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Python StreamHist.quantiles方法代码示例

本文整理汇总了Python中streamhist.StreamHist.quantiles方法的典型用法代码示例。如果您正苦于以下问题:Python StreamHist.quantiles方法的具体用法?Python StreamHist.quantiles怎么用?Python StreamHist.quantiles使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在streamhist.StreamHist的用法示例。


在下文中一共展示了StreamHist.quantiles方法的3个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: test_regression

# 需要导入模块: from streamhist import StreamHist [as 别名]
# 或者: from streamhist.StreamHist import quantiles [as 别名]
def test_regression():
    random.seed(1700)
    data = make_normal(10000)
    hist1 = StreamHist(maxbins=5)
    hist2 = StreamHist(maxbins=5, weighted=True)
    # hist3 = StreamHist(maxbins=5, weighted=True)
    hist4 = StreamHist(maxbins=5)

    hist1.update(data)
    hist2.update(data)
    hist3 = hist2 + hist1
    hist4.update(range(10000))

    reg = [{'count': 1176.0, 'mean': -1.622498097884402},
           {'count': 5290.0, 'mean': -0.3390892100898127},
           {'count': 3497.0, 'mean': 1.0310297400593385},
           {'count': 35.0, 'mean': 2.2157182954841126},
           {'count': 2.0, 'mean': 3.563619987633774}]
    assert hist1.to_dict()["bins"] == reg

    reg = [-1.022649473089556, -0.5279748744244142, 0.1476067074922296,
           0.9815338358189885, 1.6627248917927795]
    assert hist1.quantiles(0.1, 0.25, 0.5, 0.75, 0.9) == reg

    reg = [{'count': 579.0, 'mean': -2.017257931684027},
           {'count': 1902.0, 'mean': -1.0677091300958608},
           {'count': 3061.0, 'mean': -0.24660751313691653},
           {'count': 2986.0, 'mean': 0.5523120572161528},
           {'count': 1472.0, 'mean': 1.557598912751095}]
    assert hist2.to_dict()["bins"] == reg

    reg = [-1.1941285587341846, -0.6041467139342105, 0.08840996549170466,
           0.8247014091807423, 1.557598912751095]
    assert hist2.quantiles(0.1, 0.25, 0.5, 0.75, 0.9) == reg

    reg = [{'count': 1755.0, 'mean': -1.7527351028815432},
           {'count': 1902.0, 'mean': -1.0677091300958608},
           {'count': 8351.0, 'mean': -0.3051906980106826},
           {'count': 6483.0, 'mean': 0.8105375295133331},
           {'count': 1509.0, 'mean': 1.5755221868037264}]
    assert hist3.to_dict()["bins"] == reg

    reg = [-1.0074328972882012, -0.5037558708214145, 0.11958766584785563,
           0.8874923692642509, 1.432517386448461]
    assert hist3.quantiles(0.1, 0.25, 0.5, 0.75, 0.9) == reg

    reg = [{'count': 1339.0, 'mean': 669.0},
           {'count': 2673.0, 'mean': 2675.0},
           {'count': 1338.0, 'mean': 4680.5},
           {'count': 2672.0, 'mean': 6685.5},
           {'count': 1978.0, 'mean': 9010.5}]
    assert hist4.to_dict()["bins"] == reg

    reg = [1830.581598358843, 3063.70150218845, 5831.110283907479,
           8084.851093080222, 9010.5]
    assert hist4.quantiles(0.1, 0.25, 0.5, 0.75, 0.9) == reg
开发者ID:carsonfarmer,项目名称:streamhist,代码行数:58,代码来源:test_regression.py

示例2: test_quantiles

# 需要导入模块: from streamhist import StreamHist [as 别名]
# 或者: from streamhist.StreamHist import quantiles [as 别名]
def test_quantiles():
    points = 10000
    h = StreamHist()
    for p in make_uniform(points):
        h.update(p)
    assert about(h.quantiles(0.5)[0], 0.5, 0.05)

    h = StreamHist()
    for p in make_normal(points):
        h.update(p)
    a, b, c = h.quantiles(0.25, 0.5, 0.75)
    assert about(a, -0.66, 0.05)
    assert about(b, 0.00, 0.05)
    assert about(c, 0.66, 0.05)
开发者ID:carsonfarmer,项目名称:streamhist,代码行数:16,代码来源:test_histogram.py

示例3: test_multi_merge

# 需要导入模块: from streamhist import StreamHist [as 别名]
# 或者: from streamhist.StreamHist import quantiles [as 别名]
def test_multi_merge():
    points = 100000
    data = make_uniform(points)
    samples = [data[x:x+100] for x in range(0, len(data), 100)]
    hists = [StreamHist().update(s) for s in samples]
    h1 = sum(hists)
    h2 = StreamHist().update(data)

    q1 = h1.quantiles(.1, .2, .3, .4, .5, .6, .7, .8, .9)
    q2 = h2.quantiles(.1, .2, .3, .4, .5, .6, .7, .8, .9)
    from numpy import allclose
    assert allclose(q1, q2, rtol=1, atol=0.025)
开发者ID:carsonfarmer,项目名称:streamhist,代码行数:14,代码来源:test_histogram.py


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