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/dports/math/py-pandas/pandas-1.2.5/pandas/tests/indexing/
H A Dtest_scalar.py87 for r in [lambda: s.iat[1], lambda: s.iloc[1]]:
94 for r in [lambda: s.iat[1], lambda: s.iloc[1]]:
107 result = s.iloc[2]
119 result = s.iloc[[2, 3]]
124 result = df.iloc[2]
137 expected = df.iloc[0]
147 tm.assert_series_equal(df.iloc[1], expected)
176 assert s.iat[i] == s.iloc[i] == i + 1
194 assert df.iat[row, i] == df.iloc[row, i] == row * 5 + i
232 for result in [df.at[0, "A"], df.iat[0, 0], df.loc[0, "A"], df.iloc[0, 0]]:
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H A Dtest_chaining_and_caching.py29 df["bb"].iloc[0] = 0.17
126 df["A"].iloc[0] = np.nan
131 df.A.iloc[0] = np.nan
229 x = df.iloc[[0, 1, 2]]
232 x = df.iloc[[0, 1, 2, 4]]
274 s = df.iloc[:, 0].sort_values()
298 df.iloc[0:5]["group"] = "a"
370 expected = df["A"].iloc[2]
373 result2 = df.iloc[2]["A"]
377 result4 = df["A"].iloc[2]
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H A Dtest_floats.py26 expected = original.iloc[indexer]
220 expected = s.iloc[3]
223 s2.iloc[3] = expected
224 result = s2.iloc[3]
254 s.iloc[idx]
269 s.iloc[idx] = 0
365 expected = s.iloc[2:4]
377 s.iloc[idx]
471 expected = s.iloc[3:4]
492 assert s.iloc[3] == 3
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/statespace/tests/
H A Dtest_univariate.py266 obs.iloc[:50, :] = np.nan
267 obs.iloc[119:130, :] = np.nan
269 obs.iloc[0:50, 0] = np.nan
272 obs.iloc[0:50, 0] = np.nan
273 obs.iloc[19:70, 1] = np.nan
274 obs.iloc[39:90, 2] = np.nan
527 obs.iloc[:50, :] = np.nan
530 obs.iloc[0:50, 0] = np.nan
533 obs.iloc[0:50, 0] = np.nan
534 obs.iloc[19:70, 1] = np.nan
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H A Dtest_news.py288 endog1.iloc[-1] = 0.
339 endog1.iloc[-2], endog1.iloc[-1] * 0.5**np.arange(3)].reshape(4, 1)
341 endog2.iloc[-2], 0.5 ** np.arange(3) * endog2.iloc[-1]].reshape(4, 1)
389 endog1.iloc[-1] = 0.
449 endog1.iloc[-1] = 0.
488 endog = endog.iloc[1:]
501 endog1.iloc[-1] = 0.
619 endog = endog.iloc[1:]
632 endog1.iloc[-1] = 0.
686 endog = endog.iloc[1:]
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H A Dtest_models.py68 obs.iloc[:50, :] = np.nan
69 obs.iloc[119:130, :] = np.nan
71 obs.iloc[0:50, 0] = np.nan
72 obs.iloc[119:130, 0] = np.nan
74 obs.iloc[0:50, 0] = np.nan
75 obs.iloc[19:70, 1] = np.nan
76 obs.iloc[39:90, 2] = np.nan
77 obs.iloc[119:130, 0] = np.nan
78 obs.iloc[119:130, 2] = np.nan
/dports/devel/py-dask/dask-2021.11.2/docs/source/
H A Ddataframe-indexing.rst12 DataFrame.iloc
124 indexing with ``.iloc`` inefficient for selecting rows. :meth:`DataFrame.iloc`
130 >>> ddf.iloc[:, [1, 0]]
136 Dask Name: iloc, 2 tasks
138 Trying to select specific rows with ``iloc`` will raise an exception:
142 >>> ddf.iloc[[0, 2], [1]]
145 …ValueError: 'DataFrame.iloc' does not support slicing rows. The indexer must be a 2-tuple whose fi…
/dports/math/py-pandas/pandas-1.2.5/pandas/tests/groupby/aggregate/
H A Dtest_other.py443 result = gb["b"].agg(lambda x: x.iloc[0])
454 result = gb["b"].agg(lambda x: x.iloc[-1] - x.iloc[0])
479 ts = df["B"].iloc[0]
480 assert ts == grouped.nth(0)["B"].iloc[0]
481 assert ts == grouped.head(1)["B"].iloc[0]
482 assert ts == grouped.first()["B"].iloc[0]
485 assert ts == grouped.apply(lambda x: x.iloc[0]).iloc[0, 1]
487 ts = df["B"].iloc[2]
488 assert ts == grouped.last()["B"].iloc[0]
491 assert ts == grouped.apply(lambda x: x.iloc[-1]).iloc[0, 1]
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/dports/lang/racket/racket-8.3/doc/ds-store/
H A Dblueboxes.rktd2 …iloc?)) c (? . 2)) ((c def c (c (? . 0) q struct:ds)) c (? . 1)) ((c def c (c (? . 0) q fwind-b)) …
18       bytes? iloc? fwind?)
20 (struct iloc (x y)
/dports/devel/ga/ga-5.8/global/testing/
H A Dread_only.c84 int i,j,ix,iy,idx,iloc,icnt; in main() local
134 iloc = (i-lo[0])*ld[0]+(j-lo[1]); in main()
135 ptr[iloc] = idx; in main()
179 iloc = (i-lo[0])*ld[0]+(j-lo[1]); in main()
180 if (ptr[iloc] != idx) { in main()
182 printf("p[%d] expected: %d actual: %d\n",me,idx,ptr[iloc]); in main()
238 iloc = (i-lo[0])*ld[0]+(j-lo[1]); in main()
239 if (ptr[iloc] != idx) { in main()
241 printf("p[%d] expected: %d actual: %d\n",me,idx,ptr[iloc]); in main()
/dports/multimedia/vmaf/vmaf-2.3.0/python/test/
H A Dresult_test.py63 self.assertAlmostEqual(np.mean(df_vmaf.iloc[0]['scores']), 40.421899030550769, places=4)
65 self.assertAlmostEqual(np.mean(df_vif.iloc[0]['scores']), 0.156834666667, places=4)
66 self.assertAlmostEqual(np.mean(df_ansnr.iloc[0]['scores']), 7.92623066667, places=4)
67 self.assertAlmostEqual(np.mean(df_motion.iloc[0]['scores']), 12.5548366667, places=4)
74 self.assertEqual(df.iloc[0]['dataset'], 'test')
75 self.assertEqual(df.iloc[0]['content_id'], 0)
76 self.assertEqual(df.iloc[0]['asset_id'], 0)
77 self.assertEqual(df.iloc[0]['ref_name'], 'checkerboard_1920_1080_10_3_0_0.yuv')
78 self.assertEqual(df.iloc[0]['dis_name'], 'checkerboard_1920_1080_10_3_1_0.yuv')
80 df.iloc[0]['asset'],
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/dports/science/cantera/cantera-2.5.1-611-gc4d6ecc15/src/base/
H A Dxml.cpp143 if (iloc == string::npos || iloc == 0) { in findUnbackslashed()
144 return iloc; in findUnbackslashed()
146 char cm1 = s[iloc-1]; in findUnbackslashed()
151 icurrent = iloc + 1; in findUnbackslashed()
153 return iloc; in findUnbackslashed()
197 size_t iloc = s.find(' '); in parseTag() local
198 if (iloc != string::npos) { in parseTag()
199 name = s.substr(0, iloc); in parseTag()
207 iloc = s.find('='); in parseTag()
727 size_t iloc = loc.find('/'); in child() local
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/dports/math/py-pandas/pandas-1.2.5/pandas/tests/frame/indexing/
H A Dtest_categorical.py110 df.iloc[2, 0] = "b"
114 df.iloc[df.index == "j", 0] = "b"
125 df.iloc[2, 0] = "c"
129 df.iloc[2, :] = ["b", 2]
135 df.iloc[2, :] = ["c", 2]
139 df.iloc[2:4, :] = [["b", 2], ["b", 2]]
144 df.iloc[2:4, :] = [["c", 2], ["c", 2]]
149 df.iloc[2:4, 0] = Categorical(["b", "b"], categories=["a", "b"])
155 df.iloc[2:4, 0] = Categorical(list("bb"), categories=list("abc"))
165 df.iloc[2:4, 0] = ["b", "b"]
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/dports/math/py-pandas/pandas-1.2.5/pandas/tests/window/moments/
H A Dtest_moments_rolling_functions.py33 tm.assert_almost_equal(result.iloc[-1], compare_func(series[-50:]))
60 result.iloc[-1, :],
61 frame.iloc[-50:, :].apply(compare_func, axis=0, raw=raw),
146 tm.assert_almost_equal(result.iloc[-1], compare_func(obj[10:-10]))
150 assert isna(result.iloc[23])
151 assert not isna(result.iloc[24])
153 assert not isna(result.iloc[-6])
154 assert isna(result.iloc[-5])
158 assert isna(result.iloc[3])
159 assert notna(result.iloc[4])
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/dports/graphics/py-traitsui/traitsui-7.1.1/traitsui/ui_editors/
H A Ddata_frame_editor.py97 return self.item[self.column_id].iloc[0]
107 dtype = df.iloc[:, self.column].dtype
110 df.iloc[self.row, self.column] = value
145 return getattr(object, trait).iloc[row : row + 1]
157 new_df = pd.concat([df.iloc[:row, :], df.iloc[row + 1 :, :]])
159 new_df = df.iloc[row + 1 :, :]
161 new_df = df.iloc[:row, :]
174 new_df = pd.concat([df.iloc[:row, :], value, df.iloc[row:, :]])
/dports/math/py-pandas/pandas-1.2.5/pandas/tests/series/methods/
H A Dtest_sort_index.py77 backwards = s.iloc[[1, 0]]
96 backwards = s.iloc[[1, 0]]
221 backwards = s.iloc[[1, 0]]
232 backwards = s.iloc[[1, 0]]
244 expected = series.iloc[[2, 3, 0, 1, 5, 4]]
248 expected = series.iloc[[0, 1, 5, 2, 3, 4]]
252 expected = series.iloc[[4, 2, 3, 0, 1, 5]]
317 expected = s.iloc[[0, 1, 2]]
321 expected = s.iloc[[2, 1, 0]]
325 expected = s.iloc[[2, 0, 1]]
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H A Dtest_asof.py17 ts.iloc[15:30] = np.nan
42 ts.iloc[5:10] = np.NaN
43 ts.iloc[15:20] = np.NaN
76 r.iloc[3:5] = np.nan
84 r.iloc[-3:] = np.nan
99 ts.iloc[15:30] = np.nan
117 ts.iloc[5:10] = np.nan
118 ts.iloc[15:20] = np.nan
H A Dtest_nlargest.py113 tm.assert_series_equal(ser.nsmallest(2), ser.iloc[[2, 1]])
114 tm.assert_series_equal(ser.nsmallest(2, keep="last"), ser.iloc[[2, 3]])
116 empty = ser.iloc[0:0]
124 tm.assert_series_equal(ser.nlargest(len(ser)), ser.iloc[[4, 0, 1, 3, 2]])
125 tm.assert_series_equal(ser.nlargest(len(ser) + 1), ser.iloc[[4, 0, 1, 3, 2]])
130 tm.assert_series_equal(ser.nlargest(), ser.iloc[[4, 0, 3, 2]])
131 tm.assert_series_equal(ser.nsmallest(), ser.iloc[[2, 3, 0, 4]])
/dports/science/liggghts/LIGGGHTS-PUBLIC-3.8.0-26-g6e873439/lib/hotint/HotInt_V1/MBS_Interface/
H A Dnode.h77 virtual double& XG(int iloc) = 0;
79 virtual double& XGP(int iloc) = 0;
296 virtual const double& XG(int iloc) const in XG() argument
298 return GetMBS()->GetXact(ltg.Get(iloc)); in XG()
300 virtual double& XG(int iloc) in XG() argument
308 virtual double& XGP(int iloc) in XGP() argument
578 virtual const double& XG(int iloc) const in XG() argument
580 return mbs->GetXact(ltg.Get(iloc)); in XG()
582 virtual double& XG(int iloc) in XG() argument
584 return mbs->GetXact(ltg.Get(iloc)); in XG()
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/dports/math/py-statsmodels/statsmodels-0.13.1/examples/python/
H A Dstatespace_tvpvar_mcmc_cfa.py167 simulated_state_kfs.iloc[:, i] = sim_kfs.simulated_state[0]
172 simulated_state_cfa.iloc[:, i] = sim_cfa.simulated_state[0]
259 y = y.iloc[1:]
387 y_t = augmented.iloc[:, :p]
388 z_t = sm.add_constant(augmented.iloc[:, p:])
488 states.iloc[:, :5].plot(ax=ax)
494 states.iloc[:, 5:10].plot(ax=ax)
500 states.iloc[:, 10:15].plot(ax=ax)
506 states.iloc[:, 15:20].plot(ax=ax)
H A Dglm.py57 print('Total number of trials:', data.endog.iloc[:, 0].sum())
67 means25.iloc[0] = stats.scoreatpercentile(data.exog.iloc[:, 0], 25)
69 means75.iloc[0] = lowinc_75per = stats.scoreatpercentile(
70 data.exog.iloc[:, 0], 75)
86 y = data.endog.iloc[:, 0] / data.endog.sum(1)
H A Dstatespace_local_linear_trend.py201 end='%d-01-01' % df.iloc[-1, 0],
230 predict_ci.iloc[2:, 0],
231 predict_ci.iloc[2:, 1],
238 forecast_ci.iloc[:, 0],
239 forecast_ci.iloc[:, 1],
/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/regression/tests/
H A Dtest_recursive_ls.py247 results_R.iloc[:8][['beta1', 'beta2']], rtol=1e-5)
249 results_R.iloc[7:18][['beta1', 'beta2']])
251 results_R.iloc[17:][['beta1', 'beta2']])
324 results_R.iloc[:8]['rec_resid'])
326 results_R.iloc[7:18]['rec_resid'])
328 results_R.iloc[17:]['rec_resid'])
332 results_stata.iloc[3:]['rr'], atol=1e-5, rtol=1e-5)
374 desired_bounds = results_stata.iloc[3:][['lw', 'uw']].T
398 assert_allclose(res.cusum_squares, results_stata.iloc[3:]['cusum2'],
403 desired_bounds = results_stata.iloc[3:][['lw', 'uw']].T
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/dports/math/py-pandas/pandas-1.2.5/pandas/tests/frame/
H A Dtest_nonunique_indexes.py231 s = df.iloc[:, 0].describe()
301 df.iloc[2, [0, 1, 2]] = np.nan
302 df.iloc[0, 0] = np.nan
303 df.iloc[1, 1] = np.nan
304 df.iloc[:, 3] = np.nan
465 df.iloc[:, i]
478 expected = df.iloc[:, 2]
480 df.iloc[:, 0] = 3
481 tm.assert_series_equal(df.iloc[:, 2], expected)
485 expected = df.iloc[:, 1]
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/dports/graphics/engauge-digitizer/engauge-digitizer-12.2.2/test/
H A DDumpGraphAndScreenCoordinates_test.py77 parsedData = np.array (parseDigFile (title).iloc [:, :2])[0]
78 testData = np.array (engaugeOutput.iloc [:, :2]) [0]
101 parsedData = np.array (parseDigFile (title).iloc [:, :2]) [0]
102 testData = np.array (engaugeOutput.iloc [:, :2]) [0]
125 parsedData = np.array (parseDigFile (title).iloc [:, :2]) [0]
126 testData = np.array (engaugeOutput.iloc [:, :2]) [0]

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