diff --git a/demos/KaplanMeierSurvivalExplained.ipynb b/demos/KaplanMeierSurvivalExplained.ipynb index be6e638..8a71b44 100644 --- a/demos/KaplanMeierSurvivalExplained.ipynb +++ b/demos/KaplanMeierSurvivalExplained.ipynb @@ -13,9 +13,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "# use pip (or, conda) to make sure lifelines package is installed:\n", @@ -25,9 +23,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "import os, functools\n", @@ -36,7 +32,8 @@ "import lifelines.statistics\n", "from mpyc.runtime import mpc\n", "mpc.logging(False)\n", - "from kmsurvival import fit_plot, events_to_table, events_from_table, logrank_test, aggregate, agg_logrank_test" + "from lifelines import KaplanMeierFitter\n", + "from kmsurvival import plot_fits, events_to_table, events_from_table, logrank_test, aggregate, agg_logrank_test" ] }, { @@ -53,168 +50,166 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "\n", + "
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\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 3, @@ -231,31 +226,33 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Time is in weeks. The study compares the time until recurrence among two groups of patients. Patients in group 1 received maintenance chemotherapy, while patients in group 2 did not get any maintenance treatment. To plot the [Kaplan–Meier survival curve](https://en.wikipedia.org/wiki/Kaplan–Meier_estimator) for groups 1 and 2, we use the function `fit_plot()` as follows." + "Time is in weeks. The study compares the time until recurrence among two groups of patients. Patients in group 1 received maintenance chemotherapy, while patients in group 2 did not get any maintenance treatment. To plot the [Kaplan–Meier survival curve](https://en.wikipedia.org/wiki/Kaplan–Meier_estimator) for groups 1 and 2, we use the function `plot_fits()` as follows." ] }, { "cell_type": "code", "execution_count": 4, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ - "
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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ "T1, T2 = df['time'] [df['group'] == 1], df['time'] [df['group'] == 2]\n", "E1, E2 = df['status'][df['group'] == 1], df['status'][df['group'] == 2]\n", - "kmf1, kmf2 = fit_plot(T1, T2, E1, E2, 'Kaplan-Meier survival curves', 'weeks', '1=Maintained', '2=Not maintained')\n", + "kmf1 = KaplanMeierFitter(label='1=Maintained').fit(T1, E1)\n", + "kmf2 = KaplanMeierFitter(label='2=Not maintained').fit(T2, E2)\n", + "plot_fits(kmf1, kmf2, 'Kaplan-Meier survival curves', 'weeks')\n", "plt.show()" ] }, @@ -271,14 +268,12 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.06533932204050484" + "0.0653393220405049" ] }, "execution_count": 5, @@ -310,15 +305,13 @@ "source": [ "In a multiparty setting, each party holds a private dataset and the goal is to perform a survival analysis on the *union* of all the datasets. To obtain the secure union of the datasets in an efficient way, each private dataset will be represented using two survival tables, one survival table per group of patients. \n", "\n", - "The survival tables for the aml dataset are available from the Kaplan-Meier fitters `kmf1` and `kmf2` output by the call to `fit_plot()` above:" + "The survival tables for the aml dataset are available from the Kaplan-Meier fitters `kmf1` and `kmf2`:" ] }, { "cell_type": "code", "execution_count": 6, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -633,9 +626,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -665,9 +656,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -808,9 +797,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "d1, n1, d2, n2 = (functools.reduce(mpc.vector_add, mpc.input(list(map(secfxp, _)))) for _ in (d1, n1, d2, n2))" @@ -826,14 +813,12 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 10, @@ -859,18 +844,18 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -882,7 +867,9 @@ "T1_, E1_ = events_from_table(agg_d1, agg_n1)\n", "T2_, E2_ = events_from_table(agg_d2, agg_n2)\n", "T1_, T2_ = [t * stride for t in T1_], [t * stride for t in T2_]\n", - "fit_plot(T1_, T2_, E1_, E2_, 'Aggregated Kaplan-Meier survival curves', 'weeks', '1=Maintained', '2=Not maintained')\n", + "kmf1_ = KaplanMeierFitter(label='1=Maintained').fit(T1_, E1_)\n", + "kmf2_ = KaplanMeierFitter(label='2=Not maintained').fit(T2_, E2_)\n", + "plot_fits(kmf1_, kmf2_, 'Aggregated Kaplan-Meier survival curves', 'weeks')\n", "plt.show()" ] }, @@ -905,15 +892,13 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "0.06533926511489802\n" + "0.06533928754794803\n" ] } ], @@ -936,15 +921,13 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "0.06533934447922828\n" + "0.0653392245841535\n" ] } ], @@ -985,7 +968,7 @@ "usage: kmsurvival.py [-h] [-i I] [-s S] [-a A] [--collapse] [--print-tables]\n", " [--plot-curves]\n", "\n", - "optional arguments:\n", + "options:\n", " -h, --help show this help message and exit\n", " -i I, --dataset I dataset 0=btrial(default) 1=waltons 2=aml 3=lung 4=dd\n", " 5=stanford_heart_transplants 6=kidney_transplant\n", @@ -1012,9 +995,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1029,22 +1010,26 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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\n", 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\n", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { @@ -1052,7 +1037,7 @@ "output_type": "stream", "text": [ "Chi2=3.396389, p=0.065339 for all events secure, exploiting aggregates\n", - "Chi2=3.396384, p=0.065339 for all 161 time moments secure\n" + "Chi2=3.396391, p=0.065339 for all 161 time moments secure\n" ] } ], @@ -1073,7 +1058,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": { "scrolled": false }, @@ -1084,11 +1069,11 @@ "text": [ "Using secure fixed-point numbers: SecFxp64:32\n", "Dataset: aml, with 3-party split, time 1 to 41 (stride 4) months\n", - "2023-02-25 15:42:23,947 Logrank test on all events in the clear.\n", + "2024-04-10 18:16:13,332 Logrank test on all events in the clear.\n", "Chi2=2.675902, p=0.101878 for all events in the clear\n", - "2023-02-25 15:42:23,994 Start MPyC runtime v0.9\n", - "2023-02-25 15:42:26,052 All 3 parties connected.\n", - "2023-02-25 15:42:26,255 Logrank test on own events in the clear.\n", + "2024-04-10 18:16:13,348 Start MPyC runtime v0.9.11\n", + "2024-04-10 18:16:14,999 All 3 parties connected.\n", + "2024-04-10 18:16:15,024 Logrank test on own events in the clear.\n", "Chi2=0.510517, p=0.474915 for own events in the clear\n", " removed observed censored entrance at_risk\n", "event_at \n", @@ -1104,7 +1089,7 @@ "3.0 1 1 0 0 3\n", "7.0 1 1 0 0 2\n", "11.0 1 1 0 0 1\n", - "2023-02-25 15:42:26,958 Logrank test on aggregated events in the clear.\n", + "2024-04-10 18:16:15,070 Logrank test on aggregated events in the clear.\n", "Chi2=2.685357, p=0.101275 for aggregated events in the clear\n", " removed observed censored entrance at_risk\n", "event_at \n", @@ -1119,22 +1104,22 @@ "4.0 6 5 1 0 12\n", "8.0 3 3 0 0 6\n", "12.0 3 3 0 0 3\n", - "2023-02-25 15:42:27,193 Optimized secure logrank test on all individual events.\n", - "2023-02-25 15:42:27,193 Interval 1 (time 1 to 4) # observed events = 7\n", - "2023-02-25 15:42:27,193 Interval 2 (time 5 to 8) # observed events = 6\n", - "2023-02-25 15:42:27,208 Interval 3 (time 9 to 12) # observed events = 5\n", - "2023-02-25 15:42:27,208 Interval 4 (time 13 to 16) # observed events = 0\n", - "2023-02-25 15:42:27,208 Interval 5 (time 17 to 20) # observed events = 0\n", - "2023-02-25 15:42:27,208 Interval 6 (time 21 to 24) # observed events = 0\n", - "2023-02-25 15:42:27,208 Interval 7 (time 25 to 28) # observed events = 0\n", - "2023-02-25 15:42:27,208 Interval 8 (time 29 to 32) # observed events = 0\n", - "2023-02-25 15:42:27,208 Interval 9 (time 33 to 36) # observed events = 0\n", - "2023-02-25 15:42:27,208 Interval 10 (time 37 to 40) # observed events = 0\n", - "2023-02-25 15:42:27,208 Interval 11 (time 41 to 41) # observed events = 0\n", - "Chi2=2.675904, p=0.101877 for all events secure, exploiting aggregates\n", - "2023-02-25 15:42:28,385 Secure logrank test for all 41 time moments.\n", + "2024-04-10 18:16:15,105 Optimized secure logrank test on all individual events.\n", + "2024-04-10 18:16:15,105 Interval 1 (time 1 to 4) # observed events = 7\n", + "2024-04-10 18:16:15,106 Interval 2 (time 5 to 8) # observed events = 6\n", + "2024-04-10 18:16:15,106 Interval 3 (time 9 to 12) # observed events = 5\n", + "2024-04-10 18:16:15,107 Interval 4 (time 13 to 16) # observed events = 0\n", + "2024-04-10 18:16:15,107 Interval 5 (time 17 to 20) # observed events = 0\n", + "2024-04-10 18:16:15,107 Interval 6 (time 21 to 24) # observed events = 0\n", + "2024-04-10 18:16:15,107 Interval 7 (time 25 to 28) # observed events = 0\n", + "2024-04-10 18:16:15,107 Interval 8 (time 29 to 32) # observed events = 0\n", + "2024-04-10 18:16:15,107 Interval 9 (time 33 to 36) # observed events = 0\n", + "2024-04-10 18:16:15,107 Interval 10 (time 37 to 40) # observed events = 0\n", + "2024-04-10 18:16:15,107 Interval 11 (time 41 to 41) # observed events = 0\n", + "Chi2=2.675902, p=0.101878 for all events secure, exploiting aggregates\n", + "2024-04-10 18:16:15,685 Secure logrank test for all 41 time moments.\n", "Chi2=2.675903, p=0.101878 for all 41 time moments secure\n", - "2023-02-25 15:42:31,709 Stop MPyC -- elapsed time: 0:00:05.657|bytes sent: 1500642\n" + "2024-04-10 18:16:17,651 Stop MPyC -- elapsed time: 0:00:02.651|bytes sent: 1465252\n" ] } ], @@ -1151,7 +1136,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -1161,7 +1146,7 @@ "usage: kmsurvival.py [-V] [-H] [-h] [-C ini] [-P addr] [-M m] [-I i] [-T t]\n", " [-B b] [--ssl] [-W w] [-L l] [-K k] [--log-level ll]\n", " [--no-log] [--no-async] [--no-barrier] [--no-gmpy2]\n", - " [--no-numpy] [--no-prss] [--mix32-64bit]\n", + " [--no-numpy] [--no-uvloop] [--no-prss] [--mix32-64bit]\n", " [--output-windows] [--output-file] [-f F]\n", "\n", "MPyC help:\n", @@ -1188,6 +1173,7 @@ " --no-barrier disable barriers\n", " --no-gmpy2 disable use of gmpy2 package\n", " --no-numpy disable use of numpy package\n", + " --no-uvloop disable use of uvloop (winloop) package\n", " --no-prss disable use of PRSS (pseudorandom secret sharing)\n", " --mix32-64bit enable mix of 32-bit and 64-bit platforms\n", "\n", @@ -1219,9 +1205,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.10.11" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/demos/kmsurvival.py b/demos/kmsurvival.py index b6b3fcf..d2fbe82 100644 --- a/demos/kmsurvival.py +++ b/demos/kmsurvival.py @@ -77,11 +77,9 @@ from mpyc.runtime import mpc -def fit_plot(T1, T2, E1, E2, title, unit_of_time, label1, label2): - kmf1 = KaplanMeierFitter() - kmf2 = KaplanMeierFitter() - ax = kmf1.fit(T1, E1, label=label1, alpha=0.05).plot(show_censors=True) - ax = kmf2.fit(T2, E2, label=label2, alpha=0.05).plot(ax=ax, show_censors=True) +def plot_fits(kmf1, kmf2, title, unit_of_time): + ax = kmf1.plot(show_censors=True) + ax = kmf2.plot(ax=ax, show_censors=True) ax.set_title(title) if unit_of_time: plt.xlabel(f'timeline ({unit_of_time})') @@ -89,7 +87,6 @@ def fit_plot(T1, T2, E1, E2, title, unit_of_time, label1, label2): plt.tight_layout() figname = ax.figure.canvas.manager.get_window_title() ax.figure.canvas.manager.set_window_title(f'Party {mpc.pid} - {figname}') - return kmf1, kmf2 def events_to_table(maxT, T, E): @@ -261,12 +258,15 @@ async def main(): ' for own events in the clear') if args.print_tables or args.plot_curves: - plt.figure(1) - title = f'Party {mpc.pid}: {name} Survival - individual events' - kmf1, kmf2 = fit_plot(T1, T2, E1, E2, title, unit_of_time, label1, label2) + kmf1 = KaplanMeierFitter(alpha=0.05, label=label1).fit(T1, E1) + kmf2 = KaplanMeierFitter(alpha=0.05, label=label2).fit(T2, E2) if args.print_tables: print(kmf1.event_table) print(kmf2.event_table) + if args.plot_curves: + plt.figure(1) + title = f'Party {mpc.pid}: {name} Survival - individual events' + plot_fits(kmf1, kmf2, title, unit_of_time) # expand to timeline 1..maxT and add all input data homomorphically per group d1, n1 = events_to_table(maxT, T1, E1) @@ -286,14 +286,15 @@ async def main(): ' for aggregated events in the clear') if args.print_tables or args.plot_curves: - plt.figure(2) - title = f'Party {mpc.pid}: {name} Survival - aggregated by {stride} {unit_of_time}' - kmf1, kmf2 = fit_plot([t * stride for t in T1], [t * stride for t in T2], E1, E2, - title, unit_of_time, label1, label2) + kmf1 = KaplanMeierFitter(alpha=0.05, label=label1).fit([t * stride for t in T1], E1) + kmf2 = KaplanMeierFitter(alpha=0.05, label=label2).fit([t * stride for t in T2], E2) if args.print_tables: print(kmf1.event_table) print(kmf2.event_table) if args.plot_curves: + plt.figure(2) + title = f'Party {mpc.pid}: {name} Survival - aggregated by {stride} {unit_of_time}' + plot_fits(kmf1, kmf2, title, unit_of_time) plt.show() logging.info('Optimized secure logrank test on all individual events.') diff --git a/docs/cli.rst b/docs/cli.rst index 43569e4..e11708b 100644 --- a/docs/cli.rst +++ b/docs/cli.rst @@ -42,7 +42,7 @@ reserving lower case for the single-letter options of MPyC programs: .. argparse:: :module: mpyc - :func: get_arg_parser + :func: _get_arg_parser :prog: mpycprog.py MPyC configuration : @before diff --git a/docs/mpyc.rst b/docs/mpyc.rst index a4b1c5b..98eca9d 100644 --- a/docs/mpyc.rst +++ b/docs/mpyc.rst @@ -4,18 +4,18 @@ MPyC package .. automodule:: mpyc :members: -mpyc.gmpy ---------- - -.. automodule:: mpyc.gmpy - :members: - mpyc.numpy ---------- .. automodule:: mpyc.numpy :members: +mpyc.gmpy +--------- + +.. automodule:: mpyc.gmpy + :members: + mpyc.gfpx --------- diff --git a/mpyc/README.md b/mpyc/README.md index 2e724c0..1824f66 100644 --- a/mpyc/README.md +++ b/mpyc/README.md @@ -12,14 +12,14 @@ 8. [sectypes](https://lschoe.github.io/mpyc/mpyc.sectypes.html): SecInt/Fld/Fxp/Flt types for secure (secret-shared) integer/finite-field/fixed-/floating-point values 9. [runtime](https://lschoe.github.io/mpyc/mpyc.runtime.html): core MPC protocols (many hidden by Python's operator overloading) 10. [mpctools](https://lschoe.github.io/mpyc/mpyc.mpctools.html): reduce and accumulate with log round complexity -11. [seclists](https://lschoe.github.io/mpyc/mpyc.seclists.html): secure lists with oblivious access and updates -12. [secgroups](https://lschoe.github.io/mpyc/mpyc.secgroups.html): SecGrp types for secure (secret-shared) finite group elements -13. [random](https://lschoe.github.io/mpyc/mpyc.random.html): securely mimicking Python’s [random](https://docs.python.org/3/library/random.html) module +11. [random](https://lschoe.github.io/mpyc/mpyc.random.html): securely mimicking Python’s [random](https://docs.python.org/3/library/random.html) module +12. [seclists](https://lschoe.github.io/mpyc/mpyc.seclists.html): secure lists with oblivious access and updates +13. [secgroups](https://lschoe.github.io/mpyc/mpyc.secgroups.html): SecGrp types for secure (secret-shared) finite group elements 14. [statistics](https://lschoe.github.io/mpyc/mpyc.statistics.html): securely mimicking Python’s [statistics](https://docs.python.org/3/library/statistics.html) module The modules are listed in topological order w.r.t. internal dependencies: - Modules 1-5 are basic modules which can also be used outside an MPC context - Modules 6-9 form the core of MPyC -- Modules 10-12 form the extended core of MPyC -- Modules 13-14 are small libraries on top of the (extended) core \ No newline at end of file +- Modules 10-13 form the extended core of MPyC +- Module 14 is a small library on top of the (extended) core \ No newline at end of file diff --git a/mpyc/__init__.py b/mpyc/__init__.py index d627dbf..66de3a7 100644 --- a/mpyc/__init__.py +++ b/mpyc/__init__.py @@ -41,7 +41,7 @@ import asyncio -def get_arg_parser(): +def _get_arg_parser(): """Return parser for command line arguments passed to the MPyC runtime.""" parser = argparse.ArgumentParser(add_help=False) @@ -108,7 +108,7 @@ def get_arg_parser(): if os.getenv('READTHEDOCS') != 'True': - options = get_arg_parser().parse_known_args()[0] + options = _get_arg_parser().parse_known_args()[0] if options.VERSION or options.HELP: options.no_log = True diff --git a/mpyc/asyncoro.py b/mpyc/asyncoro.py index f1dc48b..c180865 100644 --- a/mpyc/asyncoro.py +++ b/mpyc/asyncoro.py @@ -317,8 +317,7 @@ def __await__(self): def _nested_list(rt, n, dims): if dims: - n0 = dims[0] - dims = dims[1:] + n0, *dims = dims s = [_nested_list(rt, n0, dims) for _ in range(n)] else: s = [rt() for _ in range(n)] diff --git a/mpyc/finfields.py b/mpyc/finfields.py index a7fd7d3..ba31a01 100644 --- a/mpyc/finfields.py +++ b/mpyc/finfields.py @@ -801,7 +801,11 @@ def __array_function__(self, func, types, args, kwargs): a = list(map(cls, a)) elif isinstance(a, bool) or a is np.True_ or a is np.False_: pass - elif not isinstance(a, tuple): # shape + elif func.__name__.startswith('atleast_'): + a = tuple(map(lambda _: cls(_, check=False), a)) + elif isinstance(a, tuple): + pass # e.g., for func like shape + else: a = cls.field(a) return a @@ -1342,8 +1346,6 @@ def trace(self, *args, **kwargs): return type(self)(a, check=True) - # TODO: add atleast1d(a), atleast2d(a), atleast3d(a) - def transpose(self, *axes): a = self.value.transpose(*axes) return type(self)(a, check=False) diff --git a/mpyc/runtime.py b/mpyc/runtime.py index bbe29c2..f0e2f10 100644 --- a/mpyc/runtime.py +++ b/mpyc/runtime.py @@ -4224,7 +4224,7 @@ def generate_configs(m, addresses): def setup(): """Setup a runtime.""" - parser = mpyc.get_arg_parser() + parser = mpyc._get_arg_parser() argv = sys.argv # keep raw args options, args = parser.parse_known_args() if options.VERSION: diff --git a/mpyc/secgroups.py b/mpyc/secgroups.py index 845a654..ae533db 100644 --- a/mpyc/secgroups.py +++ b/mpyc/secgroups.py @@ -733,6 +733,11 @@ def SecGrpFunc(*args, **kwargs): globals()[name] = SecGrpFunc +SecSymmetricGroup: type +SecQuadraticResidues: type +SecSchnorrGroup: type +SecEllipticCurve: type +SecClassGroup: type _toSecGrpFunc(fg.SymmetricGroup) # make SecSymmetricGroup as secure SymmetricGroup version _toSecGrpFunc(fg.QuadraticResidues) # make SecQuadraticResidues as secure QuadraticResidues version _toSecGrpFunc(fg.SchnorrGroup) # make SecSchnorrGroup as secure SchnorrGroup version diff --git a/mpyc/sectypes.py b/mpyc/sectypes.py index ebe005f..870ca9f 100644 --- a/mpyc/sectypes.py +++ b/mpyc/sectypes.py @@ -1009,7 +1009,8 @@ def __bool__(self): def __array_function__(self, func, types, args, kwargs): # minimal redirect for now if f'{func.__name__}' == 'vstack': - # NB: Numpy 2.0 inserts keyword arguments for np.vstack when converting deprecated np.row_stack call. + # NB: Numpy 2.0 inserts keyword arguments for np.vstack + # when converting deprecated np.row_stack call. kwargs = {} return eval(f'runtime.np_{func.__name__}')(*args, **kwargs) diff --git a/mpyc/statistics.py b/mpyc/statistics.py index 93ee1c2..b789cba 100644 --- a/mpyc/statistics.py +++ b/mpyc/statistics.py @@ -602,11 +602,11 @@ def linear_regression(x, y): """ n = len(x) if len(y) != n: - raise statistics.StatisticsError('covariance requires that both inputs ' + raise statistics.StatisticsError('linear regression requires that both inputs ' 'have same number of data points') if n < 2: - raise statistics.StatisticsError('covariance requires at least two data points') + raise statistics.StatisticsError('linear regression requires at least two data points') sectype = type(x[0]) # all elts of x assumed of same type if not issubclass(sectype, SecureObject): diff --git a/tests/test_finfields.py b/tests/test_finfields.py index fbb7338..ffde3c0 100644 --- a/tests/test_finfields.py +++ b/tests/test_finfields.py @@ -468,6 +468,12 @@ def test_array_function(self): np.assertEqual(np.tensordot(F_a, F_b), np.tensordot(a, b)) np.assertEqual(np.inner(F_a, F_b), np.inner(a, b)) np.assertEqual(np.outer(F_a, F_b), np.outer(a, b)) + np.assertEqual(np.atleast_1d(F(1)), np.atleast_1d(1)) + np.assertEqual(np.atleast_1d(F(1), F_a)[1], np.atleast_1d(1, a)[1]) + np.assertEqual(np.atleast_2d(F(1)), np.atleast_2d(1)) + np.assertEqual(np.atleast_2d(F(1), F_a)[1], np.atleast_2d(1, a)[1]) + np.assertEqual(np.atleast_3d(F(1)), np.atleast_3d(1)) + np.assertEqual(np.atleast_3d(F(1), F_a)[1], np.atleast_3d(1, a)[1]) np.assertEqual(np.concatenate((F_a, F_b, F_a.T)), np.concatenate((a, b, a.T))) np.assertEqual(np.stack([F_a, F_b]), np.stack([a, b])) np.assertEqual(np.stack([a, F_b], axis=1), np.stack([a, b], axis=1)) @@ -478,7 +484,8 @@ def test_array_function(self): np.assertEqual(np.hstack([F_a, F_b]), np.hstack([a, b])) np.assertEqual(np.dstack([F_a, F_b]), np.dstack([a, b])) np.assertEqual(np.column_stack([F_a, F_b]), np.column_stack([a, b])) - np.assertEqual(np.row_stack([F_a, F_b]), np.row_stack([a, b])) + if np.lib.NumpyVersion(np.__version__) < '2.0.0b1': + np.assertEqual(np.row_stack([F_a, F_b]), np.row_stack([a, b])) np.assertEqual(np.split(F_a, 2)[0], np.split(a, 2)[0]) np.assertEqual(np.array_split(F_a, 2)[1], np.array_split(a, 2)[1]) np.assertEqual(np.dsplit(F_a.reshape(1, 4, 4), 2)[1], np.dsplit(a.reshape(1, 4, 4), 2)[1]) diff --git a/tests/test_runtime.py b/tests/test_runtime.py index b23ec7d..6df15a3 100644 --- a/tests/test_runtime.py +++ b/tests/test_runtime.py @@ -59,7 +59,8 @@ def test_secint_array(self): np.assertEqual(mpc.run(mpc.output(np.dstack((c[0], c[0])))), np.dstack((a[0], a[0]))) np.assertEqual(mpc.run(mpc.output(np.dstack((c[0, 0],)))), np.dstack((a[0, 0],))) np.assertEqual(mpc.run(mpc.output(np.column_stack((c, c, c)))), np.column_stack((a, a, a))) - np.assertEqual(mpc.run(mpc.output(np.row_stack((c, c, c)))), np.row_stack((a, a, a))) + if np.lib.NumpyVersion(np.__version__) < '2.0.0b1': + np.assertEqual(mpc.run(mpc.output(np.row_stack((c, c, c)))), np.row_stack((a, a, a))) np.assertEqual(mpc.run(mpc.output(np.split(c, 2, 1)[0])), np.split(a, 2, 1)[0]) np.assertEqual(mpc.run(mpc.output(np.dsplit(d, 1)[0])), np.dsplit(b, 1)[0]) np.assertEqual(mpc.run(mpc.output(np.hsplit(c, 2)[0])), np.hsplit(a, 2)[0])