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Python ma.allclose方法代碼示例

本文整理匯總了Python中numpy.ma.allclose方法的典型用法代碼示例。如果您正苦於以下問題:Python ma.allclose方法的具體用法?Python ma.allclose怎麽用?Python ma.allclose使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在numpy.ma的用法示例。


在下文中一共展示了ma.allclose方法的3個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: obrientransform

# 需要導入模塊: from numpy import ma [as 別名]
# 或者: from numpy.ma import allclose [as 別名]
def obrientransform(*args):
    """
    Computes a transform on input data (any number of columns).  Used to
    test for homogeneity of variance prior to running one-way stats.  Each
    array in ``*args`` is one level of a factor.  If an `f_oneway()` run on
    the transformed data and found significant, variances are unequal.   From
    Maxwell and Delaney, p.112.

    Returns: transformed data for use in an ANOVA
    """
    data = argstoarray(*args).T
    v = data.var(axis=0,ddof=1)
    m = data.mean(0)
    n = data.count(0).astype(float)
    # result = ((N-1.5)*N*(a-m)**2 - 0.5*v*(n-1))/((n-1)*(n-2))
    data -= m
    data **= 2
    data *= (n-1.5)*n
    data -= 0.5*v*(n-1)
    data /= (n-1.)*(n-2.)
    if not ma.allclose(v,data.mean(0)):
        raise ValueError("Lack of convergence in obrientransform.")

    return data 
開發者ID:ryfeus,項目名稱:lambda-packs,代碼行數:26,代碼來源:mstats_basic.py

示例2: obrientransform

# 需要導入模塊: from numpy import ma [as 別名]
# 或者: from numpy.ma import allclose [as 別名]
def obrientransform(*args):
    """
Computes a transform on input data (any number of columns).  Used to
test for homogeneity of variance prior to running one-way stats.  Each
array in *args is one level of a factor.  If an F_oneway() run on the
transformed data and found significant, variances are unequal.   From
Maxwell and Delaney, p.112.

Returns: transformed data for use in an ANOVA
    """
    data = argstoarray(*args).T
    v = data.var(axis=0,ddof=1)
    m = data.mean(0)
    n = data.count(0).astype(float)
    # result = ((N-1.5)*N*(a-m)**2 - 0.5*v*(n-1))/((n-1)*(n-2))
    data -= m
    data **= 2
    data *= (n-1.5)*n
    data -= 0.5*v*(n-1)
    data /= (n-1.)*(n-2.)
    if not ma.allclose(v,data.mean(0)):
        raise ValueError("Lack of convergence in obrientransform.")
    return data 
開發者ID:ktraunmueller,項目名稱:Computable,代碼行數:25,代碼來源:mstats_basic.py

示例3: test_processing

# 需要導入模塊: from numpy import ma [as 別名]
# 或者: from numpy.ma import allclose [as 別名]
def test_processing(mp_tmpdir, cleantopo_br, cleantopo_tl):
    """Test correct processing (read and write) outputs."""
    for cleantopo_process in [cleantopo_br.path, cleantopo_tl.path]:
        with mapchete.open(cleantopo_process) as mp:
            for zoom in range(6):
                tiles = []
                for tile in mp.get_process_tiles(zoom):
                    output = mp.execute(tile)
                    tiles.append((tile, output))
                    assert isinstance(output, ma.MaskedArray)
                    assert output.shape == output.shape
                    assert not ma.all(output.mask)
                    mp.write(tile, output)
                mosaic = create_mosaic(tiles)
                try:
                    temp_vrt = os.path.join(mp_tmpdir, str(zoom)+".vrt")
                    gdalbuildvrt = "gdalbuildvrt %s %s/%s/*/*.tif > /dev/null" % (
                        temp_vrt, mp.config.output.path, zoom)
                    os.system(gdalbuildvrt)
                    with rasterio.open(temp_vrt, "r") as testfile:
                        for file_item, mosaic_item in zip(
                            testfile.meta["transform"], mosaic.affine
                        ):
                            assert file_item == mosaic_item
                        band = testfile.read(1, masked=True)
                        assert band.shape == mosaic.data.shape
                        assert ma.allclose(band, mosaic.data)
                        assert ma.allclose(band.mask, mosaic.data.mask)
                finally:
                    shutil.rmtree(mp_tmpdir, ignore_errors=True) 
開發者ID:ungarj,項目名稱:mapchete,代碼行數:32,代碼來源:test_mapchete.py


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