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test_autoplot.py
Source:test_autoplot.py  
...43# @viz_reg_test44# def test_autoplot_{n}():45#     return ar.autoplot(data.head({nrows}), columns={vars})46#47# show_test(test_autoplot_{n})48# """.format(49#                     nrows=nrows, vars=vars, n=n50#                 )51#             )52#'  <h3> Test autoplot #1</h3>53@viz_reg_test54def test_autoplot_1():55    return ar.autoplot(data.head(10), columns=["x"])56show_test(test_autoplot_1)57#'  <h3> Test autoplot #2</h3>58@viz_reg_test59def test_autoplot_2():60    return ar.autoplot(data.head(50), columns=["x"])61show_test(test_autoplot_2)62#'  <h3> Test autoplot #3</h3>63@viz_reg_test64def test_autoplot_3():65    return ar.autoplot(data.head(250), columns=["x"])66show_test(test_autoplot_3)67#'  <h3> Test autoplot #4</h3>68@viz_reg_test69def test_autoplot_4():70    return ar.autoplot(data.head(1000), columns=["x"])71show_test(test_autoplot_4)72#'  <h3> Test autoplot #5</h3>73@viz_reg_test74def test_autoplot_5():75    return ar.autoplot(data.head(5000), columns=["x"])76show_test(test_autoplot_5)77#'  <h3> Test autoplot #6</h3>78@viz_reg_test79def test_autoplot_6():80    return ar.autoplot(data.head(10), columns=["x_cat"])81show_test(test_autoplot_6)82#'  <h3> Test autoplot #7</h3>83@viz_reg_test84def test_autoplot_7():85    return ar.autoplot(data.head(50), columns=["x_cat"])86show_test(test_autoplot_7)87#'  <h3> Test autoplot #8</h3>88@viz_reg_test89def test_autoplot_8():90    return ar.autoplot(data.head(250), columns=["x_cat"])91show_test(test_autoplot_8)92#'  <h3> Test autoplot #9</h3>93@viz_reg_test94def test_autoplot_9():95    return ar.autoplot(data.head(1000), columns=["x_cat"])96show_test(test_autoplot_9)97#'  <h3> Test autoplot #10</h3>98@viz_reg_test99def test_autoplot_10():100    return ar.autoplot(data.head(5000), columns=["x_cat"])101show_test(test_autoplot_10)102#'  <h3> Test autoplot #11</h3>103@viz_reg_test104def test_autoplot_11():105    return ar.autoplot(data.head(10), columns=["x", "y"])106show_test(test_autoplot_11)107#'  <h3> Test autoplot #12</h3>108@viz_reg_test109def test_autoplot_12():110    return ar.autoplot(data.head(50), columns=["x", "y"])111show_test(test_autoplot_12)112#'  <h3> Test autoplot #13</h3>113@viz_reg_test114def test_autoplot_13():115    return ar.autoplot(data.head(250), columns=["x", "y"])116show_test(test_autoplot_13)117#'  <h3> Test autoplot #14</h3>118@viz_reg_test119def test_autoplot_14():120    return ar.autoplot(data.head(1000), columns=["x", "y"])121show_test(test_autoplot_14)122#'  <h3> Test autoplot #15</h3>123@viz_reg_test124def test_autoplot_15():125    return ar.autoplot(data.head(5000), columns=["x", "y"])126show_test(test_autoplot_15)127#'  <h3> Test autoplot #16</h3>128@viz_reg_test129def test_autoplot_16():130    return ar.autoplot(data.head(10), columns=["x_cat", "y"])131show_test(test_autoplot_16)132#'  <h3> Test autoplot #17</h3>133@viz_reg_test134def test_autoplot_17():135    return ar.autoplot(data.head(50), columns=["x_cat", "y"])136show_test(test_autoplot_17)137#'  <h3> Test autoplot #18</h3>138@viz_reg_test139def test_autoplot_18():140    return ar.autoplot(data.head(250), columns=["x_cat", "y"])141show_test(test_autoplot_18)142#'  <h3> Test autoplot #19</h3>143@viz_reg_test144def test_autoplot_19():145    return ar.autoplot(data.head(1000), columns=["x_cat", "y"])146show_test(test_autoplot_19)147#'  <h3> Test autoplot #20</h3>148@viz_reg_test149def test_autoplot_20():150    return ar.autoplot(data.head(5000), columns=["x_cat", "y"])151show_test(test_autoplot_20)152#'  <h3> Test autoplot #21</h3>153@viz_reg_test154def test_autoplot_21():155    return ar.autoplot(data.head(10), columns=["x_cat", "y_cat"])156show_test(test_autoplot_21)157#'  <h3> Test autoplot #22</h3>158@viz_reg_test159def test_autoplot_22():160    return ar.autoplot(data.head(50), columns=["x_cat", "y_cat"])161show_test(test_autoplot_22)162#'  <h3> Test autoplot #23</h3>163@viz_reg_test164def test_autoplot_23():165    return ar.autoplot(data.head(250), columns=["x_cat", "y_cat"])166show_test(test_autoplot_23)167#'  <h3> Test autoplot #24</h3>168@viz_reg_test169def test_autoplot_24():170    return ar.autoplot(data.head(1000), columns=["x_cat", "y_cat"])171show_test(test_autoplot_24)172#'  <h3> Test autoplot #25</h3>173@viz_reg_test174def test_autoplot_25():175    return ar.autoplot(data.head(5000), columns=["x_cat", "y_cat"])176show_test(test_autoplot_25)177#'  <h3> Test autoplot #26</h3>178@viz_reg_test179def test_autoplot_26():180    return ar.autoplot(data.head(10), columns=["x", "y", "z"])181show_test(test_autoplot_26)182#'  <h3> Test autoplot #27</h3>183@viz_reg_test184def test_autoplot_27():185    return ar.autoplot(data.head(50), columns=["x", "y", "z"])186show_test(test_autoplot_27)187#'  <h3> Test autoplot #28</h3>188@viz_reg_test189def test_autoplot_28():190    return ar.autoplot(data.head(250), columns=["x", "y", "z"])191show_test(test_autoplot_28)192#'  <h3> Test autoplot #29</h3>193@viz_reg_test194def test_autoplot_29():195    return ar.autoplot(data.head(1000), columns=["x", "y", "z"])196show_test(test_autoplot_29)197#'  <h3> Test autoplot #30</h3>198@viz_reg_test199def test_autoplot_30():200    return ar.autoplot(data.head(5000), columns=["x", "y", "z"])201show_test(test_autoplot_30)202#'  <h3> Test autoplot #31</h3>203@viz_reg_test204def test_autoplot_31():205    return ar.autoplot(data.head(10), columns=["x_cat", "y", "z"])206show_test(test_autoplot_31)207#'  <h3> Test autoplot #32</h3>208@viz_reg_test209def test_autoplot_32():210    return ar.autoplot(data.head(50), columns=["x_cat", "y", "z"])211show_test(test_autoplot_32)212#'  <h3> Test autoplot #33</h3>213@viz_reg_test214def test_autoplot_33():215    return ar.autoplot(data.head(250), columns=["x_cat", "y", "z"])216show_test(test_autoplot_33)217#'  <h3> Test autoplot #34</h3>218@viz_reg_test219def test_autoplot_34():220    return ar.autoplot(data.head(1000), columns=["x_cat", "y", "z"])221show_test(test_autoplot_34)222#'  <h3> Test autoplot #35</h3>223@viz_reg_test224def test_autoplot_35():225    return ar.autoplot(data.head(5000), columns=["x_cat", "y", "z"])226show_test(test_autoplot_35)227#'  <h3> Test autoplot #36</h3>228@viz_reg_test229def test_autoplot_36():230    return ar.autoplot(data.head(10), columns=["x_cat", "y_cat", "z"])231show_test(test_autoplot_36)232#'  <h3> Test autoplot #37</h3>233@viz_reg_test234def test_autoplot_37():235    return ar.autoplot(data.head(50), columns=["x_cat", "y_cat", "z"])236show_test(test_autoplot_37)237#'  <h3> Test autoplot #38</h3>238@viz_reg_test239def test_autoplot_38():240    return ar.autoplot(data.head(250), columns=["x_cat", "y_cat", "z"])241show_test(test_autoplot_38)242#'  <h3> Test autoplot #39</h3>243@viz_reg_test244def test_autoplot_39():245    return ar.autoplot(data.head(1000), columns=["x_cat", "y_cat", "z"])246show_test(test_autoplot_39)247#'  <h3> Test autoplot #40</h3>248@viz_reg_test249def test_autoplot_40():250    return ar.autoplot(data.head(5000), columns=["x_cat", "y_cat", "z"])251show_test(test_autoplot_40)252#'  <h3> Test autoplot #41</h3>253@viz_reg_test254def test_autoplot_41():255    return ar.autoplot(data.head(10), columns=["x_cat", "y_cat", "z_cat"])256show_test(test_autoplot_41)257#'  <h3> Test autoplot #42</h3>258@viz_reg_test259def test_autoplot_42():260    return ar.autoplot(data.head(50), columns=["x_cat", "y_cat", "z_cat"])261show_test(test_autoplot_42)262#'  <h3> Test autoplot #43</h3>263@viz_reg_test264def test_autoplot_43():265    return ar.autoplot(data.head(250), columns=["x_cat", "y_cat", "z_cat"])266show_test(test_autoplot_43)267#'  <h3> Test autoplot #44</h3>268@viz_reg_test269def test_autoplot_44():270    return ar.autoplot(data.head(1000), columns=["x_cat", "y_cat", "z_cat"])271show_test(test_autoplot_44)272#'  <h3> Test autoplot #45</h3>273@viz_reg_test274def test_autoplot_45():275    return ar.autoplot(data.head(5000), columns=["x_cat", "y_cat", "z_cat"])276show_test(test_autoplot_45)277#' To finish three corner cases when there's no overlap with categorical vars only278w = pd.Series(range(10))279no_overlap_data = pd.DataFrame(280    dict(281        x=pd.concat([w, w - 3]).astype(str),282        y=pd.concat([w, w]).astype(str),283        z=pd.concat([w, w]).astype(str),284    )285)286@viz_reg_test287def test_autoplot_CCC():288    return ar.autoplot(no_overlap_data)289show_test(test_autoplot_CCC)290@viz_reg_test291def test_autoplot_CC():292    return ar.autoplot(no_overlap_data, columns=["x", "y"])293show_test(test_autoplot_CC)294@viz_reg_test295def test_autoplot_C():296    return ar.autoplot(no_overlap_data.head(10), columns=["x"])...kernel_utils.py
Source:kernel_utils.py  
1import logging2import numpy as np3from eval_pd import get_evaluation_results4from itertools import combinations5from global_constants import  *6from global_utils import  *7def run_config(c, dataset, resulting_matrices, labels,show_test=True, probability=False,8               skip_all_positives_and_all_negatives=True):9    cs = set(c)10    label = " + ".join(cs)11    matrix = dict()12    for mode in ALL_MODES:13        matrix[mode] = sum([v[mode] for k, v in resulting_matrices.items() if k in cs])14    predictions = train_and_predict(matrix, labels, kernel='precomputed', probability=probability)15    dev_results = get_evaluation_results(dataset[DEV], predictions[DEV],16                                         skip_all_positives_and_all_negatives=skip_all_positives_and_all_negatives)17    test_results = get_evaluation_results(dataset[TEST], predictions[TEST],18                                          skip_all_positives_and_all_negatives=skip_all_positives_and_all_negatives)19    message = "%s\t%s\t%s" % (label, "\t".join(["%.2f" % (x) for x in list(dev_results)]),20                              "\t".join(["%.2f" % (x) for x in list(test_results)]))21    logging.info("DEV:\t%s\t%s" % (label, "\t".join(["%.2f" % (x) for x in list(dev_results)])))22    if show_test:23        logging.info("TEST:\t%s\t%s" % (label, "\t".join(["%.2f" % (x) for x in list(test_results)])))24    return message25def run_experiments(dataset, configurations, resulting_matrices, labels, predefined=False, show_test=True, min_length=1,26                    max_length=-1, probability=False, skip_all_positives_and_all_negatives=True):27    messages = []28    if predefined:29        for c in configurations:30            message = run_config(c, dataset, resulting_matrices, labels, show_test=show_test, probability=probability,31                                 skip_all_positives_and_all_negatives= skip_all_positives_and_all_negatives)32            messages.append(message)33    else:34        start = min_length - 135        end = max_length if max_length > 0 else len(configurations)36        for l in range(start, end):37            for c in combinations(configurations, l + 1):38                message = run_config(c, dataset, resulting_matrices, labels, show_test=show_test,39                                     probability=probability,40                                     skip_all_positives_and_all_negatives= skip_all_positives_and_all_negatives)41                messages.append(message)42    return messages43def convert_svm_light_vector_to_np_array(x,array_size,zero_vector):44    aa = zero_vector45#     print type(x),x46    if not isinstance(x,str):47        logging.debug("Substituting %s with zero vector" % (str(x)))48        return aa49#     if isinstance(x,np.ndarray):50#         return x51    aa = np.zeros(shape=(1,array_size))52    if len(x.strip())==0:53        return aa54    for tuplesa in x.strip().split(" "):55        if not ":" in tuplesa:56            logging.error("Wrong format: %s" % (str(x)))57        indexa,valuea=tuplesa.strip().split(":")58        if int(indexa)-1>=array_size:59            print x60        aa[0,int(indexa)-1]=np.float64(valuea)61#         print aa[0]...urls.py
Source:urls.py  
1from django.conf.urls import url2from booktest import views3urlpatterns = [4   url(r'^$', views.index, name='index'),5   url(r'^show_test', views.show_test, name='show_test'),6   url(r'^index2/$', views.index2, name='index2'),7   url(r'^user1/$', views.user1, name='user1'),8   url(r'^user2/$', views.user2, name='user2'),9   url(r'^zhuanyi/$', views.zhuanyi, name='zhuanyi'),10   url(r'^csrf1/$', views.csrf1, name='csrf1'),11   url(r'^csrf2/$', views.csrf2, name='csrf2'),12   url(r'^verify1/$', views.verify1, name='verify1'),13   url(r'^verify2/$', views.verify2, name='verify2'),14   url(r'^show_verify/$', views.show_verify, name='show_verify'),...Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.
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