From f27ccc3bdc4b9b26c02e2d71e5dc34db7f008a88 Mon Sep 17 00:00:00 2001 From: Mason <31526990+makdl@users.noreply.github.com> Date: Thu, 9 Jul 2020 22:05:36 -0400 Subject: [PATCH 01/16] Added new build runners on Travis Added additional build runners on Travis. One additional Linux runner for Ubuntu Bionic, 18.04. New Windows and mac OS runners. Note: When I enabled this I noticed there was an error with test_pause_resume.py not finding pause_models.py on any runner. --- .travis.yml | 54 ++++++++++++++++++++++++++++++++++++----------------- 1 file changed, 37 insertions(+), 17 deletions(-) diff --git a/.travis.yml b/.travis.yml index b65dc9e25..781dba64c 100644 --- a/.travis.yml +++ b/.travis.yml @@ -1,21 +1,40 @@ -os: linux -dist: xenial -language: python -python: "3.6" -before_script: - - "curl -L https://codeclimate.com/downloads/test-reporter/test-reporter-latest-linux-amd64 > ./cc-test-reporter" - - "chmod +x ./cc-test-reporter" - - "./cc-test-reporter before-build" +jobs: + include: + - os: linux + dist: xenial + language: python + python: 3.6 + before_script: + - "curl -L https://codeclimate.com/downloads/test-reporter/test-reporter-latest-linux-amd64 > ./cc-test-reporter" + - "chmod +x ./cc-test-reporter" + - "./cc-test-reporter before-build" + script: + - "coverage run --source=gillespy2 --omit=gillespy2/solvers/stochkit/* test/run_tests.py -m develop" + after_script: + - "coverage xml" + - "if [[ \"$TRAVIS_TEST_RESULT\" == 0 ]]; then ./cc-test-reporter after-build -t coverage.py --exit-code $TRAVIS_TEST_RESULT; fi" + - os: linux + dist: bionic + language: python + python: 3.6 + - os: osx + osx_image: xcode9.4 # Python 3.6.5 running on macOS 10.13 + language: shell # 'language: python' is an error on Travis CI macOS + - os: windows + language: shell # 'language: python' is an error on Travis CI Windows + before_install: + - choco install python --version 3.6.0 + - choco install make + - python -m pip install --upgrade pip + env: PATH=/c/Python36:/c/Python36/Scripts:$PATH install: - - pip3 install -r requirements.txt - - pip3 install python-libsbml - - pip3 install cython - - pip3 install coverage + - pip3 install --upgrade pip + - pip3 install -r requirements.txt + - pip3 install python-libsbml + - pip3 install cython + - pip3 install coverage script: - - "coverage run --source=gillespy2 --omit=gillespy2/solvers/stochkit/* test/run_tests.py -m develop" -after_script: - - "coverage xml" - - "if [[ \"$TRAVIS_TEST_RESULT\" == 0 ]]; then ./cc-test-reporter after-build -t coverage.py --exit-code $TRAVIS_TEST_RESULT; fi" + - "coverage run --source=gillespy2 --omit=gillespy2/solvers/stochkit/* test/run_tests.py -m develop" deploy: # API token stored in env var PYPI_PASSWORD on Travis CI provider: pypi @@ -23,7 +42,8 @@ deploy: edge: true # opt in to dpl v2 user: __token__ on: + condition: $TRAVIS_DIST = xenial repo: GillesPy2/GillesPy2 branch: master tags: true - + From d8ef33dc5027fb3da7115c5cbb0c1f80a3aba423 Mon Sep 17 00:00:00 2001 From: Mason <31526990+makdl@users.noreply.github.com> Date: Mon, 13 Jul 2020 16:03:35 -0400 Subject: [PATCH 02/16] Update .travis.yml --- .travis.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.travis.yml b/.travis.yml index 781dba64c..b2945ba2f 100644 --- a/.travis.yml +++ b/.travis.yml @@ -1,4 +1,6 @@ jobs: + allow_failures: + - os: windows # This should be removed once tests pass on Windows. include: - os: linux dist: xenial @@ -8,8 +10,6 @@ jobs: - "curl -L https://codeclimate.com/downloads/test-reporter/test-reporter-latest-linux-amd64 > ./cc-test-reporter" - "chmod +x ./cc-test-reporter" - "./cc-test-reporter before-build" - script: - - "coverage run --source=gillespy2 --omit=gillespy2/solvers/stochkit/* test/run_tests.py -m develop" after_script: - "coverage xml" - "if [[ \"$TRAVIS_TEST_RESULT\" == 0 ]]; then ./cc-test-reporter after-build -t coverage.py --exit-code $TRAVIS_TEST_RESULT; fi" From 7c4734896e99d2e6d28793ba4b039d054ae878e8 Mon Sep 17 00:00:00 2001 From: seanebum Date: Wed, 29 Jul 2020 10:44:38 -0400 Subject: [PATCH 03/16] removed scipy.integrate.solve_ivp tau events, tau is now just strictly defined as the end of integration for a given step --- gillespy2/solvers/numpy/tau_hybrid_solver.py | 22 ++------------------ 1 file changed, 2 insertions(+), 20 deletions(-) diff --git a/gillespy2/solvers/numpy/tau_hybrid_solver.py b/gillespy2/solvers/numpy/tau_hybrid_solver.py index 09f8ca98d..0347758cf 100644 --- a/gillespy2/solvers/numpy/tau_hybrid_solver.py +++ b/gillespy2/solvers/numpy/tau_hybrid_solver.py @@ -232,19 +232,6 @@ def __f(t, y, curr_state, species, reactions, rate_rules, propensities, return state_change - @staticmethod - def __event(curr_state, species, reactions, rate_rules, propensities, - y_map, compiled_reactions, compiled_rate_rules, event_queue, - assignment_rules, tau, - t, y): - """ - Base "Event" method used in scipy.integrate.solve_ivp. This method - utilizes the brentq method to determine root crossings, and is used in - conjunction with model stochastic reactions to discover reaction - firings. - """ - return tau - t - def __find_event_time(self, sol, model, start, end, index, depth): """ Helper method providing binary search implementation for locating @@ -443,21 +430,18 @@ def __integrate(self, integrator, integrator_options, curr_state, y0, model, cur rhs = lambda t, y: TauHybridSolver.__f(t, y, *int_args) if pure_ode: - tau_event = None next_tau = model.tspan[-1] else: next_tau = curr_time + tau_step - tau_event = partial(TauHybridSolver.__event, *int_args, next_tau) - tau_event.terminal = True curr_state['t'] = curr_time curr_state['time'] = curr_time # Integrate until end or tau is reached # TODO: Need a way to exit solve_ivp when timeout is triggered - sol = solve_ivp(rhs, [curr_time, model.tspan[-1]], y0, + sol = solve_ivp(rhs, [curr_time, next_tau], y0, method=integrator, dense_output=True, - events=tau_event, **integrator_options) + **integrator_options) # Search for precise event times if len(model.listOfEvents): @@ -468,8 +452,6 @@ def __integrate(self, integrator, integrator_options, curr_state, y0, model, cur # Get next tau time reaction_times = [] - if tau_event is not None: - reaction_times.append(min(sol.t_events)) # Set curr time to next time a change occurs in the system outside of # the standard ODE process. Determine what kind of change this is, From 9fda193e32890214d43c70223c4d499fd44ea2ce Mon Sep 17 00:00:00 2001 From: seanebum Date: Mon, 3 Aug 2020 15:14:14 -0400 Subject: [PATCH 04/16] fixed issue where base set of rate rules was being lost for dynamic models --- gillespy2/solvers/numpy/tau_hybrid_solver.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/gillespy2/solvers/numpy/tau_hybrid_solver.py b/gillespy2/solvers/numpy/tau_hybrid_solver.py index 0347758cf..464098089 100644 --- a/gillespy2/solvers/numpy/tau_hybrid_solver.py +++ b/gillespy2/solvers/numpy/tau_hybrid_solver.py @@ -68,6 +68,7 @@ def __toggle_reactions(self, model, all_compiled, deterministic_reactions, depen rate_rules = all_compiled['rules'] rxns = all_compiled['rxns'] + # If the set has changed, reactivate non-determinsitic reactions reactivate = [] for r in inactive_reactions: @@ -428,12 +429,11 @@ def __integrate(self, integrator, integrator_options, curr_state, y0, model, cur model.listOfAssignmentRules] rhs = lambda t, y: TauHybridSolver.__f(t, y, *int_args) - + tau_step = max(1e-6, tau_step) if pure_ode: next_tau = model.tspan[-1] else: next_tau = curr_time + tau_step - curr_state['t'] = curr_time curr_state['time'] = curr_time @@ -443,6 +443,7 @@ def __integrate(self, integrator, integrator_options, curr_state, y0, model, cur method=integrator, dense_output=True, **integrator_options) + # Search for precise event times if len(model.listOfEvents): event_times = self.__detect_events(event_sensitivity, sol, model, delayed_events, @@ -647,7 +648,8 @@ def __compile_all(self, model): compiled_rate_rules = OrderedDict() for i, rr in enumerate(model.listOfRateRules.values()): compiled_rate_rules[rr.variable] = compile(rr.formula, '', 'eval') - + base_set = {s.name:rr for s, rr in compiled_rate_rules.items()} + compiled_rate_rules[frozenset()] = base_set compiled_inactive_reactions = OrderedDict() compiled_propensities = compiled_reactions.copy() From dc1d6a67eacf922c4ac4ac1eed301d83f2e90ba7 Mon Sep 17 00:00:00 2001 From: seanebum Date: Mon, 3 Aug 2020 16:21:16 -0400 Subject: [PATCH 05/16] better fix for hybrid model issue --- gillespy2/solvers/numpy/tau_hybrid_solver.py | 57 ++++++++++---------- 1 file changed, 28 insertions(+), 29 deletions(-) diff --git a/gillespy2/solvers/numpy/tau_hybrid_solver.py b/gillespy2/solvers/numpy/tau_hybrid_solver.py index 464098089..5e10f0685 100644 --- a/gillespy2/solvers/numpy/tau_hybrid_solver.py +++ b/gillespy2/solvers/numpy/tau_hybrid_solver.py @@ -56,7 +56,8 @@ def __init__(self): name = 'TauHybridSolver' rc = 0 - def __toggle_reactions(self, model, all_compiled, deterministic_reactions, dependencies, curr_state, det_spec): + def __toggle_reactions(self, model, all_compiled, deterministic_reactions, dependencies, + curr_state, det_spec, rr_sets): """ Helper method which is used to convert reaction channels into rate rules, and rate rules into reaction channels, as they are switched @@ -88,14 +89,14 @@ def __toggle_reactions(self, model, all_compiled, deterministic_reactions, depen inactive_reactions[r] = rxns.pop(r, None) # Check if this reaction set is already compiled and in use: - if deterministic_reactions in rate_rules.keys(): - return - + if deterministic_reactions in rr_sets.keys(): + return rr_sets[deterministic_reactions] + else: # Otherwise, this is a new determinstic reaction set that must be compiled - if not deterministic_reactions in rate_rules: - rate_rules[deterministic_reactions] = self.__create_diff_eqs(deterministic_reactions, model, dependencies) + return self.__create_diff_eqs(deterministic_reactions, model, + dependencies, rr_sets) - def __create_diff_eqs(self, comb, model, dependencies): + def __create_diff_eqs(self, comb, model, dependencies, rr_sets): """ Helper method used to convert stochastic reaction descriptions into differential equations, used dynamically throught the simulation. @@ -106,9 +107,9 @@ def __create_diff_eqs(self, comb, model, dependencies): # Initialize sample dict for spec in model.listOfSpecies: if spec in model.listOfRateRules: - diff_eqs[spec] = model.listOfRateRules[spec].formula + diff_eqs[model.listOfSpecies[spec]] = model.listOfRateRules[spec].formula else: - diff_eqs[spec] = '0' + diff_eqs[model.listOfSpecies[spec]] = '0' # loop through each det reaction and concatenate it's diff eq for each species for reaction in comb: @@ -124,20 +125,20 @@ def __create_diff_eqs(self, comb, model, dependencies): for dep in dependencies[reaction]: if factor[dep] != 0: if model.listOfSpecies[dep].mode == 'continuous': - diff_eqs[dep] += ' + {0}*({1})'.format(factor[dep], + diff_eqs[model.listOfSpecies[dep]] += ' + {0}*({1})'.format(factor[dep], model.listOfReactions[reaction].ode_propensity_function) else: - diff_eqs[dep] += ' + {0}*({1})'.format(factor[dep], + diff_eqs[model.listOfSpecies[dep]] += ' + {0}*({1})'.format(factor[dep], model.listOfReactions[reaction].propensity_function) for spec in model.listOfSpecies: - if diff_eqs[spec] == '0': - del diff_eqs[spec] + if diff_eqs[model.listOfSpecies[spec]] == '0': + del diff_eqs[model.listOfSpecies[spec]] # create a dictionary of compiled gillespy2 rate rules for spec, rate in diff_eqs.items(): - rate_rules[spec] = compile(gillespy2.RateRule(model.listOfSpecies[spec], rate).formula, '', 'eval') - + rate_rules[spec] = compile(gillespy2.RateRule(spec, rate).formula, '', 'eval') + rr_sets[comb] = rate_rules # save values return rate_rules def __flag_det_reactions(self, model, det_spec, det_rxn, dependencies): @@ -204,7 +205,7 @@ def __calculate_statistics(self, *switch_args): @staticmethod def __f(t, y, curr_state, species, reactions, rate_rules, propensities, - y_map, compiled_reactions, compiled_rate_rules, events, assignment_rules): + y_map, compiled_reactions, active_rr, events, assignment_rules): """ Evaluate the propensities for the reactions and the RHS of the Reactions and RateRules. Also evaluates boolean value of event triggers. @@ -219,9 +220,9 @@ def __f(t, y, curr_state, species, reactions, rate_rules, propensities, {**eval_globals, **curr_state}) else: curr_state[item] = y[index] - for rr in compiled_rate_rules: + for s, rr in active_rr.items(): try: - state_change[y_map[rr]] += eval(compiled_rate_rules[rr], {**eval_globals, **curr_state}) + state_change[y_map[s.name]] += eval(rr, {**eval_globals, **curr_state}) except ValueError: pass for i, r in enumerate(compiled_reactions): @@ -408,7 +409,7 @@ def __update_stochastic_rxn_states(self, model, compiled_reactions, curr_state): def __integrate(self, integrator, integrator_options, curr_state, y0, model, curr_time, propensities, y_map, compiled_reactions, - compiled_rate_rules, event_queue, + active_rr, event_queue, delayed_events, trigger_states, event_sensitivity, tau_step, pure_ode): """ @@ -424,7 +425,7 @@ def __integrate(self, integrator, integrator_options, curr_state, y0, model, cur model.listOfRateRules, propensities, y_map, compiled_reactions, - compiled_rate_rules, + active_rr, events, model.listOfAssignmentRules] @@ -509,7 +510,7 @@ def __integrate(self, integrator, integrator_options, curr_state, y0, model, cur def __simulate(self, integrator, integrator_options, curr_state, y0, model, curr_time, propensities, species, parameters, compiled_reactions, - compiled_rate_rules, y_map, trajectory, save_times, + active_rr, y_map, trajectory, save_times, delayed_events, trigger_states, event_sensitivity, tau_step, pure_ode, debug): """ @@ -542,7 +543,7 @@ def __simulate(self, integrator, integrator_options, curr_state, y0, model, curr sol, curr_time = self.__integrate(integrator, integrator_options, curr_state, y0, model, curr_time, propensities, y_map, compiled_reactions, - compiled_rate_rules, + active_rr, event_queue, delayed_events, trigger_states, @@ -648,8 +649,6 @@ def __compile_all(self, model): compiled_rate_rules = OrderedDict() for i, rr in enumerate(model.listOfRateRules.values()): compiled_rate_rules[rr.variable] = compile(rr.formula, '', 'eval') - base_set = {s.name:rr for s, rr in compiled_rate_rules.items()} - compiled_rate_rules[frozenset()] = base_set compiled_inactive_reactions = OrderedDict() compiled_propensities = compiled_reactions.copy() @@ -1041,12 +1040,12 @@ def __run(self, model, curr_state, curr_time, timeline, trajectory_base, initial print('det_rxn: {0}'.format(det_rxn)) # Set active reactions and rate rules for this integration step - if pure_stochastic: - active_rr = compiled_rate_rules + rr_sets = {frozenset() : compiled_rate_rules} # base rr set + if pure_stochastic or pure_ode: + active_rr = rr_sets[frozenset()] else: - self.__toggle_reactions(model, all_compiled, deterministic_reactions, dependencies, curr_state[0], - det_spec) - active_rr = compiled_rate_rules[deterministic_reactions] + active_rr = self.__toggle_reactions(model, all_compiled, deterministic_reactions, + dependencies, curr_state[0], det_spec, rr_sets) # Create integration initial state vector y0, y_map = self.__map_state(species, parameters, From 95e9b70aef08f37a855023b7f0af6424026f2527 Mon Sep 17 00:00:00 2001 From: seanebum Date: Mon, 3 Aug 2020 16:24:22 -0400 Subject: [PATCH 06/16] updating notebook with correct output --- .../hybrid_continuous_species.ipynb | 3988 ++++++++++++++++- 1 file changed, 3978 insertions(+), 10 deletions(-) diff --git a/examples/AdvancedFeatures/hybrid_continuous_species.ipynb b/examples/AdvancedFeatures/hybrid_continuous_species.ipynb index f3db07aaa..e96cf9cfa 100644 --- a/examples/AdvancedFeatures/hybrid_continuous_species.ipynb +++ b/examples/AdvancedFeatures/hybrid_continuous_species.ipynb @@ -23,7 +23,7 @@ "outputs": [], "source": [ "import sys, os\n", - "sys.path.append(os.path.abspath(os.path.join(os.getcwd(), '../../../')))\n", + "sys.path.append(os.path.abspath(os.path.join(os.getcwd(), '../../')))\n", "import gillespy2\n", "from gillespy2 import TauHybridSolver" ] @@ -116,8 +116,1460 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 324 ms, sys: 1.55 ms, total: 326 ms\n", - "Wall time: 327 ms\n" + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])\n", + "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", + "rate rules used: 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" + ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ - "results.plot()\n", - "\n", - "\n" + "results.plotplotly()" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { + "@webio": { + "lastCommId": null, + "lastKernelId": null + }, "kernelspec": { "display_name": "Python 3", "language": "python", @@ -166,9 +4134,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.6.9" } }, "nbformat": 4, "nbformat_minor": 2 -} \ No newline at end of file +} From 295eaa8ed04ce32877644de50f4d42a4a249100a Mon Sep 17 00:00:00 2001 From: seanebum Date: Mon, 3 Aug 2020 17:11:16 -0400 Subject: [PATCH 07/16] updated sbml link to newer SBML database --- test/test_SBML.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/test_SBML.py b/test/test_SBML.py index 2d2273840..6c1f891a8 100644 --- a/test/test_SBML.py +++ b/test/test_SBML.py @@ -19,7 +19,7 @@ def test_sbml_conversion(self): except ImportError: from urllib.request import urlopen - sbml_file = 'http://www.ebi.ac.uk/biomodels-main/download?mid=BIOMD0000000028' + sbml_file = 'https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000028.2?filename=BIOMD0000000028_url.xml' response = urlopen(sbml_file) tmp = tempfile.NamedTemporaryFile(delete=False) tmp.write(response.read()) From 0ff51d263601afb1751c92bb7cd6059531792a00 Mon Sep 17 00:00:00 2001 From: seanebum Date: Mon, 3 Aug 2020 17:11:57 -0400 Subject: [PATCH 08/16] added names for rate rules in hybrid solver unit test --- test/test_hybrid_solver.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/test/test_hybrid_solver.py b/test/test_hybrid_solver.py index ed38af403..ccb2c9406 100644 --- a/test/test_hybrid_solver.py +++ b/test/test_hybrid_solver.py @@ -21,8 +21,8 @@ def test_add_rate_rule_dict(self): model = Example() species2 = gillespy2.Species('test_species2', initial_value=2, mode='continuous') species3 = gillespy2.Species('test_species3', initial_value=3, mode='continuous') - rule2 = gillespy2.RateRule(species2, 'cos(t)') - rule3 = gillespy2.RateRule(variable=species3, formula='sin(t)') + rule2 = gillespy2.RateRule('rule2', species2, 'cos(t)') + rule3 = gillespy2.RateRule(name='rule3', variable=species3, formula='sin(t)') rate_rule_dict = {'rule2': rule2, 'rule3': rule3} model.add_species([species2, species3]) with self.assertRaises(ParameterError): From 22b2e0cc382ecd5a73dab6e35a20aab26e5042bc Mon Sep 17 00:00:00 2001 From: seanebum Date: Mon, 3 Aug 2020 17:14:18 -0400 Subject: [PATCH 09/16] fixed continuous models from the break caused for the hybrid model fix. Also, provided error catching for when rate rule variables are declared as strings --- gillespy2/core/model.py | 5 +++++ gillespy2/solvers/numpy/tau_hybrid_solver.py | 9 ++++++--- 2 files changed, 11 insertions(+), 3 deletions(-) diff --git a/gillespy2/core/model.py b/gillespy2/core/model.py index 36920d842..1510fed90 100644 --- a/gillespy2/core/model.py +++ b/gillespy2/core/model.py @@ -440,6 +440,11 @@ def add_rate_rule(self, rate_rules): raise ModelError('Invalid Rate Rule. Expression must be a non-empty string value') if rate_rules.variable == None: raise ModelError('A GillesPy2 Rate Rule must be associated with a valid variable') + if isinstance(rate_rules.variable, str): + v = rate_rules.variable + if v not in self.listOfSpecies and v not in self.listOfParameters: + raise ModelError( + 'Invalid variable entered for Rate Rule: {}'.format(rate_rules.name)) self.listOfRateRules[rate_rules.name] = rate_rules sanitized_rate_rule = RateRule(name='RR{}'.format(len(self._listOfRateRules))) diff --git a/gillespy2/solvers/numpy/tau_hybrid_solver.py b/gillespy2/solvers/numpy/tau_hybrid_solver.py index 5e10f0685..cdaec3832 100644 --- a/gillespy2/solvers/numpy/tau_hybrid_solver.py +++ b/gillespy2/solvers/numpy/tau_hybrid_solver.py @@ -428,7 +428,6 @@ def __integrate(self, integrator, integrator_options, curr_state, y0, model, cur active_rr, events, model.listOfAssignmentRules] - rhs = lambda t, y: TauHybridSolver.__f(t, y, *int_args) tau_step = max(1e-6, tau_step) if pure_ode: @@ -648,7 +647,11 @@ def __compile_all(self, model): 'eval') compiled_rate_rules = OrderedDict() for i, rr in enumerate(model.listOfRateRules.values()): - compiled_rate_rules[rr.variable] = compile(rr.formula, '', 'eval') + if isinstance(rr.variable, str): + compiled_rate_rules[model.listOfSpecies[rr.variable]] = compile( + rr.formula, '', 'eval') + else: + compiled_rate_rules[rr.variable] = compile(rr.formula, '', 'eval') compiled_inactive_reactions = OrderedDict() compiled_propensities = compiled_reactions.copy() @@ -1041,7 +1044,7 @@ def __run(self, model, curr_state, curr_time, timeline, trajectory_base, initial # Set active reactions and rate rules for this integration step rr_sets = {frozenset() : compiled_rate_rules} # base rr set - if pure_stochastic or pure_ode: + if pure_stochastic: active_rr = rr_sets[frozenset()] else: active_rr = self.__toggle_reactions(model, all_compiled, deterministic_reactions, From 920b8be51f17a9ba12c070509d51ffa7f0cc09fb Mon Sep 17 00:00:00 2001 From: Fin Carter Date: Tue, 4 Aug 2020 10:57:47 -0400 Subject: [PATCH 10/16] - Remove old output_results_buffer method from model.cpp, replace it with method that returns non-byte data. - Change ssa_c_solver.py, variable_ssa_c_solver.py to reflect these changes - Change how ths new return data is parsed into a results object in solverutils.py --- gillespy2/solvers/cpp/c_base/model.cpp | 32 ++++++------------- gillespy2/solvers/cpp/ssa_c_solver.py | 9 ++++-- .../solvers/cpp/variable_ssa_c_solver.py | 10 ++++-- gillespy2/solvers/utilities/solverutils.py | 21 ++++++------ 4 files changed, 33 insertions(+), 39 deletions(-) diff --git a/gillespy2/solvers/cpp/c_base/model.cpp b/gillespy2/solvers/cpp/c_base/model.cpp index 852450560..aebfcdb76 100644 --- a/gillespy2/solvers/cpp/c_base/model.cpp +++ b/gillespy2/solvers/cpp/c_base/model.cpp @@ -82,27 +82,15 @@ namespace Gillespy{ return os; } - void Simulation :: output_results_buffer(std :: ostream& os){ - double temp; - unsigned char* temp_byte = reinterpret_cast(&temp); - for(unsigned int i = 0; i < number_timesteps; i++){ - temp = timeline[i]; - for(unsigned int byte_i = 0; byte_i < sizeof(double); byte_i++){ - os << temp_byte[byte_i]; - } - for(unsigned int trajectory = 0; trajectory < number_trajectories; trajectory++){ - for(unsigned int j = 0; j < model -> number_species; j++){ - temp = trajectories[trajectory][i][j]; - for(unsigned int byte_i = 0; byte_i < sizeof(double); byte_i++){ - os << temp_byte[byte_i]; - } - } - } +void Simulation :: output_results_buffer(std::ostream& os){ + for (int i = 0 ; i < number_trajectories; i++){ + for (int j = 0; jnumber_species; k++){ + os<(&temp); - for (unsigned int byte_i=0; byte_i < sizeof(double); byte_i++){ - os << temp_byte[byte_i]; - } - } + } diff --git a/gillespy2/solvers/cpp/ssa_c_solver.py b/gillespy2/solvers/cpp/ssa_c_solver.py index 15fd8f940..188c3a251 100644 --- a/gillespy2/solvers/cpp/ssa_c_solver.py +++ b/gillespy2/solvers/cpp/ssa_c_solver.py @@ -233,10 +233,15 @@ def run(self=None, model=None, t=20, number_of_trajectories=1, timeout=0, pause = True return_code = 33 - # Parse/return results. + # Decode from byte, split by comma into array + stdout = stdout.decode('utf-8').split(',') + # Remove extra value at end of array + stdout = stdout[:-1] + # Parse/return results + if return_code in [0, 33]: trajectory_base, timeStopped = cutils._parse_binary_output(stdout, number_of_trajectories, - number_timesteps, len(model.listOfSpecies), + number_timesteps, len(model.listOfSpecies), stdout, pause=pause) if model.tspan[2] - model.tspan[1] == 1: timeStopped = int(timeStopped) diff --git a/gillespy2/solvers/cpp/variable_ssa_c_solver.py b/gillespy2/solvers/cpp/variable_ssa_c_solver.py index 375b07260..dae441ce9 100644 --- a/gillespy2/solvers/cpp/variable_ssa_c_solver.py +++ b/gillespy2/solvers/cpp/variable_ssa_c_solver.py @@ -290,12 +290,16 @@ def run(self=None, model=None, t=20, number_of_trajectories=1, timeout=0, stdout, stderr = simulation.communicate() pause = True return_code = 33 - + # Decode from byte, split by comma into array + stdout = stdout.decode('utf-8').split(',') + # Remove extra value at end of array + stdout = stdout[:-1] # Parse/return results. + if return_code in [0, 33]: trajectory_base, timeStopped = cutils._parse_binary_output(stdout, number_of_trajectories, - number_timesteps, - len(model.listOfSpecies), pause=pause) + number_timesteps, len(model.listOfSpecies), + stdout, pause=pause) if model.tspan[2] - model.tspan[1] == 1: timeStopped = int(timeStopped) diff --git a/gillespy2/solvers/utilities/solverutils.py b/gillespy2/solvers/utilities/solverutils.py index 03b09b7f5..a33c2d2d4 100644 --- a/gillespy2/solvers/utilities/solverutils.py +++ b/gillespy2/solvers/utilities/solverutils.py @@ -75,7 +75,7 @@ def _write_reactions(outfile, model, reactions, species): outfile.write("model.reactions[{0}].affected_reactions.push_back({1});\n".format(i, j)) -def _parse_binary_output(results_buffer, number_of_trajectories, number_timesteps, number_species, pause=False): +def _parse_binary_output(results_buffer, number_of_trajectories, number_timesteps, number_species, data, pause=False): """ This function reads binary output from a CPP simulation :param results_buffer: stdout of the CPP simulation ran @@ -90,25 +90,22 @@ def _parse_binary_output(results_buffer, number_of_trajectories, number_timestep timeout. """ trajectory_base = np.empty((number_of_trajectories, number_timesteps, number_species+1)) - step_size = number_species * number_of_trajectories + 1 #1 for timestep - data = np.frombuffer(results_buffer, dtype=np.float64) + # Timestopped is added to the end of the data, when a simulation completes or is paused + np.set_printoptions(suppress=True) if pause: timeStopped = data[-1] else: timeStopped = 0 - assert(len(data) == (number_of_trajectories*number_timesteps*number_species + number_timesteps)+1) - for timestep in range(number_timesteps): - index = step_size * timestep - trajectory_base[:, timestep, 0] = data[index] - index += 1 - for trajectory in range(number_of_trajectories): - for species in range(number_species): - trajectory_base[trajectory, timestep, 1 + species] = data[index + species] - index += number_species + for t in range(number_of_trajectories): + for i in range(number_timesteps*(number_species+1)): + index = i + (number_timesteps*(number_species+1)*t) + trajectory_base[t][i//(number_species+1)][i % (number_species+1)] = data[index] + return trajectory_base, timeStopped + def c_solver_resume(timeStopped, simulation_data, t, resume=None): """ If a simulation is being resumed from a previous simulation, this function is called in the VariableSSACSolver, From 2841afd2c33abc23d91dbde93c200f8fddec8b80 Mon Sep 17 00:00:00 2001 From: Fin Carter Date: Tue, 4 Aug 2020 11:26:51 -0400 Subject: [PATCH 11/16] - Fix pause/resume for this PR (WIP) --- gillespy2/solvers/cpp/c_base/model.cpp | 1 + gillespy2/solvers/cpp/ssa_c_solver.py | 3 --- gillespy2/solvers/cpp/variable_ssa_c_solver.py | 2 -- gillespy2/solvers/utilities/solverutils.py | 4 ++-- 4 files changed, 3 insertions(+), 7 deletions(-) diff --git a/gillespy2/solvers/cpp/c_base/model.cpp b/gillespy2/solvers/cpp/c_base/model.cpp index aebfcdb76..29fbd9da6 100644 --- a/gillespy2/solvers/cpp/c_base/model.cpp +++ b/gillespy2/solvers/cpp/c_base/model.cpp @@ -91,6 +91,7 @@ void Simulation :: output_results_buffer(std::ostream& os){ } } } + os<<(int)current_time; } } diff --git a/gillespy2/solvers/cpp/ssa_c_solver.py b/gillespy2/solvers/cpp/ssa_c_solver.py index 188c3a251..f63c4cb3f 100644 --- a/gillespy2/solvers/cpp/ssa_c_solver.py +++ b/gillespy2/solvers/cpp/ssa_c_solver.py @@ -235,8 +235,6 @@ def run(self=None, model=None, t=20, number_of_trajectories=1, timeout=0, # Decode from byte, split by comma into array stdout = stdout.decode('utf-8').split(',') - # Remove extra value at end of array - stdout = stdout[:-1] # Parse/return results if return_code in [0, 33]: @@ -245,7 +243,6 @@ def run(self=None, model=None, t=20, number_of_trajectories=1, timeout=0, pause=pause) if model.tspan[2] - model.tspan[1] == 1: timeStopped = int(timeStopped) - # Format results self.simulation_data = [] for trajectory in range(number_of_trajectories): diff --git a/gillespy2/solvers/cpp/variable_ssa_c_solver.py b/gillespy2/solvers/cpp/variable_ssa_c_solver.py index dae441ce9..0a2aa3465 100644 --- a/gillespy2/solvers/cpp/variable_ssa_c_solver.py +++ b/gillespy2/solvers/cpp/variable_ssa_c_solver.py @@ -292,8 +292,6 @@ def run(self=None, model=None, t=20, number_of_trajectories=1, timeout=0, return_code = 33 # Decode from byte, split by comma into array stdout = stdout.decode('utf-8').split(',') - # Remove extra value at end of array - stdout = stdout[:-1] # Parse/return results. if return_code in [0, 33]: diff --git a/gillespy2/solvers/utilities/solverutils.py b/gillespy2/solvers/utilities/solverutils.py index a33c2d2d4..460ddce92 100644 --- a/gillespy2/solvers/utilities/solverutils.py +++ b/gillespy2/solvers/utilities/solverutils.py @@ -92,9 +92,9 @@ def _parse_binary_output(results_buffer, number_of_trajectories, number_timestep trajectory_base = np.empty((number_of_trajectories, number_timesteps, number_species+1)) # Timestopped is added to the end of the data, when a simulation completes or is paused - np.set_printoptions(suppress=True) if pause: - timeStopped = data[-1] + timeStopped = int(data[-1]) + data.pop() else: timeStopped = 0 for t in range(number_of_trajectories): From 54ece237e57f594005d62043d6c49f43ab455f24 Mon Sep 17 00:00:00 2001 From: Fin Carter Date: Fri, 7 Aug 2020 13:24:22 -0400 Subject: [PATCH 12/16] - Change #include in model.h to include C++ - Fix issue where makefile not being properly path'd when attempting to compile a model outside of the root GillesPy2 directory --- gillespy2/solvers/cpp/c_base/makefile | 10 +++++--- gillespy2/solvers/cpp/c_base/model.h | 8 +++--- gillespy2/solvers/cpp/ssa_c_solver.py | 25 +++++++++++-------- .../solvers/cpp/variable_ssa_c_solver.py | 21 ++++++++++------ 4 files changed, 41 insertions(+), 23 deletions(-) diff --git a/gillespy2/solvers/cpp/c_base/makefile b/gillespy2/solvers/cpp/c_base/makefile index d2bdd317a..60bb51d6f 100644 --- a/gillespy2/solvers/cpp/c_base/makefile +++ b/gillespy2/solvers/cpp/c_base/makefile @@ -1,16 +1,20 @@ CC=g++ CFLAGS=-c -std=c++14 -Wall -O3 -SIMFLAGS = -std=c++14 -Wall -O3 +SIMFLAGS = -L. -std=c++14 -Wall -O3 DEPS = model.h ssa.h OBJ = model.o ssa.o +.PHONY: all all: UserSimulation %.o: %.cpp $(DEPS) $(CC) -c -o $@ $< $(CFLAGS) -UserSimulation: $(OBJ) - $(CC) UserSimulation.cpp $(SIMFLAGS) -o $@ $^ +UserSimulation.o: + $(CC) -c -o UserSimulation.o UserSimulation.cpp $(CFLAGS) + +UserSimulation: $(OBJ) UserSimulation.o + $(CC) -o UserSimulation $(OBJ) UserSimulation.o $(SIMFLAGS) cleanSimulation: rm -f UserSimulation diff --git a/gillespy2/solvers/cpp/c_base/model.h b/gillespy2/solvers/cpp/c_base/model.h index 372b18fb3..e5047a21c 100644 --- a/gillespy2/solvers/cpp/c_base/model.h +++ b/gillespy2/solvers/cpp/c_base/model.h @@ -4,7 +4,7 @@ #include #include #include -#include +#include namespace Gillespy{ @@ -24,12 +24,13 @@ namespace Gillespy{ //Represents a model of reactions and species struct Model{ + void update_affected_reactions(); + unsigned int number_species; std :: unique_ptr species; unsigned int number_reactions; std :: unique_ptr reactions; Model(std :: vector species_names, std :: vector species_populations, std :: vector reaction_names); - void update_affected_reactions(); }; //Interface class to represent container for propensity functions @@ -43,6 +44,8 @@ namespace Gillespy{ //Represents simulation return data struct Simulation{ Model* model; + ~Simulation(); + double* timeline; double end_time; double current_time; @@ -53,7 +56,6 @@ namespace Gillespy{ unsigned int*** trajectories; IPropensityFunction *propensity_function; Simulation(Model* model, unsigned int number_trajectories, unsigned int number_timesteps, double end_time, IPropensityFunction* propensity_function, int random_seed, double current_time); - ~Simulation(); friend std :: ostream& operator<<(std :: ostream& os, const Simulation& simulation); void output_results_buffer(std :: ostream& os); }; diff --git a/gillespy2/solvers/cpp/ssa_c_solver.py b/gillespy2/solvers/cpp/ssa_c_solver.py index f63c4cb3f..9d4d3546b 100644 --- a/gillespy2/solvers/cpp/ssa_c_solver.py +++ b/gillespy2/solvers/cpp/ssa_c_solver.py @@ -11,7 +11,7 @@ GILLESPY_PATH = os.path.dirname(inspect.getfile(gillespy2)) GILLESPY_C_DIRECTORY = os.path.join(GILLESPY_PATH, 'solvers/cpp/c_base') - +MAKE_FILE = os.path.dirname(os.path.abspath(__file__))+'/c_base/makefile' def _write_constants(outfile, model, reactions, species, parameter_mappings, resume): """ @@ -135,16 +135,21 @@ def __compile(self): if self.resume[0].model != self.model: raise gillespyError.ModelError('When resuming, one must not alter the model being resumed.') else: - built = subprocess.run(["make", "-C", self.output_directory, 'UserSimulation'], stdout=subprocess.PIPE, - stderr=subprocess.PIPE) - else: - try: - cleaned = subprocess.run(["make", "-C", self.output_directory, 'cleanSimulation'], - stdout=subprocess.PIPE, stderr=subprocess.PIPE) built = subprocess.run(["make", "-C", self.output_directory, 'UserSimulation'], - stdout=subprocess.PIPE, stderr=subprocess.PIPE) - except KeyboardInterrupt: - log.warning("Solver has been interrupted during compile time, unexpected behavior may occur.") + stdout=subprocess.PIPE, stderr=subprocess.PIPE) + else: + try: + cleaned = subprocess.run( + ["make", "-C", self.output_directory, '-f', MAKE_FILE, + 'cleanSimulation'], + stdout=subprocess.PIPE, stderr=subprocess.PIPE) + built = subprocess.run( + ["make", "-C", self.output_directory, '-f', MAKE_FILE, + 'UserSimulation'], stdout=subprocess.PIPE, + stderr=subprocess.PIPE) + except KeyboardInterrupt: + log.warning( + "Solver has been interrupted during compile time, unexpected behavior may occur.") if built.returncode == 0: self.__compiled = True diff --git a/gillespy2/solvers/cpp/variable_ssa_c_solver.py b/gillespy2/solvers/cpp/variable_ssa_c_solver.py index 0a2aa3465..549e2e141 100644 --- a/gillespy2/solvers/cpp/variable_ssa_c_solver.py +++ b/gillespy2/solvers/cpp/variable_ssa_c_solver.py @@ -11,6 +11,7 @@ GILLESPY_PATH = os.path.dirname(inspect.getfile(gillespy2)) GILLESPY_C_DIRECTORY = os.path.join(GILLESPY_PATH, 'solvers/cpp/c_base') +MAKE_FILE = os.path.dirname(os.path.abspath(__file__))+'/c_base/makefile' def _write_variables(outfile, model, reactions, species, parameters, parameter_mappings, resume=None): @@ -149,16 +150,22 @@ def __compile(self): if self.resume[0].model != self.model: raise gillespyError.ModelError('When resuming, one must not alter the model being resumed.') else: - built = subprocess.run(["make", "-C", self.output_directory, 'UserSimulation'], stdout=subprocess.PIPE, - stderr=subprocess.PIPE) + built = subprocess.run( + ["make", "-C", self.output_directory, 'UserSimulation'], + stdout=subprocess.PIPE, stderr=subprocess.PIPE) else: try: - cleaned = subprocess.run(["make", "-C", self.output_directory, 'cleanSimulation'], - stdout=subprocess.PIPE, stderr=subprocess.PIPE) - built = subprocess.run(["make", "-C", self.output_directory, 'UserSimulation'], - stdout=subprocess.PIPE, stderr=subprocess.PIPE) + cleaned = subprocess.run( + ["make", "-C", self.output_directory, '-f', MAKE_FILE, + 'cleanSimulation'], + stdout=subprocess.PIPE, stderr=subprocess.PIPE) + built = subprocess.run( + ["make", "-C", self.output_directory, '-f', MAKE_FILE, + 'UserSimulation'], stdout=subprocess.PIPE, + stderr=subprocess.PIPE) except KeyboardInterrupt: - log.warning("Solver has been interrupted during compile time, unexpected behavior may occur.") + log.warning( + "Solver has been interrupted during compile time, unexpected behavior may occur.") if built.returncode == 0: self.__compiled = True From 2b0a81780743f995b62658f25ac02747755bde37 Mon Sep 17 00:00:00 2001 From: Fin Carter Date: Fri, 7 Aug 2020 13:47:24 -0400 Subject: [PATCH 13/16] -Output fix --- .../hybrid_continuous_species.ipynb | 3306 +++++------------ 1 file changed, 919 insertions(+), 2387 deletions(-) diff --git a/examples/AdvancedFeatures/hybrid_continuous_species.ipynb b/examples/AdvancedFeatures/hybrid_continuous_species.ipynb index e96cf9cfa..355d8e1f7 100644 --- a/examples/AdvancedFeatures/hybrid_continuous_species.ipynb +++ b/examples/AdvancedFeatures/hybrid_continuous_species.ipynb @@ -19,8 +19,21 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, - "outputs": [], + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [ + { + "name": "stderr", + "text": [ + "C:\\Users\\finca\\PycharmProjects\\GillesPy2\\gillespy2\\solvers\\numpy\\tau_hybrid_solver.py:872: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n", + " if model.listOfSpecies[s].mode is 'continuous':\n" + ], + "output_type": "stream" + } + ], "source": [ "import sys, os\n", "sys.path.append(os.path.abspath(os.path.join(os.getcwd(), '../../')))\n", @@ -39,7 +52,11 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [], "source": [ "\n", @@ -91,7 +108,10 @@ "cell_type": "code", "execution_count": 3, "metadata": { - "scrolled": true + "scrolled": true, + "pycharm": { + "is_executing": false + } }, "outputs": [], "source": [ @@ -109,1468 +129,18 @@ "cell_type": "code", "execution_count": 4, "metadata": { - "scrolled": true + "scrolled": true, + "pycharm": { + "is_executing": false + } }, "outputs": [ { "name": "stdout", - "output_type": "stream", - "text": [ - "rr sets: {frozenset(): OrderedDict([(, at 0x7f0a2754b930, file \"\", line 1>)])}\n", - "rate rules used: OrderedDict([(, at 0x7f0a2754b930, file \"\", line 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+ "text/plain": [ + "
" + ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ - "results.plotplotly()" + "results.plot()" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": { "pycharm": { "is_executing": false @@ -2671,4 +201,4 @@ }, "nbformat": 4, "nbformat_minor": 2 -} \ No newline at end of file +} diff --git a/gillespy2/solvers/numpy/tau_hybrid_solver.py b/gillespy2/solvers/numpy/tau_hybrid_solver.py index 7d6720bd7..1d1a270d3 100644 --- a/gillespy2/solvers/numpy/tau_hybrid_solver.py +++ b/gillespy2/solvers/numpy/tau_hybrid_solver.py @@ -429,7 +429,10 @@ def __integrate(self, integrator, integrator_options, curr_state, y0, model, cur events, model.listOfAssignmentRules] rhs = lambda t, y: TauHybridSolver.__f(t, y, *int_args) - tau_step = max(1e-6, tau_step) + if 'min_step' in integrator_options: + tau_step = max(min_step, tau_step) + else: + tau_step = max(1e-6, tau_step) if pure_ode: next_tau = model.tspan[-1] else: @@ -869,7 +872,7 @@ def run(self, model, t=20, number_of_trajectories=1, increment=0.05, seed=None, if live_output_options['type'] == "graph": for i, s in enumerate(list(model._listOfSpecies.keys())): - if model.listOfSpecies[s].mode is 'continuous': + if model.listOfSpecies[s].mode == 'continuous': log.warning('display \"type\" = \"graph\" not recommended with continuous species. ' 'Try display \"type\" = \"text\" or \"progress\".') break From df731c56ef8953ae7eb7890527fbc401b9d0b1c5 Mon Sep 17 00:00:00 2001 From: seanebum Date: Fri, 7 Aug 2020 11:02:16 -0400 Subject: [PATCH 16/16] changed "min_step" to "integrator_options["min_step"]... oops --- gillespy2/solvers/numpy/tau_hybrid_solver.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/gillespy2/solvers/numpy/tau_hybrid_solver.py b/gillespy2/solvers/numpy/tau_hybrid_solver.py index 1d1a270d3..b9018e6e2 100644 --- a/gillespy2/solvers/numpy/tau_hybrid_solver.py +++ b/gillespy2/solvers/numpy/tau_hybrid_solver.py @@ -430,7 +430,7 @@ def __integrate(self, integrator, integrator_options, curr_state, y0, model, cur model.listOfAssignmentRules] rhs = lambda t, y: TauHybridSolver.__f(t, y, *int_args) if 'min_step' in integrator_options: - tau_step = max(min_step, tau_step) + tau_step = max(integrator_options['min_step'], tau_step) else: tau_step = max(1e-6, tau_step) if pure_ode: