Add random functions tests and truncexpon (#441)

- Add random functions tests
- Fix truncation in Vensim's RANDOM NORMAL
- Support Vensim's RANDOM EXPONENTIAL

Author: enekomartinmartinez

docs/tables/functions.tab

@@ -46,3 +46,7 @@ ALLOCATE AVAILABLE	"ALLOCATE AVAILABLE(request, pp, avail)"			"AllocateAvailable
 ALLOCATE BY PRIORITY	"ALLOCATE BY PRIORITY(request, priority, size, width, supply)"			"AllocateByPriorityStructure(request, priority, size, width, supply)"	allocate_by_priority(request, priority, width, supply)
 INITIAL	INITIAL(value)	init	init(value)	InitialStructure(value)	pysd.statefuls.Initial
 SAMPLE IF TRUE	"SAMPLE IF TRUE(condition, input, initial_value)"			"SampleIfTrueStructure(condition, input, initial_value)"	pysd.statefuls.SampleIfTrue(...)
+RANDOM 0 1	"RANDOM 0 1()"			"CallStructure('random_0_1', ())"	np.random.uniform(0, 1, size=final_shape)
+RANDOM UNIFORM	"RANDOM UNIFORM(m, x, s)"			"CallStructure('random_uniform', (m, x, s))"	np.random.uniform(m, x, size=final_shape)
+RANDOM NORMAL	"RANDOM NORMAL(m, x, h, r, s)"			"CallStructure('random_normal', (m, x, h, r, s))"	stats.truncnorm.rvs((m-h)/r, (x-h)/r, loc=h, scale=r, size=final_shape)
+RANDOM EXPONENTIAL	"RANDOM EXPONENTIAL(m, x, h, r, s)"			"CallStructure('random_exponential', (m, x, h, r, s))"	stats.truncexpon.rvs((x-np.maximum(m, h))/r, loc=np.maximum(m, h), scale=r, size=final_shape)

docs/whats_new.rst

@@ -1,5 +1,33 @@
 What's New
 ==========
+v3.14.0 (2024/04/24)
+--------------------
+New Features
+~~~~~~~~~~~~
+- Support Vensim's `RANDOM EXPONENTIAL <https://www.vensim.com/documentation/fn_random.html>`_ function (:issue:`107`). (`@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
+
+Breaking changes
+~~~~~~~~~~~~~~~~
+
+Deprecations
+~~~~~~~~~~~~
+
+Bug fixes
+~~~~~~~~~
+- Fix truncation in Vensim's `RANDOM NORMAL <https://www.vensim.com/documentation/fn_random.html>`_ function translation. (`@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
+
+Documentation
+~~~~~~~~~~~~~
+- Add supported random functions to the documentation tables. (`@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
+
+Performance
+~~~~~~~~~~~
+
+Internal Changes
+~~~~~~~~~~~~~~~~
+- Add test for random functions including comparison with Vensim outputs and expected values (:issue:`107`). (`@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
+- Allow to add multiple imports by the python function call builder. (`@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
+
 v3.13.4 (2024/02/29)
 --------------------
 New Features

pysd/_version.py

@@ -1 +1 @@
-__version__ = "3.13.4"
+__version__ = "3.14.0"

pysd/builders/python/python_expressions_builder.py

@@ -606,9 +606,9 @@ def build_function_call(self, arguments: dict) -> BuildAST:
         """
         # Get the function expression from the functionspace
         expression, modules = functionspace[self.function]
-        if modules:
+        for module in modules:
             # Update module dependencies in imports
-            self.section.imports.add(*modules)
+            self.section.imports.add(*module)
 
         calls = self.join_calls(arguments)
 

pysd/builders/python/python_functions.py

@@ -2,118 +2,120 @@
 # functions that can be diretcly applied over an array
 functionspace = {
     # directly build functions without dependencies
-    "elmcount": ("len(%(0)s)", None),
+    "elmcount": ("len(%(0)s)", ()),
 
     # directly build numpy based functions
-    "pi": ("np.pi", ("numpy",)),
-    "abs": ("np.abs(%(0)s)", ("numpy",)),
-    "power": ("np.power(%(0)s,%(1)s)", ("numpy",)),
-    "min": ("np.minimum(%(0)s, %(1)s)", ("numpy",)),
-    "max": ("np.maximum(%(0)s, %(1)s)", ("numpy",)),
-    "exp": ("np.exp(%(0)s)", ("numpy",)),
-    "sin": ("np.sin(%(0)s)", ("numpy",)),
-    "cos": ("np.cos(%(0)s)", ("numpy",)),
-    "tan": ("np.tan(%(0)s)", ("numpy",)),
-    "arcsin": ("np.arcsin(%(0)s)", ("numpy",)),
-    "arccos": ("np.arccos(%(0)s)", ("numpy",)),
-    "arctan": ("np.arctan(%(0)s)", ("numpy",)),
-    "sinh": ("np.sinh(%(0)s)", ("numpy",)),
-    "cosh": ("np.cosh(%(0)s)", ("numpy",)),
-    "tanh": ("np.tanh(%(0)s)", ("numpy",)),
-    "sqrt": ("np.sqrt(%(0)s)", ("numpy",)),
-    "ln": ("np.log(%(0)s)", ("numpy",)),
-    "log": ("(np.log(%(0)s)/np.log(%(1)s))", ("numpy",)),
-    # NUMPY: "invert_matrix": ("np.linalg.inv(%(0)s)", ("numpy",)),
+    "pi": ("np.pi", (("numpy",),)),
+    "abs": ("np.abs(%(0)s)", (("numpy",),)),
+    "power": ("np.power(%(0)s,%(1)s)", (("numpy",),)),
+    "min": ("np.minimum(%(0)s, %(1)s)", (("numpy",),)),
+    "max": ("np.maximum(%(0)s, %(1)s)", (("numpy",),)),
+    "exp": ("np.exp(%(0)s)", (("numpy",),)),
+    "sin": ("np.sin(%(0)s)", (("numpy",),)),
+    "cos": ("np.cos(%(0)s)", (("numpy",),)),
+    "tan": ("np.tan(%(0)s)", (("numpy",),)),
+    "arcsin": ("np.arcsin(%(0)s)", (("numpy",),)),
+    "arccos": ("np.arccos(%(0)s)", (("numpy",),)),
+    "arctan": ("np.arctan(%(0)s)", (("numpy",),)),
+    "sinh": ("np.sinh(%(0)s)", (("numpy",),)),
+    "cosh": ("np.cosh(%(0)s)", (("numpy",),)),
+    "tanh": ("np.tanh(%(0)s)", (("numpy",),)),
+    "sqrt": ("np.sqrt(%(0)s)", (("numpy",),)),
+    "ln": ("np.log(%(0)s)", (("numpy",),)),
+    "log": ("(np.log(%(0)s)/np.log(%(1)s))", (("numpy",),)),
+    # NUMPY: "invert_matrix": ("np.linalg.inv(%(0)s)", (("numpy",),)),
 
     # vector functions with axis to apply over
     # NUMPY:
-    # "prod": "np.prod(%(0)s, axis=%(axis)s)", ("numpy",)),
-    # "sum": "np.sum(%(0)s, axis=%(axis)s)", ("numpy",)),
-    # "vmax": "np.max(%(0)s, axis=%(axis)s)", ("numpy", )),
-    # "vmin": "np.min(%(0)s, axis=%(axis)s)", ("numpy",))
-    "prod": ("prod(%(0)s, dim=%(axis)s)", ("functions", "prod")),
-    "sum": ("sum(%(0)s, dim=%(axis)s)", ("functions", "sum")),
-    "vmax": ("vmax(%(0)s, dim=%(axis)s)", ("functions", "vmax")),
-    "vmin": ("vmin(%(0)s, dim=%(axis)s)", ("functions", "vmin")),
-    "vmax_xmile": ("vmax(%(0)s)", ("functions", "vmax")),
-    "vmin_xmile": ("vmin(%(0)s)", ("functions", "vmin")),
+    # "prod": "np.prod(%(0)s, axis=%(axis)s)", (("numpy",),)),
+    # "sum": "np.sum(%(0)s, axis=%(axis)s)", (("numpy",),)),
+    # "vmax": "np.max(%(0)s, axis=%(axis)s)", ("numpy",),)),
+    # "vmin": "np.min(%(0)s, axis=%(axis)s)", (("numpy",),))
+    "prod": ("prod(%(0)s, dim=%(axis)s)", (("functions", "prod"),)),
+    "sum": ("sum(%(0)s, dim=%(axis)s)", (("functions", "sum"),)),
+    "vmax": ("vmax(%(0)s, dim=%(axis)s)", (("functions", "vmax"),)),
+    "vmin": ("vmin(%(0)s, dim=%(axis)s)", (("functions", "vmin"),)),
+    "vmax_xmile": ("vmax(%(0)s)", (("functions", "vmax"),)),
+    "vmin_xmile": ("vmin(%(0)s)", (("functions", "vmin"),)),
     "vector_select": (
         "vector_select(%(0)s, %(1)s, %(axis)s, %(2)s, %(3)s, %(4)s)",
-        ("functions", "vector_select")
+        (("functions", "vector_select"),)
     ),
 
     # functions defined in pysd.py_bakcend.functions
     "active_initial": (
         "active_initial(__data[\"time\"].stage, lambda: %(0)s, %(1)s)",
-        ("functions", "active_initial")),
+        (("functions", "active_initial"),)),
     "if_then_else": (
         "if_then_else(%(0)s, lambda: %(1)s, lambda: %(2)s)",
-        ("functions", "if_then_else")),
+        (("functions", "if_then_else"),)),
     "integer": (
         "integer(%(0)s)",
-        ("functions", "integer")),
+        (("functions", "integer"),)),
     "invert_matrix": (  # NUMPY: remove
         "invert_matrix(%(0)s)",
-        ("functions", "invert_matrix")),  # NUMPY: remove
+        (("functions", "invert_matrix"),)),  # NUMPY: remove
     "modulo": (
         "modulo(%(0)s, %(1)s)",
-        ("functions", "modulo")),
+        (("functions", "modulo"),)),
     "pulse": (
         "pulse(__data['time'], %(0)s, width=%(1)s)",
-        ("functions", "pulse")),
+        (("functions", "pulse"),)),
     "Xpulse": (
         "pulse(__data['time'], %(0)s, magnitude=%(1)s)",
-        ("functions", "pulse")),
+        (("functions", "pulse"),)),
     "pulse_train": (
         "pulse(__data['time'], %(0)s, repeat_time=%(1)s, width=%(2)s, "\
         "end=%(3)s)",
-        ("functions", "pulse")),
+        (("functions", "pulse"),)),
     "Xpulse_train": (
         "pulse(__data['time'], %(0)s, repeat_time=%(1)s, magnitude=%(2)s)",
-        ("functions", "pulse")),
+        (("functions", "pulse"),)),
     "get_time_value": (
         "get_time_value(__data['time'], %(0)s, %(1)s, %(2)s)",
-        ("functions", "get_time_value")),
+        (("functions", "get_time_value"),)),
     "quantum": (
         "quantum(%(0)s, %(1)s)",
-        ("functions", "quantum")),
+        (("functions", "quantum"),)),
     "Xramp": (
         "ramp(__data['time'], %(0)s, %(1)s)",
-        ("functions", "ramp")),
+        (("functions", "ramp"),)),
     "ramp": (
         "ramp(__data['time'], %(0)s, %(1)s, %(2)s)",
-        ("functions", "ramp")),
+        (("functions", "ramp"),)),
     "step": (
         "step(__data['time'], %(0)s, %(1)s)",
-        ("functions", "step")),
+        (("functions", "step"),)),
     "xidz": (
         "xidz(%(0)s, %(1)s, %(2)s)",
-        ("functions", "xidz")),
+        (("functions", "xidz"),)),
     "zidz": (
         "zidz(%(0)s, %(1)s)",
-        ("functions", "zidz")),
+        (("functions", "zidz"),)),
     "vector_sort_order": (
         "vector_sort_order(%(0)s, %(1)s)",
-        ("functions", "vector_sort_order")),
+        (("functions", "vector_sort_order"),)),
     "vector_reorder": (
         "vector_reorder(%(0)s, %(1)s)",
-        ("functions", "vector_reorder")),
+        (("functions", "vector_reorder"),)),
     "vector_rank": (
         "vector_rank(%(0)s, %(1)s)",
-        ("functions", "vector_rank")),
+        (("functions", "vector_rank"),)),
 
     # random functions must have the shape of the component subscripts
     # most of them are shifted, scaled and truncated
-    # TODO: it is difficult to find same parametrization in Python,
-    # maybe build a new model
     "random_0_1": (
         "np.random.uniform(0, 1, size=%(size)s)",
-        ("numpy",)),
+        (("numpy",),)),
     "random_uniform": (
         "np.random.uniform(%(0)s, %(1)s, size=%(size)s)",
-        ("numpy",)),
+        (("numpy",),)),
     "random_normal": (
-        "stats.truncnorm.rvs(%(0)s, %(1)s, loc=%(2)s, scale=%(3)s,"
-        " size=%(size)s)",
-        ("scipy", "stats")),
+        "stats.truncnorm.rvs((%(0)s-%(2)s)/%(3)s, (%(1)s-%(2)s)/%(3)s,"
+        " loc=%(2)s, scale=%(3)s, size=%(size)s)",
+        (("scipy", "stats"),)),
+    "random_exponential": (
+        "stats.truncexpon.rvs((%(1)s-np.maximum(%(0)s, %(2)s))/%(3)s,"
+        " loc=np.maximum(%(0)s, %(2)s), scale=%(3)s, size=%(size)s)",
+        (("scipy", "stats"), ("numpy",),)),
 }

tests/conftest.py

@@ -1,13 +1,18 @@
 import shutil
 from pathlib import Path
+from dataclasses import dataclass
+
 
 import pytest
+
 from pysd import read_vensim, read_xmile, load
 from pysd.translators.vensim.vensim_utils import supported_extensions as\
     vensim_extensions
 from pysd.translators.xmile.xmile_utils import supported_extensions as\
     xmile_extensions
 
+from pysd.builders.python.imports import ImportsManager
+
 
 @pytest.fixture(scope="session")
 def _root():
@@ -21,6 +26,12 @@ def _test_models(_root):
     return _root.joinpath("test-models/tests")
 
 
+@pytest.fixture(scope="session")
+def _test_random(_root):
+    # test-models directory
+    return _root.joinpath("test-models/random")
+
+
 @pytest.fixture(scope="class")
 def shared_tmpdir(tmp_path_factory):
     # shared temporary directory for each class
@@ -58,3 +69,38 @@ def ignore_warns():
         "future version. Use timezone-aware objects to represent datetimes "
         "in UTC.*",
     ]
+
+
+@pytest.fixture(scope="session")
+def random_size():
+    # size of generated random samples
+    return int(1e6)
+
+
+@dataclass
+class FakeComponent:
+    element: str
+    section: object
+    subscripts_dict: dict
+
+
+@dataclass
+class FakeSection:
+    namespace: object
+    macrospace: dict
+    imports: object
+
+
+@dataclass
+class FakeNamespace:
+    cleanspace: dict
+
+
+@pytest.fixture(scope="function")
+def fake_component():
+    # fake_component used to translate random functions to python
+    return FakeComponent(
+        '',
+        FakeSection(FakeNamespace({}), {}, ImportsManager()),
+        {}
+    )