How to use test_call method in pytest-mock
Best Python code snippet using pytest-mock
test_options.py
Source:test_options.py 
1import unittest2import copy3import numpy as np4import numpy.testing as np_test5import pandas as pd6import pandas.testing as pd_test7import warnings8from pyblackscholesanalytics.market.market import MarketEnvironment9from pyblackscholesanalytics.options.options import PlainVanillaOption, DigitalOption10from pyblackscholesanalytics.utils.utils import scalarize11class TestPlainVanillaOption(unittest.TestCase):12 """Class to test public methods of PlainVanillaOption class"""13 def setUp(self) -> None:14 warnings.filterwarnings("ignore")15 # common market environment16 mkt_env = MarketEnvironment()17 # option objects18 self.call_opt = PlainVanillaOption(mkt_env)19 self.put_opt = PlainVanillaOption(mkt_env, option_type="put")20 # pricing parameters21 S_scalar = 10022 S_vector = [90, 100, 110]23 t_scalar_string = "01-06-2020"24 t_date_range = pd.date_range(start="2020-04-19", end="2020-12-21", periods=5)25 # common pricing parameter setup26 common_params = {"np_output": True, "minimization_method": "Least-Squares"}27 # scalar parameters setup28 self.scalar_params = copy.deepcopy(common_params)29 self.scalar_params["S"] = S_scalar30 self.scalar_params["t"] = t_scalar_string31 # vector parameters setup32 self.vector_params = copy.deepcopy(common_params)33 self.vector_params["S"] = S_vector34 self.vector_params["t"] = t_date_range35 # complex pricing parameter setup36 # (S scalar, K and t vector, sigma distributed as Kxt grid, r distributed as Kxt grid)37 K_vector = [75, 85, 90, 95]38 mK = len(K_vector)39 n = 340 sigma_grid_K = np.array([0.1 * (1 + i) for i in range(mK * n)]).reshape(n, mK)41 r_grid_K = np.array([0.01 * (1 + i) for i in range(mK * n)]).reshape(n, mK)42 self.complex_params = {"S": S_vector[0],43 "K": K_vector,44 "t": pd.date_range(start="2020-04-19", end="2020-12-21", periods=n),45 "sigma": sigma_grid_K,46 "r": r_grid_K,47 "np_output": False,48 "minimization_method": "Least-Squares"}49 def test_price_scalar(self):50 """Test price - scalar case"""51 # call52 test_call = scalarize(self.call_opt.price(**self.scalar_params))53 expected_call = 7.54838171681183954 self.assertEqual(test_call, expected_call)55 # put56 test_put = scalarize(self.put_opt.price(**self.scalar_params))57 expected_put = 4.67273050640795958 self.assertEqual(test_put, expected_put)59 def test_price_vector_np(self):60 """Test price - np.ndarray output case"""61 # call62 test_call = self.call_opt.price(**self.vector_params)63 expected_call = np.array([[3.48740247e+00, 8.42523213e+00, 1.55968082e+01],64 [2.53045128e+00, 7.14167587e+00, 1.43217796e+01],65 [1.56095778e+00, 5.72684668e+00, 1.29736886e+01],66 [5.89165298e-01, 4.00605304e+00, 1.14939139e+01],67 [7.21585753e-04, 1.38927959e+00, 1.01386434e+01]])68 np_test.assert_allclose(test_call, expected_call)69 # put70 test_put = self.put_opt.price(**self.vector_params)71 expected_put = np.array([[1.00413306e+01, 4.97916024e+00, 2.15073633e+00],72 [9.90791873e+00, 4.51914332e+00, 1.69924708e+00],73 [9.75553655e+00, 3.92142545e+00, 1.16826738e+00],74 [9.62127704e+00, 3.03816479e+00, 5.26025639e-01],75 [9.86382907e+00, 1.25238707e+00, 1.75090342e-03]])76 np_test.assert_allclose(test_put, expected_put)77 def test_price_vector_df(self):78 """Test price - pd.DataFrame output case"""79 # request Pandas DataFrame as output format80 self.vector_params["np_output"] = False81 # call82 test_call = self.call_opt.price(**self.vector_params)83 expected_call = pd.DataFrame(data=[[3.48740247e+00, 8.42523213e+00, 1.55968082e+01],84 [2.53045128e+00, 7.14167587e+00, 1.43217796e+01],85 [1.56095778e+00, 5.72684668e+00, 1.29736886e+01],86 [5.89165298e-01, 4.00605304e+00, 1.14939139e+01],87 [7.21585753e-04, 1.38927959e+00, 1.01386434e+01]],88 index=self.vector_params["t"],89 columns=self.vector_params["S"])90 expected_call.rename_axis("S", axis='columns', inplace=True)91 expected_call.rename_axis("t", axis='rows', inplace=True)92 pd_test.assert_frame_equal(test_call, expected_call)93 # put94 test_put = self.put_opt.price(**self.vector_params)95 expected_put = pd.DataFrame(data=[[1.00413306e+01, 4.97916024e+00, 2.15073633e+00],96 [9.90791873e+00, 4.51914332e+00, 1.69924708e+00],97 [9.75553655e+00, 3.92142545e+00, 1.16826738e+00],98 [9.62127704e+00, 3.03816479e+00, 5.26025639e-01],99 [9.86382907e+00, 1.25238707e+00, 1.75090342e-03]],100 index=self.vector_params["t"],101 columns=self.vector_params["S"])102 expected_put.rename_axis("S", axis='columns', inplace=True)103 expected_put.rename_axis("t", axis='rows', inplace=True)104 pd_test.assert_frame_equal(test_put, expected_put)105 def test_PnL_scalar(self):106 """Test P&L - scalar case"""107 # call108 test_call = scalarize(self.call_opt.PnL(**self.scalar_params))109 expected_call = 4.060979245868182110 self.assertEqual(test_call, expected_call)111 # put112 test_put = scalarize(self.put_opt.PnL(**self.scalar_params))113 expected_put = -5.368600081057167114 self.assertEqual(test_put, expected_put)115 def test_PnL_vector_np(self):116 """Test P&L - np.ndarray output case"""117 # call118 test_call = self.call_opt.PnL(**self.vector_params)119 expected_call = np.array([[0., 4.93782966, 12.10940574],120 [-0.95695119, 3.6542734, 10.83437716],121 [-1.92644469, 2.2394442, 9.48628613],122 [-2.89823717, 0.51865057, 8.00651142],123 [-3.48668089, -2.09812288, 6.65124095]])124 np_test.assert_allclose(test_call, expected_call)125 # put126 test_put = self.put_opt.PnL(**self.vector_params)127 expected_put = np.array([[0., -5.06217034, -7.89059426],128 [-0.13341186, -5.52218727, -8.3420835],129 [-0.28579403, -6.11990513, -8.87306321],130 [-0.42005355, -7.0031658, -9.51530495],131 [-0.17750152, -8.78894351, -10.03957968]])132 np_test.assert_allclose(test_put, expected_put)133 def test_PnL_vector_df(self):134 """Test P&L - pd.DataFrame output case"""135 # request Pandas DataFrame as output format136 self.vector_params["np_output"] = False137 # call138 test_call = self.call_opt.PnL(**self.vector_params)139 expected_call = pd.DataFrame(data=[[0., 4.93782966, 12.10940574],140 [-0.95695119, 3.6542734, 10.83437716],141 [-1.92644469, 2.2394442, 9.48628613],142 [-2.89823717, 0.51865057, 8.00651142],143 [-3.48668089, -2.09812288, 6.65124095]],144 index=self.vector_params["t"],145 columns=self.vector_params["S"])146 expected_call.rename_axis("S", axis='columns', inplace=True)147 expected_call.rename_axis("t", axis='rows', inplace=True)148 pd_test.assert_frame_equal(test_call, expected_call)149 # put150 test_put = self.put_opt.PnL(**self.vector_params)151 expected_put = pd.DataFrame(data=[[0., -5.06217034, -7.89059426],152 [-0.13341186, -5.52218727, -8.3420835],153 [-0.28579403, -6.11990513, -8.87306321],154 [-0.42005355, -7.0031658, -9.51530495],155 [-0.17750152, -8.78894351, -10.03957968]],156 index=self.vector_params["t"],157 columns=self.vector_params["S"])158 expected_put.rename_axis("S", axis='columns', inplace=True)159 expected_put.rename_axis("t", axis='rows', inplace=True)160 pd_test.assert_frame_equal(test_put, expected_put)161 def test_delta_scalar(self):162 """Test Delta - scalar case"""163 # call164 test_call = scalarize(self.call_opt.delta(**self.scalar_params))165 expected_call = 0.6054075531684143166 self.assertEqual(test_call, expected_call)167 # put168 test_put = scalarize(self.put_opt.delta(**self.scalar_params))169 expected_put = -0.3945924468315857170 self.assertEqual(test_put, expected_put)171 def test_delta_vector_np(self):172 """Test Delta - np.ndarray output case"""173 # call174 test_call = self.call_opt.delta(**self.vector_params)175 expected_call = np.array([[3.68466757e-01, 6.15283790e-01, 8.05697003e-01],176 [3.20097309e-01, 6.00702480e-01, 8.18280131e-01],177 [2.54167521e-01, 5.83663527e-01, 8.41522350e-01],178 [1.49152172e-01, 5.61339299e-01, 8.91560577e-01],179 [8.89758553e-04, 5.23098767e-01, 9.98343116e-01]])180 np_test.assert_allclose(test_call, expected_call)181 # put182 test_put = self.put_opt.delta(**self.vector_params)183 expected_put = np.array([[-0.63153324, -0.38471621, -0.194303],184 [-0.67990269, -0.39929752, -0.18171987],185 [-0.74583248, -0.41633647, -0.15847765],186 [-0.85084783, -0.4386607, -0.10843942],187 [-0.99911024, -0.47690123, -0.00165688]])188 np_test.assert_allclose(test_put, expected_put, rtol=5e-6)189 def test_delta_vector_df(self):190 """Test Delta - pd.DataFrame output case"""191 # request Pandas DataFrame as output format192 self.vector_params["np_output"] = False193 # call194 test_call = self.call_opt.delta(**self.vector_params)195 expected_call = pd.DataFrame(data=[[3.68466757e-01, 6.15283790e-01, 8.05697003e-01],196 [3.20097309e-01, 6.00702480e-01, 8.18280131e-01],197 [2.54167521e-01, 5.83663527e-01, 8.41522350e-01],198 [1.49152172e-01, 5.61339299e-01, 8.91560577e-01],199 [8.89758553e-04, 5.23098767e-01, 9.98343116e-01]],200 index=self.vector_params["t"],201 columns=self.vector_params["S"])202 expected_call.rename_axis("S", axis='columns', inplace=True)203 expected_call.rename_axis("t", axis='rows', inplace=True)204 pd_test.assert_frame_equal(test_call, expected_call)205 # put206 test_put = self.put_opt.delta(**self.vector_params)207 expected_put = pd.DataFrame(data=[[-0.63153324, -0.38471621, -0.194303],208 [-0.67990269, -0.39929752, -0.18171987],209 [-0.74583248, -0.41633647, -0.15847765],210 [-0.85084783, -0.4386607, -0.10843942],211 [-0.99911024, -0.47690123, -0.00165688]],212 index=self.vector_params["t"],213 columns=self.vector_params["S"])214 expected_put.rename_axis("S", axis='columns', inplace=True)215 expected_put.rename_axis("t", axis='rows', inplace=True)216 pd_test.assert_frame_equal(test_put, expected_put)217 def test_gamma_scalar(self):218 """Test Gamma - scalar case"""219 # call220 test_call = scalarize(self.call_opt.gamma(**self.scalar_params))221 expected_call = 0.025194958512498786222 self.assertEqual(test_call, expected_call)223 # put224 test_put = scalarize(self.put_opt.gamma(**self.scalar_params))225 expected_put = copy.deepcopy(expected_call)226 self.assertEqual(test_put, expected_put)227 # assert call and put gamma coincide228 self.assertEqual(test_call, test_put)229 def test_gamma_vector_np(self):230 """Test Gamma - np.ndarray output case"""231 # call232 test_call = self.call_opt.gamma(**self.vector_params)233 expected_call = np.array([[0.02501273, 0.02281654, 0.01493167],234 [0.02725456, 0.02648423, 0.01645793],235 [0.02950243, 0.03231528, 0.01820714],236 [0.02925862, 0.0446913, 0.01918121],237 [0.00101516, 0.12030889, 0.00146722]])238 np_test.assert_allclose(test_call, expected_call, rtol=5e-6)239 # put240 test_put = self.put_opt.gamma(**self.vector_params)241 expected_put = copy.deepcopy(expected_call)242 np_test.assert_allclose(test_put, expected_put, rtol=5e-6)243 # assert call and put gamma coincide244 np_test.assert_allclose(test_call, test_put)245 def test_gamma_vector_df(self):246 """Test Gamma - pd.DataFrame output case"""247 # request Pandas DataFrame as output format248 self.vector_params["np_output"] = False249 # call250 test_call = self.call_opt.gamma(**self.vector_params)251 expected_call = pd.DataFrame(data=[[0.02501273, 0.02281654, 0.01493167],252 [0.02725456, 0.02648423, 0.01645793],253 [0.02950243, 0.03231528, 0.01820714],254 [0.02925862, 0.0446913, 0.01918121],255 [0.00101516, 0.12030889, 0.00146722]],256 index=self.vector_params["t"],257 columns=self.vector_params["S"])258 expected_call.rename_axis("S", axis='columns', inplace=True)259 expected_call.rename_axis("t", axis='rows', inplace=True)260 pd_test.assert_frame_equal(test_call, expected_call)261 # put262 test_put = self.put_opt.gamma(**self.vector_params)263 expected_put = copy.deepcopy(expected_call)264 pd_test.assert_frame_equal(test_put, expected_put)265 # assert call and put gamma coincide266 pd_test.assert_frame_equal(test_call, test_put)267 def test_vega_scalar(self):268 """Test Vega - scalar case"""269 # call270 test_call = scalarize(self.call_opt.vega(**self.scalar_params))271 expected_call = 0.29405622811847903272 self.assertEqual(test_call, expected_call)273 # put274 test_put = scalarize(self.put_opt.vega(**self.scalar_params))275 expected_put = copy.deepcopy(expected_call)276 self.assertEqual(test_put, expected_put)277 # assert call and put vega coincide278 self.assertEqual(test_call, test_put)279 def test_vega_vector_np(self):280 """Test Vega - np.ndarray output case"""281 # call282 test_call = self.call_opt.vega(**self.vector_params)283 expected_call = np.array([[0.28419942, 0.32005661, 0.2534375],284 [0.23467293, 0.28153094, 0.21168961],285 [0.17415326, 0.23550311, 0.16055207],286 [0.09220072, 0.17386752, 0.09029355],287 [0.00045056, 0.06592268, 0.00097279]])288 np_test.assert_allclose(test_call, expected_call, rtol=1e-5)289 # put290 test_put = self.put_opt.vega(**self.vector_params)291 expected_put = copy.deepcopy(expected_call)292 np_test.assert_allclose(test_put, expected_put, rtol=1e-5)293 # assert call and put vega coincide294 np_test.assert_allclose(test_call, test_put)295 def test_vega_vector_df(self):296 """Test Vega - pd.DataFrame output case"""297 # request Pandas DataFrame as output format298 self.vector_params["np_output"] = False299 # call300 test_call = self.call_opt.vega(**self.vector_params)301 expected_call = pd.DataFrame(data=[[0.28419942, 0.32005661, 0.2534375],302 [0.23467293, 0.28153094, 0.21168961],303 [0.17415326, 0.23550311, 0.16055207],304 [0.09220072, 0.17386752, 0.09029355],305 [0.00045056, 0.06592268, 0.00097279]],306 index=self.vector_params["t"],307 columns=self.vector_params["S"])308 expected_call.rename_axis("S", axis='columns', inplace=True)309 expected_call.rename_axis("t", axis='rows', inplace=True)310 pd_test.assert_frame_equal(test_call, expected_call, check_less_precise=True)311 # put312 test_put = self.put_opt.vega(**self.vector_params)313 expected_put = copy.deepcopy(expected_call)314 pd_test.assert_frame_equal(test_put, expected_put, check_less_precise=True)315 # assert call and put vega coincide316 pd_test.assert_frame_equal(test_call, test_put)317 def test_theta_scalar(self):318 """Test Theta - scalar case"""319 # call320 test_call = scalarize(self.call_opt.theta(**self.scalar_params))321 expected_call = -0.021064685979455443322 self.assertEqual(test_call, expected_call)323 # put324 test_put = scalarize(self.put_opt.theta(**self.scalar_params))325 expected_put = -0.007759980665812141326 self.assertEqual(test_put, expected_put)327 def test_theta_vector_np(self):328 """Test Theta - np.ndarray output case"""329 # call330 test_call = self.call_opt.theta(**self.vector_params)331 expected_call = np.array([[-0.01516655, -0.01977662, -0.01990399],332 [-0.01569631, -0.02176239, -0.0212802],333 [-0.01601397, -0.02491789, -0.02297484],334 [-0.01474417, -0.03162919, -0.02457737],335 [-0.00046144, -0.0728981, -0.01462746]])336 np_test.assert_allclose(test_call, expected_call, rtol=5e-4)337 # put338 test_put = self.put_opt.theta(**self.vector_params)339 expected_put = np.array([[-0.00193999, -0.00655005, -0.00667743],340 [-0.00235693, -0.00842301, -0.00794082],341 [-0.00256266, -0.01146658, -0.00952353],342 [-0.00117813, -0.01806315, -0.01101133],343 [0.01321844, -0.05921823, -0.00094758]])344 np_test.assert_allclose(test_put, expected_put, rtol=1e-5)345 def test_theta_vector_df(self):346 """Test Theta - pd.DataFrame output case"""347 # request Pandas DataFrame as output format348 self.vector_params["np_output"] = False349 # call350 test_call = self.call_opt.theta(**self.vector_params)351 expected_call = pd.DataFrame(data=[[-0.01516655, -0.01977662, -0.01990399],352 [-0.01569631, -0.02176239, -0.0212802],353 [-0.01601397, -0.02491789, -0.02297484],354 [-0.01474417, -0.03162919, -0.02457737],355 [-0.00046144, -0.0728981, -0.01462746]],356 index=self.vector_params["t"],357 columns=self.vector_params["S"])358 expected_call.rename_axis("S", axis='columns', inplace=True)359 expected_call.rename_axis("t", axis='rows', inplace=True)360 pd_test.assert_frame_equal(test_call, expected_call, check_less_precise=True)361 # put362 test_put = self.put_opt.theta(**self.vector_params)363 expected_put = pd.DataFrame(data=[[-0.00193999, -0.00655005, -0.00667743],364 [-0.00235693, -0.00842301, -0.00794082],365 [-0.00256266, -0.01146658, -0.00952353],366 [-0.00117813, -0.01806315, -0.01101133],367 [0.01321844, -0.05921823, -0.00094758]],368 index=self.vector_params["t"],369 columns=self.vector_params["S"])370 expected_put.rename_axis("S", axis='columns', inplace=True)371 expected_put.rename_axis("t", axis='rows', inplace=True)372 pd_test.assert_frame_equal(test_put, expected_put, check_less_precise=True)373 def test_rho_scalar(self):374 """Test Rho - scalar case"""375 # call376 test_call = scalarize(self.call_opt.rho(**self.scalar_params))377 expected_call = 0.309243166487844378 self.assertEqual(test_call, expected_call)379 # put380 test_put = scalarize(self.put_opt.rho(**self.scalar_params))381 expected_put = -0.2575372798733608382 self.assertEqual(test_put, expected_put)383 def test_rho_vector_np(self):384 """Test Rho - np.ndarray output case"""385 # call386 test_call = self.call_opt.rho(**self.vector_params)387 expected_call = np.array([[2.08128741e-01, 3.72449469e-01, 5.12209444e-01],388 [1.39670999e-01, 2.81318986e-01, 4.02292404e-01],389 [7.76651463e-02, 1.91809707e-01, 2.90026614e-01],390 [2.49657984e-02, 1.01399432e-01, 1.68411513e-01],391 [2.17415573e-05, 1.39508485e-02, 2.73093423e-02]])392 np_test.assert_allclose(test_call, expected_call, rtol=1e-5)393 # put394 test_put = self.put_opt.rho(**self.vector_params)395 expected_put = np.array([[-4.69071412e-01, -3.04750685e-01, -1.64990710e-01],396 [-3.77896910e-01, -2.36248923e-01, -1.15275505e-01],397 [-2.80139757e-01, -1.65995197e-01, -6.77782897e-02],398 [-1.67672008e-01, -9.12383748e-02, -2.42262934e-02],399 [-2.73380139e-02, -1.34089069e-02, -5.04131783e-05]])400 np_test.assert_allclose(test_put, expected_put, rtol=1e-5)401 def test_rho_vector_df(self):402 """Test Theta - pd.DataFrame output case"""403 # request Pandas DataFrame as output format404 self.vector_params["np_output"] = False405 # call406 test_call = self.call_opt.rho(**self.vector_params)407 expected_call = pd.DataFrame(data=[[2.08128741e-01, 3.72449469e-01, 5.12209444e-01],408 [1.39670999e-01, 2.81318986e-01, 4.02292404e-01],409 [7.76651463e-02, 1.91809707e-01, 2.90026614e-01],410 [2.49657984e-02, 1.01399432e-01, 1.68411513e-01],411 [2.17415573e-05, 1.39508485e-02, 2.73093423e-02]],412 index=self.vector_params["t"],413 columns=self.vector_params["S"])414 expected_call.rename_axis("S", axis='columns', inplace=True)415 expected_call.rename_axis("t", axis='rows', inplace=True)416 pd_test.assert_frame_equal(test_call, expected_call, check_less_precise=True)417 # put418 test_put = self.put_opt.rho(**self.vector_params)419 expected_put = pd.DataFrame(data=[[-4.69071412e-01, -3.04750685e-01, -1.64990710e-01],420 [-3.77896910e-01, -2.36248923e-01, -1.15275505e-01],421 [-2.80139757e-01, -1.65995197e-01, -6.77782897e-02],422 [-1.67672008e-01, -9.12383748e-02, -2.42262934e-02],423 [-2.73380139e-02, -1.34089069e-02, -5.04131783e-05]],424 index=self.vector_params["t"],425 columns=self.vector_params["S"])426 expected_put.rename_axis("S", axis='columns', inplace=True)427 expected_put.rename_axis("t", axis='rows', inplace=True)428 pd_test.assert_frame_equal(test_put, expected_put, check_less_precise=True)429 def test_Implied_Vol_scalar(self):430 """Test Implied Volatility - scalar case"""431 # call432 test_call = scalarize(self.call_opt.implied_volatility(**self.scalar_params))433 expected_call = 0.2434 self.assertAlmostEqual(test_call, expected_call)435 # put436 test_put = scalarize(self.put_opt.implied_volatility(**self.scalar_params))437 expected_put = 0.2438 self.assertAlmostEqual(test_put, expected_put)439 def test_Implied_Vol_vector_np(self):440 """Test Implied Volatility - np.ndarray output case"""441 # call442 test_call = self.call_opt.implied_volatility(**self.vector_params)443 expected_call = 0.2 + np.zeros_like(test_call)444 np_test.assert_allclose(test_call, expected_call, rtol=1e-5)445 # put446 test_put = self.put_opt.implied_volatility(**self.vector_params)447 expected_put = 0.2 + np.zeros_like(test_put)448 np_test.assert_allclose(test_put, expected_put, rtol=1e-5)449 def test_Implied_Vol_vector_df(self):450 """Test Implied Volatility - pd.DataFrame output case"""451 # request Pandas DataFrame as output format452 self.vector_params["np_output"] = False453 # call454 test_call = self.call_opt.implied_volatility(**self.vector_params)455 expected_call = pd.DataFrame(data=0.2 + np.zeros_like(test_call),456 index=self.vector_params["t"],457 columns=self.vector_params["S"])458 expected_call.rename_axis("S", axis='columns', inplace=True)459 expected_call.rename_axis("t", axis='rows', inplace=True)460 pd_test.assert_frame_equal(test_call, expected_call, check_less_precise=True)461 # put462 test_put = self.put_opt.implied_volatility(**self.vector_params)463 expected_put = pd.DataFrame(data=0.2 + np.zeros_like(test_put),464 index=self.vector_params["t"],465 columns=self.vector_params["S"])466 expected_put.rename_axis("S", axis='columns', inplace=True)467 expected_put.rename_axis("t", axis='rows', inplace=True)468 pd_test.assert_frame_equal(test_put, expected_put, check_less_precise=True)469 def test_complex_parameters_setup(self):470 """471 Test complex parameter setup:472 (S scalar, K and t vector, sigma distributed as Kxt grid, r distributed as Kxt grid)473 """474 # call475 test_call_price = self.call_opt.price(**self.complex_params)476 test_call_PnL = self.call_opt.PnL(**self.complex_params)477 test_call_delta = self.call_opt.delta(**self.complex_params)478 test_call_gamma = self.call_opt.gamma(**self.complex_params)479 test_call_vega = self.call_opt.vega(**self.complex_params)480 test_call_theta = self.call_opt.theta(**self.complex_params)481 test_call_rho = self.call_opt.rho(**self.complex_params)482 test_call_iv = self.call_opt.implied_volatility(**self.complex_params)483 expected_call_price = pd.DataFrame(data=[[15.55231058, 9.40714796, 9.87150919, 10.97983523],484 [20.05777231, 16.15277891, 16.02977848, 16.27588191],485 [15.81433361, 8.75227505, 6.65476799, 5.19785143]],486 index=self.complex_params["t"],487 columns=self.complex_params["K"])488 expected_call_price.rename_axis("K", axis='columns', inplace=True)489 expected_call_price.rename_axis("t", axis='rows', inplace=True)490 expected_call_PnL = pd.DataFrame(data=[[12.06490811, 5.91974549, 6.38410672, 7.49243276],491 [16.57036984, 12.66537644, 12.54237601, 12.78847944],492 [12.32693114, 5.26487258, 3.16736552, 1.71044896]],493 index=self.complex_params["t"],494 columns=self.complex_params["K"])495 expected_call_PnL.rename_axis("K", axis='columns', inplace=True)496 expected_call_PnL.rename_axis("t", axis='rows', inplace=True)497 expected_call_delta = pd.DataFrame(data=[[0.98935079, 0.69453583, 0.58292013, 0.53579465],498 [0.79256302, 0.65515368, 0.60705014, 0.57529078],499 [0.90573251, 0.6717088, 0.54283905, 0.43788167]],500 index=self.complex_params["t"],501 columns=self.complex_params["K"])502 expected_call_delta.rename_axis("K", axis='columns', inplace=True)503 expected_call_delta.rename_axis("t", axis='rows', inplace=True)504 expected_call_gamma = pd.DataFrame(data=[[0.00373538, 0.02325203, 0.01726052, 0.01317896],505 [0.01053321, 0.01130107, 0.01011038, 0.0090151],506 [0.01253481, 0.0242596, 0.02420515, 0.02204576]],507 index=self.complex_params["t"],508 columns=self.complex_params["K"])509 expected_call_gamma.rename_axis("K", axis='columns', inplace=True)510 expected_call_gamma.rename_axis("t", axis='rows', inplace=True)511 expected_call_vega = pd.DataFrame(data=[[0.02122104, 0.26419398, 0.29417607, 0.29948378],512 [0.15544424, 0.20013116, 0.20888592, 0.2128651],513 [0.02503527, 0.05383637, 0.05908709, 0.05870816]],514 index=self.complex_params["t"],515 columns=self.complex_params["K"])516 expected_call_vega.rename_axis("K", axis='columns', inplace=True)517 expected_call_vega.rename_axis("t", axis='rows', inplace=True)518 expected_call_theta = pd.DataFrame(data=[[-0.00242788, -0.01322973, -0.02073753, -0.02747845],519 [-0.03624253, -0.0521798, -0.06237363, -0.07180046],520 [-0.12885912, -0.28334665, -0.33769702, -0.36349655]],521 index=self.complex_params["t"],522 columns=self.complex_params["K"])523 expected_call_theta.rename_axis("K", axis='columns', inplace=True)524 expected_call_theta.rename_axis("t", axis='rows', inplace=True)525 expected_call_rho = pd.DataFrame(data=[[0.51543152, 0.37243495, 0.29872256, 0.26120194],526 [0.18683002, 0.15599644, 0.14066931, 0.12935721],527 [0.01800044, 0.0141648, 0.01156185, 0.00937301]],528 index=self.complex_params["t"],529 columns=self.complex_params["K"])530 expected_call_rho.rename_axis("K", axis='columns', inplace=True)531 expected_call_rho.rename_axis("t", axis='rows', inplace=True)532 expected_call_iv = pd.DataFrame(data=self.complex_params["sigma"],533 index=self.complex_params["t"],534 columns=self.complex_params["K"])535 expected_call_iv.rename_axis("K", axis='columns', inplace=True)536 expected_call_iv.rename_axis("t", axis='rows', inplace=True)537 pd_test.assert_frame_equal(test_call_price, expected_call_price)538 pd_test.assert_frame_equal(test_call_PnL, expected_call_PnL)539 pd_test.assert_frame_equal(test_call_delta, expected_call_delta)540 pd_test.assert_frame_equal(test_call_gamma, expected_call_gamma)541 pd_test.assert_frame_equal(test_call_vega, expected_call_vega)542 pd_test.assert_frame_equal(test_call_theta, expected_call_theta)543 pd_test.assert_frame_equal(test_call_rho, expected_call_rho)544 pd_test.assert_frame_equal(test_call_iv, expected_call_iv)545 # put546 test_put_price = self.put_opt.price(**self.complex_params)547 test_put_PnL = self.put_opt.PnL(**self.complex_params)548 test_put_delta = self.put_opt.delta(**self.complex_params)549 test_put_gamma = self.put_opt.gamma(**self.complex_params)550 test_put_vega = self.put_opt.vega(**self.complex_params)551 test_put_theta = self.put_opt.theta(**self.complex_params)552 test_put_rho = self.put_opt.rho(**self.complex_params)553 test_put_iv = self.put_opt.implied_volatility(**self.complex_params)554 expected_put_price = pd.DataFrame(data=[[0.02812357, 3.22314287, 7.9975943, 13.35166847],555 [3.70370639, 9.31459014, 13.76319167, 18.54654119],556 [0.62962992, 3.51971706, 6.38394341, 9.88603552]],557 index=self.complex_params["t"],558 columns=self.complex_params["K"])559 expected_put_price.rename_axis("K", axis='columns', inplace=True)560 expected_put_price.rename_axis("t", axis='rows', inplace=True)561 expected_put_PnL = pd.DataFrame(data=[[-10.01320701, -6.81818772, -2.04373628, 3.31033788],562 [-6.3376242, -0.72674045, 3.72186108, 8.5052106],563 [-9.41170067, -6.52161353, -3.65738717, -0.15529507]],564 index=self.complex_params["t"],565 columns=self.complex_params["K"])566 expected_put_PnL.rename_axis("K", axis='columns', inplace=True)567 expected_put_PnL.rename_axis("t", axis='rows', inplace=True)568 expected_put_delta = pd.DataFrame(data=[[-0.01064921, -0.30546417, -0.41707987, -0.46420535],569 [-0.20743698, -0.34484632, -0.39294986, -0.42470922],570 [-0.09426749, -0.3282912, -0.45716095, -0.56211833]],571 index=self.complex_params["t"],572 columns=self.complex_params["K"])573 expected_put_delta.rename_axis("K", axis='columns', inplace=True)574 expected_put_delta.rename_axis("t", axis='rows', inplace=True)575 expected_put_gamma = copy.deepcopy(expected_call_gamma)576 expected_put_vega = copy.deepcopy(expected_call_vega)577 expected_put_theta = pd.DataFrame(data=[[-0.00038744, -0.00863707, -0.01349429, -0.01735551],578 [-0.02615404, -0.03850937, -0.04554804, -0.05157676],579 [-0.11041151, -0.26012269, -0.31065535, -0.33236619]],580 index=self.complex_params["t"],581 columns=self.complex_params["K"])582 expected_put_theta.rename_axis("K", axis='columns', inplace=True)583 expected_put_theta.rename_axis("t", axis='rows', inplace=True)584 expected_put_rho = pd.DataFrame(data=[[-0.00691938, -0.21542518, -0.31936724, -0.38666626],585 [-0.08152366, -0.14703153, -0.17901683, -0.2068619],586 [-0.00249691, -0.00905916, -0.01302149, -0.01656895]],587 index=self.complex_params["t"],588 columns=self.complex_params["K"])589 expected_put_rho.rename_axis("K", axis='columns', inplace=True)590 expected_put_rho.rename_axis("t", axis='rows', inplace=True)591 expected_put_iv = pd.DataFrame(data=self.complex_params["sigma"],592 index=self.complex_params["t"],593 columns=self.complex_params["K"])594 expected_put_iv.rename_axis("K", axis='columns', inplace=True)595 expected_put_iv.rename_axis("t", axis='rows', inplace=True)596 pd_test.assert_frame_equal(test_put_price, expected_put_price)597 pd_test.assert_frame_equal(test_put_PnL, expected_put_PnL)598 pd_test.assert_frame_equal(test_put_delta, expected_put_delta)599 pd_test.assert_frame_equal(test_put_gamma, expected_put_gamma)600 pd_test.assert_frame_equal(test_put_vega, expected_put_vega)601 pd_test.assert_frame_equal(test_put_theta, expected_put_theta, check_less_precise=True)602 pd_test.assert_frame_equal(test_put_rho, expected_put_rho)603 pd_test.assert_frame_equal(test_put_iv, expected_put_iv)604 # test gamma and vega consistency605 pd_test.assert_frame_equal(test_call_gamma, test_put_gamma)606 pd_test.assert_frame_equal(test_call_vega, test_put_vega)607class TestDigitalOption(unittest.TestCase):608 """Class to test public methods of DigitalOption class"""609 def setUp(self) -> None:610 warnings.filterwarnings("ignore")611 # common market environment612 mkt_env = MarketEnvironment()613 # option objects614 self.call_opt = DigitalOption(mkt_env)615 self.put_opt = DigitalOption(mkt_env, option_type="put")616 # pricing parameters617 S_scalar = 100618 S_vector = [90, 100, 110]619 t_scalar_string = "01-06-2020"620 t_date_range = pd.date_range(start="2020-04-19", end="2020-12-21", periods=5)621 # common pricing parameter setup622 common_params = {"np_output": True, "minimization_method": "Least-Squares"}623 # scalar parameters setup624 self.scalar_params = copy.deepcopy(common_params)625 self.scalar_params["S"] = S_scalar626 self.scalar_params["t"] = t_scalar_string627 # vector parameters setup628 self.vector_params = copy.deepcopy(common_params)629 self.vector_params["S"] = S_vector630 self.vector_params["t"] = t_date_range631 # complex pricing parameter setup632 # (S scalar, K and t vector, sigma distributed as Kxt grid, r distributed as Kxt grid)633 K_vector = [75, 85, 90, 95]634 mK = len(K_vector)635 n = 3636 sigma_grid_K = np.array([0.1 * (1 + i) for i in range(mK * n)]).reshape(n, mK)637 r_grid_K = np.array([0.01 * (1 + i) for i in range(mK * n)]).reshape(n, mK)638 self.complex_params = {"S": S_vector[0],639 "K": K_vector,640 "t": pd.date_range(start="2020-04-19", end="2020-12-21", periods=n),641 "sigma": sigma_grid_K,642 "r": r_grid_K,643 "np_output": False,644 "minimization_method": "Least-Squares"}645 def test_price_scalar(self):646 """Test price - scalar case"""647 # call648 test_call = scalarize(self.call_opt.price(**self.scalar_params))649 expected_call = 0.529923736000296650 self.assertEqual(test_call, expected_call)651 # put652 test_put = scalarize(self.put_opt.price(**self.scalar_params))653 expected_put = 0.4413197518956652654 self.assertEqual(test_put, expected_put)655 def test_price_vector_np(self):656 """Test price - np.ndarray output case"""657 # call658 test_call = self.call_opt.price(**self.vector_params)659 expected_call = np.array([[2.96746057e-01, 5.31031469e-01, 7.30298621e-01],660 [2.62783065e-01, 5.29285722e-01, 7.56890348e-01],661 [2.13141191e-01, 5.26395060e-01, 7.95937699e-01],662 [1.28345302e-01, 5.21278768e-01, 8.65777496e-01],663 [7.93566840e-04, 5.09205971e-01, 9.96790994e-01]])664 np_test.assert_allclose(test_call, expected_call)665 # put666 test_put = self.put_opt.price(**self.vector_params)667 expected_put = np.array([[0.66879322, 0.43450781, 0.23524066],668 [0.71099161, 0.44448895, 0.21688433],669 [0.7688046, 0.45555073, 0.18600809],670 [0.86197582, 0.46904235, 0.12454362],671 [0.99783751, 0.4894251, 0.00184008]])672 np_test.assert_allclose(test_put, expected_put, rtol=1e-6)673 def test_price_vector_df(self):674 """Test price - pd.DataFrame output case"""675 # request Pandas DataFrame as output format676 self.vector_params["np_output"] = False677 # call678 test_call = self.call_opt.price(**self.vector_params)679 expected_call = pd.DataFrame(data=[[2.96746057e-01, 5.31031469e-01, 7.30298621e-01],680 [2.62783065e-01, 5.29285722e-01, 7.56890348e-01],681 [2.13141191e-01, 5.26395060e-01, 7.95937699e-01],682 [1.28345302e-01, 5.21278768e-01, 8.65777496e-01],683 [7.93566840e-04, 5.09205971e-01, 9.96790994e-01]],684 index=self.vector_params["t"],685 columns=self.vector_params["S"])686 expected_call.rename_axis("S", axis='columns', inplace=True)687 expected_call.rename_axis("t", axis='rows', inplace=True)688 pd_test.assert_frame_equal(test_call, expected_call)689 # put690 test_put = self.put_opt.price(**self.vector_params)691 expected_put = pd.DataFrame(data=[[0.66879322, 0.43450781, 0.23524066],692 [0.71099161, 0.44448895, 0.21688433],693 [0.7688046, 0.45555073, 0.18600809],694 [0.86197582, 0.46904235, 0.12454362],695 [0.99783751, 0.4894251, 0.00184008]],696 index=self.vector_params["t"],697 columns=self.vector_params["S"])698 expected_put.rename_axis("S", axis='columns', inplace=True)699 expected_put.rename_axis("t", axis='rows', inplace=True)700 pd_test.assert_frame_equal(test_put, expected_put)701 def test_PnL_scalar(self):702 """Test P&L - scalar case"""703 # call704 test_call = scalarize(self.call_opt.PnL(**self.scalar_params))705 expected_call = 0.23317767915072352706 self.assertEqual(test_call, expected_call)707 # put708 test_put = scalarize(self.put_opt.PnL(**self.scalar_params))709 expected_put = -0.22747347241997717710 self.assertEqual(test_put, expected_put)711 def test_PnL_vector_np(self):712 """Test P&L - np.ndarray output case"""713 # call714 test_call = self.call_opt.PnL(**self.vector_params)715 expected_call = np.array([[0., 0.23428541, 0.43355256],716 [-0.03396299, 0.23253966, 0.46014429],717 [-0.08360487, 0.229649, 0.49919164],718 [-0.16840076, 0.22453271, 0.56903144],719 [-0.29595249, 0.21245991, 0.70004494]])720 np_test.assert_allclose(test_call, expected_call)721 # put722 test_put = self.put_opt.PnL(**self.vector_params)723 expected_put = np.array([[0., -0.23428541, -0.43355256],724 [0.04219839, -0.22430427, -0.4519089],725 [0.10001137, -0.2132425, -0.48278514],726 [0.19318259, -0.19975088, -0.5442496],727 [0.32904428, -0.17936812, -0.66695314]])728 np_test.assert_allclose(test_put, expected_put, rtol=1e-6)729 def test_PnL_vector_df(self):730 """Test P&L - pd.DataFrame output case"""731 # request Pandas DataFrame as output format732 self.vector_params["np_output"] = False733 # call734 test_call = self.call_opt.PnL(**self.vector_params)735 expected_call = pd.DataFrame(data=[[0., 0.23428541, 0.43355256],736 [-0.03396299, 0.23253966, 0.46014429],737 [-0.08360487, 0.229649, 0.49919164],738 [-0.16840076, 0.22453271, 0.56903144],739 [-0.29595249, 0.21245991, 0.70004494]],740 index=self.vector_params["t"],741 columns=self.vector_params["S"])742 expected_call.rename_axis("S", axis='columns', inplace=True)743 expected_call.rename_axis("t", axis='rows', inplace=True)744 pd_test.assert_frame_equal(test_call, expected_call)745 # put746 test_put = self.put_opt.PnL(**self.vector_params)747 expected_put = pd.DataFrame(data=[[0., -0.23428541, -0.43355256],748 [0.04219839, -0.22430427, -0.4519089],749 [0.10001137, -0.2132425, -0.48278514],750 [0.19318259, -0.19975088, -0.5442496],751 [0.32904428, -0.17936812, -0.66695314]],752 index=self.vector_params["t"],753 columns=self.vector_params["S"])754 expected_put.rename_axis("S", axis='columns', inplace=True)755 expected_put.rename_axis("t", axis='rows', inplace=True)756 pd_test.assert_frame_equal(test_put, expected_put)757 def test_delta_scalar(self):758 """Test Delta - scalar case"""759 # call760 test_call = scalarize(self.call_opt.delta(**self.scalar_params))761 expected_call = 0.025194958512498786762 self.assertEqual(test_call, expected_call)763 # put764 test_put = scalarize(self.put_opt.delta(**self.scalar_params))765 expected_put = copy.deepcopy(-expected_call)766 self.assertEqual(test_put, expected_put)767 # assert call and put delta consistency768 self.assertEqual(test_call, -test_put)769 def test_delta_vector_np(self):770 """Test Delta - np.ndarray output case"""771 # call772 test_call = self.call_opt.delta(**self.vector_params)773 expected_call = np.array([[0.02251146, 0.02281654, 0.01642484],774 [0.0245291, 0.02648423, 0.01810373],775 [0.02655219, 0.03231528, 0.02002786],776 [0.02633276, 0.0446913, 0.02109933],777 [0.00091364, 0.12030889, 0.00161394]])778 np_test.assert_allclose(test_call, expected_call, rtol=5e-6)779 # put780 test_put = self.put_opt.delta(**self.vector_params)781 expected_put = copy.deepcopy(-expected_call)782 np_test.assert_allclose(test_put, expected_put, rtol=5e-6)783 # assert call and put delta consistency784 np_test.assert_allclose(test_call, -test_put)785 def test_delta_vector_df(self):786 """Test Delta - pd.DataFrame output case"""787 # request Pandas DataFrame as output format788 self.vector_params["np_output"] = False789 # call790 test_call = self.call_opt.delta(**self.vector_params)791 expected_call = pd.DataFrame(data=[[0.02251146, 0.02281654, 0.01642484],792 [0.0245291, 0.02648423, 0.01810373],793 [0.02655219, 0.03231528, 0.02002786],794 [0.02633276, 0.0446913, 0.02109933],795 [0.00091364, 0.12030889, 0.00161394]],796 index=self.vector_params["t"],797 columns=self.vector_params["S"])798 expected_call.rename_axis("S", axis='columns', inplace=True)799 expected_call.rename_axis("t", axis='rows', inplace=True)800 pd_test.assert_frame_equal(test_call, expected_call)801 # put802 test_put = self.put_opt.delta(**self.vector_params)803 expected_put = copy.deepcopy(-expected_call)804 pd_test.assert_frame_equal(test_put, expected_put)805 # assert call and put delta consistency806 pd_test.assert_frame_equal(test_call, -test_put)807 def test_gamma_scalar(self):808 """Test Gamma - scalar case"""809 # call810 test_call = scalarize(self.call_opt.gamma(**self.scalar_params))811 expected_call = -0.0004409117739687288812 self.assertEqual(test_call, expected_call)813 # put814 test_put = scalarize(self.put_opt.gamma(**self.scalar_params))815 expected_put = copy.deepcopy(-expected_call)816 self.assertEqual(test_put, expected_put)817 # assert call and put gamma coincide818 self.assertEqual(test_call, -test_put)819 def test_gamma_vector_np(self):820 """Test Gamma - np.ndarray output case"""821 # call822 test_call = self.call_opt.gamma(**self.vector_params)823 expected_call = np.array([[0.00050164, -0.00039929, -0.00076858],824 [0.00087371, -0.00046347, -0.00102583],825 [0.00161634, -0.00056552, -0.00150922],826 [0.0034499, -0.0007821, -0.00268525],827 [0.00095822, -0.00210541, -0.00130173]])828 np_test.assert_allclose(test_call, expected_call, rtol=1e-5)829 # put830 test_put = self.put_opt.gamma(**self.vector_params)831 expected_put = copy.deepcopy(-expected_call)832 np_test.assert_allclose(test_put, expected_put, rtol=1e-5)833 # assert call and put gamma coincide834 np_test.assert_allclose(test_call, -test_put)835 def test_gamma_vector_df(self):836 """Test Gamma - pd.DataFrame output case"""837 # request Pandas DataFrame as output format838 self.vector_params["np_output"] = False839 # call840 test_call = self.call_opt.gamma(**self.vector_params)841 expected_call = pd.DataFrame(data=[[0.00050164, -0.00039929, -0.00076858],842 [0.00087371, -0.00046347, -0.00102583],843 [0.00161634, -0.00056552, -0.00150922],844 [0.0034499, -0.0007821, -0.00268525],845 [0.00095822, -0.00210541, -0.00130173]],846 index=self.vector_params["t"],847 columns=self.vector_params["S"])848 expected_call.rename_axis("S", axis='columns', inplace=True)849 expected_call.rename_axis("t", axis='rows', inplace=True)850 pd_test.assert_frame_equal(test_call, expected_call, check_less_precise=True)851 # put852 test_put = self.put_opt.gamma(**self.vector_params)853 expected_put = copy.deepcopy(-expected_call)854 pd_test.assert_frame_equal(test_put, expected_put, check_less_precise=True)855 # assert call and put gamma coincide856 pd_test.assert_frame_equal(test_call, -test_put)857 def test_vega_scalar(self):858 """Test Vega - scalar case"""859 # call860 test_call = scalarize(self.call_opt.vega(**self.scalar_params))861 expected_call = -0.005145983992073383862 self.assertEqual(test_call, expected_call)863 # put864 test_put = scalarize(self.put_opt.vega(**self.scalar_params))865 expected_put = copy.deepcopy(-expected_call)866 self.assertEqual(test_put, expected_put)867 # assert call and put vega coincide868 self.assertEqual(test_call, -test_put)869 def test_vega_vector_np(self):870 """Test Vega - np.ndarray output case"""871 # call872 test_call = self.call_opt.vega(**self.vector_params)873 expected_call = np.array([[0.00569969, -0.00560099, -0.01304515],874 [0.00752302, -0.00492679, -0.01319465],875 [0.0095413, -0.0041213, -0.01330838],876 [0.01087143, -0.00304268, -0.01264053],877 [0.00042529, -0.00115365, -0.00086306]])878 np_test.assert_allclose(test_call, expected_call, rtol=1e-5)879 # put880 test_put = self.put_opt.vega(**self.vector_params)881 expected_put = copy.deepcopy(-expected_call)882 np_test.assert_allclose(test_put, expected_put, rtol=5e-5)883 # assert call and put vega coincide884 np_test.assert_allclose(test_call, -test_put)885 def test_vega_vector_df(self):886 """Test Vega - pd.DataFrame output case"""887 # request Pandas DataFrame as output format888 self.vector_params["np_output"] = False889 # call890 test_call = self.call_opt.vega(**self.vector_params)891 expected_call = pd.DataFrame(data=[[0.00569969, -0.00560099, -0.01304515],892 [0.00752302, -0.00492679, -0.01319465],893 [0.0095413, -0.0041213, -0.01330838],894 [0.01087143, -0.00304268, -0.01264053],895 [0.00042529, -0.00115365, -0.00086306]],896 index=self.vector_params["t"],897 columns=self.vector_params["S"])898 expected_call.rename_axis("S", axis='columns', inplace=True)899 expected_call.rename_axis("t", axis='rows', inplace=True)900 pd_test.assert_frame_equal(test_call, expected_call, check_less_precise=True)901 # put902 test_put = self.put_opt.vega(**self.vector_params)903 expected_put = copy.deepcopy(-expected_call)904 pd_test.assert_frame_equal(test_put, expected_put, check_less_precise=True)905 # assert call and put vega coincide906 pd_test.assert_frame_equal(test_call, -test_put)907 def test_theta_scalar(self):908 """Test Theta - scalar case"""909 # call910 test_call = scalarize(self.call_opt.theta(**self.scalar_params))911 expected_call = -3.094863279105034e-05912 self.assertEqual(test_call, expected_call)913 # put914 test_put = scalarize(self.put_opt.theta(**self.scalar_params))915 expected_put = 0.00016399568592748338916 self.assertEqual(test_put, expected_put)917 def test_theta_vector_np(self):918 """Test Theta - np.ndarray output case"""919 # call920 test_call = self.call_opt.theta(**self.vector_params)921 expected_call = np.array([[-4.59532646e-04, -2.10225482e-05, 3.62119705e-04],922 [-6.54200322e-04, -3.63343877e-05, 5.11024346e-04],923 [-1.01554953e-03, -6.06935961e-05, 8.07873242e-04],924 [-1.83825681e-03, -1.12254822e-04, 1.58102099e-03],925 [-4.36449645e-04, -4.24665854e-04, 9.75289889e-04]])926 np_test.assert_allclose(test_call, expected_call)927 # put928 test_put = self.put_opt.theta(**self.vector_params)929 expected_put = np.array([[0.0005918, 0.00015329, -0.00022985],930 [0.00078759, 0.00016973, -0.00037763],931 [0.00115006, 0.00019521, -0.00067336],932 [0.00197392, 0.00024792, -0.00144536],933 [0.00057325, 0.00056146, -0.00083849]])934 np_test.assert_allclose(test_put, expected_put, rtol=5e-5)935 def test_theta_vector_df(self):936 """Test Theta - pd.DataFrame output case"""937 # request Pandas DataFrame as output format938 self.vector_params["np_output"] = False939 # call940 test_call = self.call_opt.theta(**self.vector_params)941 expected_call = pd.DataFrame(data=[[-4.59532646e-04, -2.10225482e-05, 3.62119705e-04],942 [-6.54200322e-04, -3.63343877e-05, 5.11024346e-04],943 [-1.01554953e-03, -6.06935961e-05, 8.07873242e-04],944 [-1.83825681e-03, -1.12254822e-04, 1.58102099e-03],945 [-4.36449645e-04, -4.24665854e-04, 9.75289889e-04]],946 index=self.vector_params["t"],947 columns=self.vector_params["S"])948 expected_call.rename_axis("S", axis='columns', inplace=True)949 expected_call.rename_axis("t", axis='rows', inplace=True)950 pd_test.assert_frame_equal(test_call, expected_call, check_less_precise=True)951 # put952 test_put = self.put_opt.theta(**self.vector_params)953 expected_put = pd.DataFrame(data=[[0.0005918, 0.00015329, -0.00022985],954 [0.00078759, 0.00016973, -0.00037763],955 [0.00115006, 0.00019521, -0.00067336],956 [0.00197392, 0.00024792, -0.00144536],957 [0.00057325, 0.00056146, -0.00083849]],958 index=self.vector_params["t"],959 columns=self.vector_params["S"])960 expected_put.rename_axis("S", axis='columns', inplace=True)961 expected_put.rename_axis("t", axis='rows', inplace=True)962 pd_test.assert_frame_equal(test_put, expected_put, check_less_precise=True)963 def test_rho_scalar(self):964 """Test Rho - scalar case"""965 # call966 test_call = scalarize(self.call_opt.rho(**self.scalar_params))967 expected_call = 0.011610379741045512968 self.assertEqual(test_call, expected_call)969 # put970 test_put = scalarize(self.put_opt.rho(**self.scalar_params))971 expected_put = -0.01727818420465756972 self.assertEqual(test_put, expected_put)973 def test_rho_vector_np(self):974 """Test Rho - np.ndarray output case"""975 # call976 test_call = self.call_opt.rho(**self.vector_params)977 expected_call = np.array([[1.21286837e-02, 1.22783358e-02, 7.54978064e-03],978 [1.03369366e-02, 1.12633572e-02, 6.56155667e-03],979 [7.93101136e-03, 9.85705868e-03, 5.12733711e-03],980 [4.36037779e-03, 7.67938163e-03, 2.83056260e-03],981 [2.23107982e-05, 3.15662549e-03, -2.24454016e-04]])982 np_test.assert_allclose(test_call, expected_call)983 # put984 test_put = self.put_opt.rho(**self.vector_params)985 expected_put = np.array([[-1.89006853e-02, -1.90503374e-02, -1.43217822e-02],986 [-1.55126157e-02, -1.64390362e-02, -1.17372358e-02],987 [-1.15090604e-02, -1.34351077e-02, -8.70538615e-03],988 [-6.28675585e-03, -9.60575970e-03, -4.75694066e-03],989 [-2.95908353e-04, -3.43022305e-03, -4.91435388e-05]])990 np_test.assert_allclose(test_put, expected_put)991 def test_rho_vector_df(self):992 """Test Theta - pd.DataFrame output case"""993 # request Pandas DataFrame as output format994 self.vector_params["np_output"] = False995 # call996 test_call = self.call_opt.rho(**self.vector_params)997 expected_call = pd.DataFrame(data=[[1.21286837e-02, 1.22783358e-02, 7.54978064e-03],998 [1.03369366e-02, 1.12633572e-02, 6.56155667e-03],999 [7.93101136e-03, 9.85705868e-03, 5.12733711e-03],1000 [4.36037779e-03, 7.67938163e-03, 2.83056260e-03],1001 [2.23107982e-05, 3.15662549e-03, -2.24454016e-04]],1002 index=self.vector_params["t"],1003 columns=self.vector_params["S"])1004 expected_call.rename_axis("S", axis='columns', inplace=True)1005 expected_call.rename_axis("t", axis='rows', inplace=True)1006 pd_test.assert_frame_equal(test_call, expected_call)1007 # put1008 test_put = self.put_opt.rho(**self.vector_params)1009 expected_put = pd.DataFrame(data=[[-1.89006853e-02, -1.90503374e-02, -1.43217822e-02],1010 [-1.55126157e-02, -1.64390362e-02, -1.17372358e-02],1011 [-1.15090604e-02, -1.34351077e-02, -8.70538615e-03],1012 [-6.28675585e-03, -9.60575970e-03, -4.75694066e-03],1013 [-2.95908353e-04, -3.43022305e-03, -4.91435388e-05]],1014 index=self.vector_params["t"],1015 columns=self.vector_params["S"])1016 expected_put.rename_axis("S", axis='columns', inplace=True)1017 expected_put.rename_axis("t", axis='rows', inplace=True)1018 pd_test.assert_frame_equal(test_put, expected_put)1019 def test_Implied_Vol_scalar(self):1020 """Test Implied Volatility - scalar case"""1021 # call1022 test_call = scalarize(self.call_opt.implied_volatility(**self.scalar_params))1023 expected_call = 0.21024 self.assertAlmostEqual(test_call, expected_call)1025 # put1026 test_put = scalarize(self.put_opt.implied_volatility(**self.scalar_params))1027 expected_put = 0.21028 self.assertAlmostEqual(test_put, expected_put)1029 def test_Implied_Vol_vector_np(self):1030 """Test Implied Volatility - np.ndarray output case"""1031 # call1032 test_call = self.call_opt.implied_volatility(**self.vector_params)1033 expected_call = 0.2 + np.zeros_like(test_call)1034 np_test.assert_allclose(test_call, expected_call, rtol=5e-7)1035 # put1036 test_put = self.put_opt.implied_volatility(**self.vector_params)1037 expected_put = 0.2 + np.zeros_like(test_put)1038 np_test.assert_allclose(test_put, expected_put, rtol=5e-7)1039 def test_Implied_Vol_vector_df(self):1040 """Test Implied Volatility - pd.DataFrame output case"""1041 # request Pandas DataFrame as output format1042 self.vector_params["np_output"] = False1043 # call1044 test_call = self.call_opt.implied_volatility(**self.vector_params)1045 expected_call = pd.DataFrame(data=0.2 + np.zeros_like(test_call),1046 index=self.vector_params["t"],1047 columns=self.vector_params["S"])1048 expected_call.rename_axis("S", axis='columns', inplace=True)1049 expected_call.rename_axis("t", axis='rows', inplace=True)1050 pd_test.assert_frame_equal(test_call, expected_call)1051 # put1052 test_put = self.put_opt.implied_volatility(**self.vector_params)1053 expected_put = pd.DataFrame(data=0.2 + np.zeros_like(test_put),1054 index=self.vector_params["t"],1055 columns=self.vector_params["S"])1056 expected_put.rename_axis("S", axis='columns', inplace=True)1057 expected_put.rename_axis("t", axis='rows', inplace=True)1058 pd_test.assert_frame_equal(test_put, expected_put)1059 def test_complex_parameters_setup(self):1060 """1061 Test complex parameter setup:1062 (S scalar, K and t vector, sigma distributed as Kxt grid, r distributed as Kxt grid)1063 """1064 # call1065 test_call_price = self.call_opt.price(**self.complex_params)1066 test_call_PnL = self.call_opt.PnL(**self.complex_params)1067 test_call_delta = self.call_opt.delta(**self.complex_params)1068 test_call_gamma = self.call_opt.gamma(**self.complex_params)1069 test_call_vega = self.call_opt.vega(**self.complex_params)1070 test_call_theta = self.call_opt.theta(**self.complex_params)1071 test_call_rho = self.call_opt.rho(**self.complex_params)1072 test_call_iv = self.call_opt.implied_volatility(**self.complex_params)1073 expected_call_price = pd.DataFrame(data=[[0.9798568, 0.62471855, 0.47323669, 0.39201772],1074 [0.68363866, 0.50365944, 0.42894149, 0.37368724],1075 [0.87602123, 0.60825314, 0.46889718, 0.36012104]],1076 index=self.complex_params["t"],1077 columns=self.complex_params["K"])1078 expected_call_price.rename_axis("K", axis='columns', inplace=True)1079 expected_call_price.rename_axis("t", axis='rows', inplace=True)1080 expected_call_PnL = pd.DataFrame(data=[[0.68311074, 0.3279725, 0.17649063, 0.09527166],1081 [0.3868926, 0.20691339, 0.13219544, 0.07694118],1082 [0.57927518, 0.31150708, 0.17215112, 0.06337498]],1083 index=self.complex_params["t"],1084 columns=self.complex_params["K"])1085 expected_call_PnL.rename_axis("K", axis='columns', inplace=True)1086 expected_call_PnL.rename_axis("t", axis='rows', inplace=True)1087 expected_call_delta = pd.DataFrame(data=[[0.00448245, 0.02461979, 0.01726052, 0.01248533],1088 [0.01263986, 0.01196584, 0.01011038, 0.00854062],1089 [0.01504177, 0.02568663, 0.02420515, 0.02088546]],1090 index=self.complex_params["t"],1091 columns=self.complex_params["K"])1092 expected_call_delta.rename_axis("K", axis='columns', inplace=True)1093 expected_call_delta.rename_axis("t", axis='rows', inplace=True)1094 expected_call_gamma = pd.DataFrame(data=[[-1.36939276e-03, -8.30886510e-04, -1.59819664e-04, -3.72062630e-05],1095 [-3.79395726e-04, -1.46568014e-04, -7.22169767e-05, -3.73088881e-05],1096 [-1.47523572e-03, -7.66683834e-04, -1.58922692e-04, 1.82659675e-04]],1097 index=self.complex_params["t"],1098 columns=self.complex_params["K"])1099 expected_call_gamma.rename_axis("K", axis='columns', inplace=True)1100 expected_call_gamma.rename_axis("t", axis='rows', inplace=True)1101 expected_call_vega = pd.DataFrame(data=[[-0.00777965, -0.00944069, -0.00272385, -0.00084549],1102 [-0.00559895, -0.00259558, -0.00149204, -0.00088094],1103 [-0.00294643, -0.00170141, -0.00038795, 0.00048643]],1104 index=self.complex_params["t"],1105 columns=self.complex_params["K"])1106 expected_call_vega.rename_axis("K", axis='columns', inplace=True)1107 expected_call_vega.rename_axis("t", axis='rows', inplace=True)1108 expected_call_theta = pd.DataFrame(data=[[1.67739087e-04, 2.81595503e-04, 7.08163129e-05, -1.41282958e-05],1109 [9.90248652e-04, 4.91233384e-04, 3.00397593e-04, 1.78375694e-04],1110 [1.31411352e-02, 8.04031544e-03, 1.61848869e-03, -3.41813594e-03]],1111 index=self.complex_params["t"],1112 columns=self.complex_params["K"])1113 expected_call_theta.rename_axis("K", axis='columns', inplace=True)1114 expected_call_theta.rename_axis("t", axis='rows', inplace=True)1115 expected_call_rho = pd.DataFrame(data=[[-0.00404295, 0.01115923, 0.00757627, 0.00513166],1116 [0.00165411, 0.00208889, 0.00175266, 0.0014392],1117 [0.00013089, 0.00046672, 0.00046837, 0.00041632]],1118 index=self.complex_params["t"],1119 columns=self.complex_params["K"])1120 expected_call_rho.rename_axis("K", axis='columns', inplace=True)1121 expected_call_rho.rename_axis("t", axis='rows', inplace=True)1122 expected_call_iv = pd.DataFrame(data=self.complex_params["sigma"],1123 index=self.complex_params["t"],1124 columns=self.complex_params["K"])1125 expected_call_iv.rename_axis("K", axis='columns', inplace=True)1126 expected_call_iv.rename_axis("t", axis='rows', inplace=True)1127 pd_test.assert_frame_equal(test_call_price, expected_call_price)1128 pd_test.assert_frame_equal(test_call_PnL, expected_call_PnL)1129 pd_test.assert_frame_equal(test_call_delta, expected_call_delta)1130 pd_test.assert_frame_equal(test_call_gamma, expected_call_gamma)1131 pd_test.assert_frame_equal(test_call_vega, expected_call_vega, check_less_precise=True)1132 pd_test.assert_frame_equal(test_call_theta, expected_call_theta)1133 pd_test.assert_frame_equal(test_call_rho, expected_call_rho, check_less_precise=True)1134 pd_test.assert_frame_equal(test_call_iv.iloc[:, :-1], expected_call_iv.iloc[:, :-1])1135 self.assertAlmostEqual(test_call_iv.iloc[-1, -1], expected_call_iv.iloc[-1, -1], places=5)1136 # put1137 test_put_price = self.put_opt.price(**self.complex_params)1138 test_put_PnL = self.put_opt.PnL(**self.complex_params)1139 test_put_delta = self.put_opt.delta(**self.complex_params)1140 test_put_gamma = self.put_opt.gamma(**self.complex_params)1141 test_put_vega = self.put_opt.vega(**self.complex_params)1142 test_put_theta = self.put_opt.theta(**self.complex_params)1143 test_put_rho = self.put_opt.rho(**self.complex_params)1144 test_put_iv = self.put_opt.implied_volatility(**self.complex_params)1145 expected_put_price = pd.DataFrame(data=[[0.01315404, 0.36135198, 0.50594203, 0.58031737],1146 [0.29830713, 0.47471481, 0.54587421, 0.59758286],1147 [0.12151605, 0.38901089, 0.52809366, 0.63659669]],1148 index=self.complex_params["t"],1149 columns=self.complex_params["K"])1150 expected_put_price.rename_axis("K", axis='columns', inplace=True)1151 expected_put_price.rename_axis("t", axis='rows', inplace=True)1152 expected_put_PnL = pd.DataFrame(data=[[-0.65563919, -0.30744125, -0.16285119, -0.08847586],1153 [-0.37048609, -0.19407842, -0.12291901, -0.07121037],1154 [-0.54727717, -0.27978234, -0.14069957, -0.03219654]],1155 index=self.complex_params["t"],1156 columns=self.complex_params["K"])1157 expected_put_PnL.rename_axis("K", axis='columns', inplace=True)1158 expected_put_PnL.rename_axis("t", axis='rows', inplace=True)1159 expected_put_delta = copy.deepcopy(-expected_call_delta)1160 expected_put_gamma = copy.deepcopy(-expected_call_gamma)1161 expected_put_vega = copy.deepcopy(-expected_call_vega)1162 expected_put_theta = pd.DataFrame(data=[[-1.40533310e-04, -2.27564242e-04, 9.66413009e-06, 1.20685566e-04],1163 [-8.55735531e-04, -3.30404740e-04, -1.13446636e-04, 3.45054237e-05],1164 [-1.28951671e-02, -7.76709242e-03, -1.31802569e-03, 3.74582396e-03]],1165 index=self.complex_params["t"],1166 columns=self.complex_params["K"])1167 expected_put_theta.rename_axis("K", axis='columns', inplace=True)1168 expected_put_theta.rename_axis("t", axis='rows', inplace=True)1169 expected_put_rho = pd.DataFrame(data=[[-0.00292173, -0.01807524, -0.01444393, -0.01195132],1170 [-0.00523216, -0.00565392, -0.00530473, -0.00497835],1171 [-0.00040418, -0.00073995, -0.00074152, -0.00068939]],1172 index=self.complex_params["t"],1173 columns=self.complex_params["K"])1174 expected_put_rho.rename_axis("K", axis='columns', inplace=True)1175 expected_put_rho.rename_axis("t", axis='rows', inplace=True)1176 expected_put_iv = pd.DataFrame(data=self.complex_params["sigma"],1177 index=self.complex_params["t"],1178 columns=self.complex_params["K"])1179 expected_put_iv.rename_axis("K", axis='columns', inplace=True)1180 expected_put_iv.rename_axis("t", axis='rows', inplace=True)1181 pd_test.assert_frame_equal(test_put_price, expected_put_price)1182 pd_test.assert_frame_equal(test_put_PnL, expected_put_PnL)1183 pd_test.assert_frame_equal(test_put_delta, expected_put_delta)1184 pd_test.assert_frame_equal(test_put_gamma, expected_put_gamma)1185 pd_test.assert_frame_equal(test_put_vega, expected_put_vega, check_less_precise=True)1186 pd_test.assert_frame_equal(test_put_theta, expected_put_theta)1187 pd_test.assert_frame_equal(test_put_rho, expected_put_rho, check_less_precise=True)1188 pd_test.assert_frame_equal(test_put_iv.iloc[:, :-1], expected_put_iv.iloc[:, :-1])1189 self.assertAlmostEqual(test_put_iv.iloc[-1, -1], expected_put_iv.iloc[-1, -1], places=5)1190 # test gamma and vega consistency1191 pd_test.assert_frame_equal(test_call_delta, -test_put_delta)1192 pd_test.assert_frame_equal(test_call_gamma, -test_put_gamma)1193 pd_test.assert_frame_equal(test_call_vega, -test_put_vega)1194if __name__ == '__main__':...
tests.py
Source:tests.py
...299#300## # general.py tests301#302#class TestLook(CommandTest):303# def test_call(self):304# self.execute_cmd("look here")305#class TestHome(CommandTest):306# def test_call(self):307# self.char1.location = self.room1308# self.char1.home = self.room2309# self.execute_cmd("home")310# self.assertEqual(self.char1.location, self.room2)311#class TestPassword(CommandTest):312# def test_call(self):313# self.execute_cmd("@password testpassword = newpassword")314#class TestInventory(CommandTest):315# def test_call(self):316# self.execute_cmd("inv")317#class TestQuit(CommandTest):318# def test_call(self):319# self.execute_cmd("@quit")320#class TestPose(CommandTest):321# def test_call(self):322# self.execute_cmd("pose is testing","TestChar is testing")323#class TestNick(CommandTest):324# def test_call(self):325# self.char1.player.user.is_superuser = False326# self.execute_cmd("nickname testalias = testaliasedstring1")327# self.execute_cmd("nickname/player testalias = testaliasedstring2")328# self.execute_cmd("nickname/object testalias = testaliasedstring3")329# self.assertEqual(u"testaliasedstring1", self.char1.nicks.get("testalias"))330# self.assertEqual(u"testaliasedstring2", self.char1.nicks.get("testalias",nick_type="player"))331# self.assertEqual(u"testaliasedstring3", self.char1.nicks.get("testalias",nick_type="object"))332#class TestGet(CommandTest):333# def test_call(self):334# self.obj1.location = self.room1335# self.execute_cmd("get obj1", "You pick up obj1.")336#class TestDrop(CommandTest):337# def test_call(self):338# self.obj1.location = self.char1339# self.execute_cmd("drop obj1", "You drop obj1.")340#class TestWho(CommandTest):341# def test_call(self):342# self.execute_cmd("who")343#class TestSay(CommandTest):344# def test_call(self):345# self.execute_cmd("say Hello", 'You say, "Hello')346#class TestAccess(CommandTest):347# def test_call(self):348# self.execute_cmd("access")349#class TestEncoding(CommandTest):350# def test_call(self):351# global NOMANGLE352# NOMANGLE = True353# self.char1.db.encoding="utf-8"354# self.execute_cmd("@encoding", "Default encoding:")355# NOMANGLE = False356#357## help.py command tests358#359#class TestHelpSystem(CommandTest):360# def test_call(self):361# self.NOMANGLE = True362# sep = "-"*78 + "\n"363# self.execute_cmd("@help/add TestTopic,TestCategory = Test1", )364# self.execute_cmd("help TestTopic",sep + "Help topic for Testtopic\nTest1" + "\n" + sep)365# self.execute_cmd("@help/merge TestTopic = Test2", "Added the new text right after")366# self.execute_cmd("help TestTopic", sep + "Help topic for Testtopic\nTest1 Test2")367# self.execute_cmd("@help/append TestTopic = Test3", "Added the new text as a")368# self.execute_cmd("help TestTopic",sep + "Help topic for Testtopic\nTest1 Test2\n\nTest3")369# self.execute_cmd("@help/delete TestTopic","Deleted the help entry")370# self.execute_cmd("help TestTopic","No help entry found for 'TestTopic'")371#372## system.py command tests373#class TestPy(CommandTest):374# def test_call(self):375# self.execute_cmd("@py 1+2", [">>> 1+2", "<<< 3"])376#class TestScripts(CommandTest):377# def test_call(self):378# script = create.create_script(None, "test")379# self.execute_cmd("@scripts", "id")380#class TestObjects(CommandTest):381# def test_call(self):382# self.execute_cmd("@objects", "Database totals")383## Cannot be tested since we don't have an active server running at this point.384## class TestListService(CommandTest):385## def test_call(self):386## self.execute_cmd("@service/list", "---")387#class TestVersion(CommandTest):388# def test_call(self):389# self.execute_cmd("@version", '---')390#class TestTime(CommandTest):391# def test_call(self):392# self.execute_cmd("@time", "Current server uptime")393#class TestServerLoad(CommandTest):394# def test_call(self):395# self.execute_cmd("@serverload", "Server load")396#class TestPs(CommandTest):397# def test_call(self):398# self.execute_cmd("@ps","Non-timed scripts")399#400## admin.py command tests401#402#class TestBoot(CommandTest):403# def test_call(self):404# self.execute_cmd("@boot TestChar2","You booted TestChar2.")405#class TestDelPlayer(CommandTest):406# def test_call(self):407# self.execute_cmd("@delplayer TestChar2","Booting and informing player ...")408#class TestEmit(CommandTest):409# def test_call(self):410# self.execute_cmd("@emit Test message", "Emitted to room1.")411#class TestUserPassword(CommandTest):412# def test_call(self):413# self.execute_cmd("@userpassword TestChar2 = newpass", "TestChar2 - new password set to 'newpass'.")414#class TestPerm(CommandTest):415# def test_call(self):416# self.execute_cmd("@perm TestChar2 = Builders", "Permission 'Builders' given to")417## cannot test this here; screws up the test suite418##class TestPuppet(CommandTest):419## def test_call(self):420## self.execute_cmd("@puppet TestChar3", "You now control TestChar3.")421## self.execute_cmd("@puppet TestChar", "You now control TestChar.")422#class TestWall(CommandTest):423# def test_call(self):424# self.execute_cmd("@wall = This is a test message", "TestChar shouts")425#426#427## building.py command tests428#429#class TestObjAlias(BuildTest):430# def test_call(self):431# self.execute_cmd("@alias obj1 = obj1alias, obj1alias2", "Aliases for")432# self.execute_cmd("look obj1alias2", "obj1")433#class TestCopy(BuildTest):434# def test_call(self):435# self.execute_cmd("@copy obj1 = obj1_copy;alias1;alias2", "Copied obj1 to 'obj1_copy'")436# self.execute_cmd("look alias2","obj1_copy")437#class TestSet(BuildTest):438# def test_call(self):439# self.execute_cmd("@set obj1/test = value", "Created attribute obj1/test = value")440# self.execute_cmd("@set obj1/test", "Attribute obj1/test = value")441# self.assertEqual(self.obj1.db.test, u"value")442#class TestCpAttr(BuildTest):443# def test_call(self):444# self.execute_cmd("@set obj1/test = value")445# self.execute_cmd("@set obj2/test2 = value2")446# #self.execute_cmd("@cpattr obj1/test = obj2/test") # can't be tested since instances changes447# #self.assertEqual(self.obj2.db.test, u"value")448#class TestMvAttr(BuildTest):449# def test_call(self):450# self.execute_cmd("@set obj1/test = value")451# self.execute_cmd("@mvattr obj1/test = obj2")452# #self.assertEqual(self.obj2.db.test, u"value")453# #self.assertEqual(self.obj1.db.test, None)454#class TestCreate(BuildTest):455# def test_call(self):456# self.execute_cmd("@create testobj;alias1;alias2")457# self.execute_cmd("look alias1", "testobj")458#class TestDebug(BuildTest):459# def test_call(self):460# self.execute_cmd("@debug/obj obj1")461#class TestDesc(BuildTest):462# def test_call(self):463# self.execute_cmd("@desc obj1 = Test object", "The description was set on")464# #self.assertEqual(self.obj1.db.desc, u"Test object")465#class TestDestroy(BuildTest):466# def test_call(self):467# self.execute_cmd("@destroy obj1, obj2", "obj1 was destroyed.\nobj2 was destroyed.")468#class TestFind(BuildTest):469# def test_call(self):470# self.execute_cmd("@find obj1", "One Match")471#class TestDig(BuildTest):472# def test_call(self):473# self.execute_cmd("@dig room3;roomalias1;roomalias2 = north;n,south;s")474# self.execute_cmd("@find room3", "One Match")475# self.execute_cmd("@find roomalias1", "One Match")476# self.execute_cmd("@find roomalias2", "One Match")477# self.execute_cmd("@find/room roomalias2", "One Match")478# self.execute_cmd("@find/exit south", "One Match")479# self.execute_cmd("@find/exit n", "One Match")480#class TestUnLink(BuildTest):481# def test_call(self):482# self.execute_cmd("@dig room3;roomalias1, north, south")483# self.execute_cmd("@unlink north")484#class TestLink(BuildTest):485# def test_call(self):486# self.execute_cmd("@dig room3;roomalias1, north, south")487# self.execute_cmd("@unlink north")488# self.execute_cmd("@link north = room3")489#class TestHome(BuildTest):490# def test_call(self):491# self.obj1.db_home = self.obj2.dbobj492# self.obj1.save()493# self.execute_cmd("@home obj1")494# self.assertEqual(self.obj1.db_home, self.obj2.dbobj)495#class TestCmdSets(BuildTest):496# def test_call(self):497# self.execute_cmd("@cmdsets")498# self.execute_cmd("@cmdsets obj1")499#class TestName(BuildTest):500# def test_call(self):501# self.execute_cmd("@name obj1 = Test object", "Object's name changed to 'Test object'.")502# #self.assertEqual(self.obj1.key, u"Test object")503#class TestOpen(BuildTest):504# def test_call(self):505# self.execute_cmd("@dig room4;roomalias4")506# self.execute_cmd("@open testexit4;aliasexit4 = roomalias4", "Created new Exit")507#class TestTypeclass(BuildTest):508# def test_call(self):509# self.execute_cmd("@typeclass obj1 = src.objects.objects.Character", "obj's type is now")510# #self.assertEqual(self.obj1.db_typeclass_path, u"src.objects.objects.Character")511#class TestSet(BuildTest):512# def test_call(self):513# self.execute_cmd("@set box1/test = value")514# self.execute_cmd("@wipe box1", "Wiped")515# self.assertEqual(self.obj1.db.all, [])516#class TestLock(BuildTest):517# # lock functionality itseld is tested separately518# def test_call(self):519# self.char1.permissions = ["TestPerm"]520# self.execute_cmd("@lock obj1 = test:perm(TestPerm)")521# #self.assertEqual(True, self.obj1.access(self.char1, u"test"))522#class TestExamine(BuildTest):523# def test_call(self):524# self.execute_cmd("examine obj1", "------------")525#class TestTeleport(BuildTest):526# def test_call(self):527# self.execute_cmd("@tel obj1 = room1")528# self.assertEqual(self.obj1.location.key, self.room1.key)529#class TestScript(BuildTest):530# def test_call(self):531# self.execute_cmd("@script TestChar = examples.bodyfunctions.BodyFunctions", "Script successfully added")532#533## Comms commands534#535#class TestChannelCreate(CommandTest):536# def test_call(self):537# self.execute_cmd("@ccreate testchannel1;testchan1;testchan1b = This is a test channel")538# self.execute_cmd("testchan1 Hello", "[testchannel1] TestChar: Hello")539#class TestAddCom(CommandTest):540# def test_call(self):541# self.execute_cmd("@cdestroy testchannel1", "Channel 'testchannel1'")542# self.execute_cmd("@ccreate testchannel1;testchan1;testchan1b = This is a test channel")543# self.execute_cmd("addcom chan1 = testchannel1")544# self.execute_cmd("addcom chan2 = testchan1")545# self.execute_cmd("delcom testchannel1")546# self.execute_cmd("addcom testchannel1" "You now listen to the channel channel.")547#class TestDelCom(CommandTest):548# def test_call(self):549# self.execute_cmd("@cdestroy testchannel1", "Channel 'testchannel1'")550# self.execute_cmd("@ccreate testchannel1;testchan1;testchan1b = This is a test channel")551# self.execute_cmd("addcom chan1 = testchan1")552# self.execute_cmd("addcom chan2 = testchan1b")553# self.execute_cmd("addcom chan3 = testchannel1")554# self.execute_cmd("delcom chan1", "Your alias 'chan1' for ")555# self.execute_cmd("delcom chan2", "Your alias 'chan2' for ")556# self.execute_cmd("delcom testchannel1" "You stop listening to")557#class TestAllCom(CommandTest):558# def test_call(self):559# self.execute_cmd("@ccreate testchannel1;testchan1;testchan1b = This is a test channel")560# self.execute_cmd("@ccreate testchannel1;testchan1;testchan1b = This is a test channel")561# self.execute_cmd("allcom off")562# self.execute_cmd("allcom on")563# self.execute_cmd("allcom destroy")564#class TestChannels(CommandTest):565# def test_call(self):566# self.execute_cmd("@ccreate testchannel1;testchan1;testchan1b = This is a test channel")567# self.execute_cmd("@cdestroy testchannel1", "Channel 'testchannel1'")568#class TestCBoot(CommandTest):569# def test_call(self):570# self.execute_cmd("@cdestroy testchannel1", "Channel 'testchannel1'")571# self.execute_cmd("@ccreate testchannel1;testchan1;testchan1b = This is a test channel")572# self.execute_cmd("addcom testchan = testchannel1")573# self.execute_cmd("@cboot testchannel1 = TestChar", "TestChar boots TestChar from channel.")574#class TestCemit(CommandTest):575# def test_call(self):576# self.execute_cmd("@ccreate testchannel1;testchan1;testchan1b = This is a test channel")577# self.execute_cmd("@cemit testchan1 = Testing!", "[testchannel1] Testing!")578#class TestCwho(CommandTest):579# def test_call(self):580# self.execute_cmd("@ccreate testchannel1;testchan1;testchan1b = This is a test channel")581# self.execute_cmd("@cwho testchan1b", "Channel subscriptions")582#583# OOC commands584#class TestOOC_and_IC(CommandTest): # can't be tested it seems, causes errors in other commands (?)585# def test_call(self):586# self.execute_cmd("@ooc", "\nYou go OOC.")587# self.execute_cmd("@ic", "\nYou become TestChar")588# Unloggedin commands...
tasks.py
Source:tasks.py
1import json2import os3import random4if os.name == "nt":5 import multiprocessing6else:7 import billiard as multiprocessing8from .LoadTester import load_tests, abstract9from .LoadTester.proc_func import process_function10from .celery import app11from .models import TestCall, Result12import typing13import inspect14import requests15from datetime import datetime16import time17from .serializers import TestCallSerializer18def filter_classes(o):19 return inspect.isclass(o) and 'LoadTesterBase' in map(lambda x: x.__name__, inspect.getmro(o))20@app.task21def run_test(test_call_str: str):22 test_call_dict = TestCallSerializer(test_call_str).instance23 test_call = TestCall.objects.get(pk = test_call_dict['id'])24 classes = inspect.getmembers(load_tests, filter_classes)25 print(classes)26 print(test_call)27 needed_class = list(filter(lambda x: x[0] == test_call.test.class_name, classes))28 if len(needed_class) != 1:29 raise TypeError('Cannot find described class: %s' % test_call.test.class_name)30 needed_class = needed_class[0]31 counter = multiprocessing.Value('i', 0)32 lock = multiprocessing.Lock()33 processes = []34 for i in range(test_call.num_users):35 from django import db36 db.connections.close_all()37 proc = multiprocessing.Process(target=process_function, args=(needed_class, test_call.max_calls, counter, lock, test_call_dict))38 proc.start()39 processes.append(proc)40 timestamp = time.time()41 est = test_call.max_calls / test_call.num_users42 rand = random.randint(5, 30)43 m_t = min(random.randint(720, 900), (rand if rand > est else est) + random.randint(0, test_call.num_users))44 for proc in processes:45 print("WAITING FOR: ", proc)46 proc.join(timeout=(m_t - max((time.time() - timestamp), 0)))47 for proc in processes:48 if proc.is_alive():49 proc.terminate()50 try:51 print("WAITING FISHED")52 result = requests.post("%s/rest-auth/login/" % os.getenv("BACKEND_URL"),53 json={"username": os.getenv("BACKEND_USER"), "password": os.getenv("BACKEND_PASSWORD")})54 print("STARTING FILE WRITTING")55 with open('prices%s.txt' % test_call.start_date.strftime("%m-%d-%Y %H-%M-%S"), 'w') as f:56 f.write(json.dumps(requests.get("%s/price_history/" % os.getenv("BACKEND_URL"), headers={"OBCIAZNIK": "DUPA", "Authorization": "Bearer %s" % result.json()['token']}).json()))57 with open('transactions%s.txt' % test_call.start_date.strftime("%m-%d-%Y %H-%M-%S"), 'w') as f:58 f.write(json.dumps(requests.get("%s/transaction/" % os.getenv("BACKEND_URL"), headers={"OBCIAZNIK": "DUPA", "Authorization": "Bearer %s" % result.json()['token']}).json()))59 print("FILE FINISHED")60 except Exception:61 pass62 test_call.is_finished = True63 test_call.end_date = datetime.now()64 test_call.save()...
pipeline.py
Source:pipeline.py
...3import joinDataFrames as joindf4import toCSVDataFrame as tocsv5import selectDataFrame as selectdf6import json7msg_oh = fromcsv.api.test_call(fromcsv.test.ORDER_HEADERS)8info_str = json.dumps(msg_oh.attributes, indent=4)9print(info_str)10msg_oh = sampledf.api.test_call(msg_oh,sampledf.test.BIGDATA)11info_str = json.dumps(msg_oh.attributes, indent=4)12print(info_str)13msg_od = fromcsv.api.test_call(fromcsv.test.ORDER_DETAILS)14info_str = json.dumps(msg_od.attributes, indent=4)15print(info_str)16msg = joindf.api.test_call(msg_oh,msg_od,joindf.test.ORDER_HEADER_DETAIL)17info_str = json.dumps(msg.attributes, indent=4)18print(info_str)19#msg = selectdf.api.test_call(msg)20#info_str = json.dumps(msg.attributes, indent=4)21#print(info_str)22msg_pmd = fromcsv.api.test_call(fromcsv.test.PRODUCTS_MD)23info_str = json.dumps(msg_pmd.attributes, indent=4)24print(info_str)25msg = joindf.api.test_call(msg,msg_pmd,joindf.test.ORDER_PRODUCT_MD)26info_str = json.dumps(msg.attributes, indent=4)27print(info_str)28csv = tocsv.api.test_call(msg)29with open(r"/Users/d051079/OneDrive - SAP SE/Datahub-Dev/data/sample_pos.csv", 'w') as fd:30 if isinstance(csv.body,list) :31 for s in csv.body :32 fd.write(s)33 else :34 fd.write(csv.body)...
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