of
        src, dst (2-tuple of int or float): start and end of line profile. If the co-ordinates
            are given as intergers then they are assumed to be pxiel co-ordinates, floats are
            assumed to be real-space co-ordinates using the embedded metadata.
        linewidth (int): the wideth of the profile to be taken.
        order (int 1-3): Order of interpolation used to find image data when not aligned to a point
        mode (str): How to handle data outside of the image.
        cval (float): The constant value to assume for data outside of the image is mode is "constant"
        constrain (bool): Ensure the src and dst are within the image (default True).

    Returns:
        A :py:class:`Stoner.Data` object containing the line profile data and the metadata from the image.
    """
    scale = img.get("MicronsPerPixel", 1.0)
    r, c = img.shape
    if src is None and dst is None:
        if "x" in kargs:
            src = (kargs["x"], 0)
            dst = (kargs["x"], r)
        if "y" in kargs:
            src = (0, kargs["y"])
            dst = (c, kargs["y"])
    if isinstance(src, float):
        src = (src, src)
    if isinstance(dst, float):
        dst = (dst, dst)
    dst = _scale(dst, scale)
    src = _scale(src, scale)
    if not istuple(src, int, int):
        raise ValueError("src co-ordinates are not a 2-tuple of ints.")
    if not istuple(dst, int, int):
        raise ValueError("dst co-ordinates are not a 2-tuple of ints.")

    if constrain:
        fix = lambda x, mx: int(round(sorted([0, x, mx])[1]))
        r, c = img.shape
        src = list(src)
        src = (fix(src[0], r), fix(src[1], c))
        dst = (fix(dst[0], r), fix(dst[1], c))

    result = measure.profile_line(img, src, dst, linewidth, order, mode, cval)
    points = measure.profile._line_profile_coordinates(src, dst, linewidth)[:, :, 0]
    ret = Data()
    ret.data = points.T
    ret.setas = "xy"
    ret &= np.sqrt(ret.x ** 2 + ret.y ** 2) * scale
    ret &= result
    ret.column_headers = ["X", "Y", "Distance", "Intensity"]
    ret.setas = "..xy"
    ret.metadata = img.metadata.copy()
    return ret