Merge pull request #87 from CURENT/misc

Misc

README.md

@@ -59,7 +59,9 @@ Use the following resources to get involved.
 
 # Installation
 
-***NOTE:*** ``kvxopt`` is recommended to install via ``conda`` as sometimes ``pip`` struggles to set the correct path for compiled libraries.
+***NOTE:***
+- ``kvxopt`` is recommended to install via ``conda`` as sometimes ``pip`` struggles to set the correct path for compiled libraries
+- `cvxpy` versions **below 1.5** are incompatible with `numpy` versions **2.0 and above**.
 
 AMS is released as ``ltbams`` on PyPI and conda-forge.
 Install from PyPI using pip:

ams/cli.py

@@ -111,7 +111,7 @@ def preamble():
 
 def main():
  """
- Entry point of the ANDES command-line interface.
+ Entry point of the AMS command-line interface.
  """
 
  parser = create_parser()

ams/interop/andes.py

@@ -11,6 +11,7 @@
 from andes.system import System as andes_System
 
 from ams.io import input_formats
+from ams.shared import nan
 
 logger = logging.getLogger(__name__)
 
@@ -260,7 +261,7 @@ def parse_addfile(adsys, amsys, addfile):
  except KeyError: # set the most frequent string as the model name
  split_list = []
  for item in df[idxn].values:
- if item is None or np.nan:
+ if item is None or nan:
  continue
  try:
  split_list.append(item.split('_'))
@@ -295,7 +296,7 @@ def parse_addfile(adsys, amsys, addfile):
  # add dynamic models
  for name, df in df_models.items():
  # drop rows that all nan
- df.replace(['', ' '], np.NaN, inplace=True) # replace empty string with nan
+ df.replace(['', ' '], nan, inplace=True) # replace empty string with nan
  df.dropna(axis=0, how='all', inplace=True)
  # if the dynamic model also exists in AMS, use AMS parameters for overlap
  if (name in amsys.models.keys()) and amsys.models[name].n > 0:
@@ -684,15 +685,15 @@ def receive(self, adsys=None, routine=None, no_update=False):
  cond_ads_stg_u = (mname_ads in ['StaticGen', 'PV', 'Sclak']) and (pname_ads == 'u')
  if cond_ads_stg_u and (self.is_tds):
  # --- SynGen ---
- u_sg = sa.SynGen.get(idx=link['syg_idx'].replace(np.NaN, None).to_list(),
+ u_sg = sa.SynGen.get(idx=link['syg_idx'].replace(nan, None).to_list(),
  src='u', attr='v',
  allow_none=True, default=0,)
  # --- DG ---
- u_dg = sa.DG.get(idx=link['dg_idx'].replace(np.NaN, None).to_list(),
+ u_dg = sa.DG.get(idx=link['dg_idx'].replace(nan, None).to_list(),
  src='u', attr='v',
  allow_none=True, default=0,)
  # --- RenGen ---
- u_rg = sa.RenGen.get(idx=link['rg_idx'].replace(np.NaN, None).to_list(),
+ u_rg = sa.RenGen.get(idx=link['rg_idx'].replace(nan, None).to_list(),
  src='u', attr='v',
  allow_none=True, default=0,)
  # --- output ---
@@ -722,19 +723,19 @@ def receive(self, adsys=None, routine=None, no_update=False):
  cond_ads_stg_p = (mname_ads in ['StaticGen', 'PV', 'Sclak']) and (pname_ads == 'p')
  if cond_ads_stg_p and (self.is_tds):
  # --- SynGen ---
- p_sg = sa.SynGen.get(idx=link['syg_idx'].replace(np.NaN, None).to_list(),
+ p_sg = sa.SynGen.get(idx=link['syg_idx'].replace(nan, None).to_list(),
  src='Pe', attr='v',
  allow_none=True, default=0,)
  # --- DG ---
- Ie_dg = sa.DG.get(idx=link['dg_idx'].replace(np.NaN, None).to_list(),
+ Ie_dg = sa.DG.get(idx=link['dg_idx'].replace(nan, None).to_list(),
  src='Ipout_y', attr='v',
  allow_none=True, default=0,)
- v_dg = sa.DG.get(idx=link['dg_idx'].replace(np.NaN, None).to_list(),
+ v_dg = sa.DG.get(idx=link['dg_idx'].replace(nan, None).to_list(),
  src='v', attr='v',
  allow_none=True, default=0,)
  p_dg = Ie_dg * v_dg
  # --- RenGen ---
- p_rg = sa.RenGen.get(idx=link['rg_idx'].replace(np.NaN, None).to_list(),
+ p_rg = sa.RenGen.get(idx=link['rg_idx'].replace(nan, None).to_list(),
  src='Pe', attr='v',
  allow_none=True, default=0,)
  # --- output ---

ams/main.py

@@ -308,7 +308,7 @@ def run(filename, input_path='', verbose=20, mp_verbose=30,
  ncpu=NCPUS_PHYSICAL, pool=False,
  cli=False, shell=False, **kwargs):
  """
- Entry point to run ANDES routines.
+ Entry point to run AMS routines.
 
  Parameters
  ----------
@@ -511,7 +511,7 @@ def demo(**kwargs):
 
 def versioninfo():
  """
- Print version info for ANDES and dependencies.
+ Print version info for AMS and dependencies.
  """
 
  import numpy as np
@@ -563,7 +563,7 @@ def print_license():
 
 def edit_conf(edit_config: Optional[Union[str, bool]] = ''):
  """
- Edit the Andes config file which occurs first in the search path.
+ Edit the AMS config file which occurs first in the search path.
 
  Parameters
  ----------
@@ -647,7 +647,7 @@ def save_conf(config_path=None, overwrite=None, **kwargs):
 # TODO: list AMS output files here
 def remove_output(recursive=False):
  """
- Remove the outputs generated by Andes, including power flow reports
+ Remove the outputs generated by AMS, including power flow reports
  ``_out.txt``, time-domain list ``_out.lst`` and data ``_out.dat``,
  eigenvalue analysis report ``_eig.txt``.
 

ams/opt/omodel.py

@@ -412,8 +412,10 @@ def v(self):
 
  @v.setter
  def v(self, value):
- # FIXME: is this safe?
- self._v = value
+ if self.optz is None:
+ logger.info(f"Variable <{self.name}> is not initialized yet.")
+ else:
+ self.optz.value = value
 
  def get_idx(self):
  if self.is_group:
@@ -595,6 +597,10 @@ def v(self):
  else:
  return self.optz._expr.value
 
+ @v.setter
+ def v(self, value):
+ raise AttributeError("Cannot set the value of the constraint.")
+
 
 class Objective(OptzBase):
  """
@@ -634,7 +640,6 @@ def __init__(self,
  OptzBase.__init__(self, name=name, info=info, unit=unit)
  self.e_str = e_str
  self.sense = sense
- self._v = 0
  self.code = None
 
  @property
@@ -673,13 +678,12 @@ def v(self):
  """
  if self.optz is None:
  return None
- out = self.om.obj.value
- out = self._v if out is None else out
- return out
+ else:
+ return self.optz.value
 
  @v.setter
  def v(self, value):
- self._v = value
+ raise AttributeError("Cannot set the value of the objective function.")
 
  def parse(self, no_code=True):
  """

ams/pypower/core/pips.py

@@ -1,22 +1,24 @@
 """
 Python Interior Point Solver (PIPS).
 """
-import logging # NOQA
+import logging
 
-import numpy as np # NOQA
-from numpy import flatnonzero as find # NOQA
+import numpy as np
+from numpy import flatnonzero as find
 
-import scipy.sparse as sp # NOQA
-from scipy.sparse import csr_matrix as c_sparse # NOQA
+import scipy.sparse as sp
+from scipy.sparse import csr_matrix as c_sparse
 
-from andes.shared import deg2rad, rad2deg # NOQA
+from andes.shared import deg2rad, rad2deg
 
-from ams.pypower.eps import EPS # NOQA
-from ams.pypower.idx import IDX # NOQA
-from ams.pypower.utils import sub2ind # NOQA
-from ams.pypower.make import makeYbus # NOQA
+from ams.shared import inf
+
+from ams.pypower.eps import EPS
+from ams.pypower.idx import IDX
+from ams.pypower.utils import sub2ind
+from ams.pypower.make import makeYbus
 from ams.pypower.routines.opffcns import (opf_costfcn, opf_consfcn,
- opf_hessfcn,) # NOQA
+ opf_hessfcn,)
 
 
 logger = logging.getLogger(__name__)
@@ -205,13 +207,13 @@ def pips(f_fcn, x0=None, A=None, l=None, u=None, xmin=None, xmax=None,
 
  # default argument values
  if l is None or len(l) == 0:
- l = -np.Inf * np.ones(nA)
+ l = -inf * np.ones(nA)
  if u is None or len(u) == 0:
- u = np.Inf * np.ones(nA)
+ u = inf * np.ones(nA)
  if xmin is None or len(xmin) == 0:
- xmin = -np.Inf * np.ones(x0.shape[0])
+ xmin = -inf * np.ones(x0.shape[0])
  if xmax is None or len(xmax) == 0:
- xmax = np.Inf * np.ones(x0.shape[0])
+ xmax = inf * np.ones(x0.shape[0])
  if gh_fcn is None:
  nonlinear = False
  gn = np.array([])
@@ -343,15 +345,15 @@ def pips(f_fcn, x0=None, A=None, l=None, u=None, xmin=None, xmax=None,
 
  maxh = np.zeros(1) if len(h) == 0 else max(h)
 
- gnorm = np.linalg.norm(g, np.Inf) if len(g) else 0.0
- lam_norm = np.linalg.norm(lam, np.Inf) if len(lam) else 0.0
- mu_norm = np.linalg.norm(mu, np.Inf) if len(mu) else 0.0
- znorm = np.linalg.norm(z, np.Inf) if len(z) else 0.0
+ gnorm = np.linalg.norm(g, inf) if len(g) else 0.0
+ lam_norm = np.linalg.norm(lam, inf) if len(lam) else 0.0
+ mu_norm = np.linalg.norm(mu, inf) if len(mu) else 0.0
+ znorm = np.linalg.norm(z, inf) if len(z) else 0.0
  feascond = \
- max([gnorm, maxh]) / (1 + max([np.linalg.norm(x, np.Inf), znorm]))
+ max([gnorm, maxh]) / (1 + max([np.linalg.norm(x, inf), znorm]))
  gradcond = \
- np.linalg.norm(Lx, np.Inf) / (1 + max([lam_norm, mu_norm]))
- compcond = np.dot(z, mu) / (1 + np.linalg.norm(x, np.Inf))
+ np.linalg.norm(Lx, inf) / (1 + max([lam_norm, mu_norm]))
+ compcond = np.dot(z, mu) / (1 + np.linalg.norm(x, inf))
  costcond = np.abs(f - f0) / (1 + np.abs(f0))
 
  # save history
@@ -467,14 +469,14 @@ def pips(f_fcn, x0=None, A=None, l=None, u=None, xmin=None, xmax=None,
 
  maxh1 = np.zeros(1) if len(h1) == 0 else max(h1)
 
- g1norm = np.linalg.norm(g1, np.Inf) if len(g1) else 0.0
- lam1_norm = np.linalg.norm(lam, np.Inf) if len(lam) else 0.0
- mu1_norm = np.linalg.norm(mu, np.Inf) if len(mu) else 0.0
- z1norm = np.linalg.norm(z, np.Inf) if len(z) else 0.0
+ g1norm = np.linalg.norm(g1, inf) if len(g1) else 0.0
+ lam1_norm = np.linalg.norm(lam, inf) if len(lam) else 0.0
+ mu1_norm = np.linalg.norm(mu, inf) if len(mu) else 0.0
+ z1norm = np.linalg.norm(z, inf) if len(z) else 0.0
 
  feascond1 = max([g1norm, maxh1]) / \
- (1 + max([np.linalg.norm(x1, np.Inf), z1norm]))
- gradcond1 = np.linalg.norm(Lx1, np.Inf) / (1 + max([lam1_norm, mu1_norm]))
+ (1 + max([np.linalg.norm(x1, inf), z1norm]))
+ gradcond1 = np.linalg.norm(Lx1, inf) / (1 + max([lam1_norm, mu1_norm]))
 
  if (feascond1 > feascond) and (gradcond1 > gradcond):
  sc = True
@@ -560,15 +562,15 @@ def pips(f_fcn, x0=None, A=None, l=None, u=None, xmin=None, xmax=None,
  else:
  maxh = max(h)
 
- gnorm = np.linalg.norm(g, np.Inf) if len(g) else 0.0
- lam_norm = np.linalg.norm(lam, np.Inf) if len(lam) else 0.0
- mu_norm = np.linalg.norm(mu, np.Inf) if len(mu) else 0.0
- znorm = np.linalg.norm(z, np.Inf) if len(z) else 0.0
+ gnorm = np.linalg.norm(g, inf) if len(g) else 0.0
+ lam_norm = np.linalg.norm(lam, inf) if len(lam) else 0.0
+ mu_norm = np.linalg.norm(mu, inf) if len(mu) else 0.0
+ znorm = np.linalg.norm(z, inf) if len(z) else 0.0
  feascond = \
- max([gnorm, maxh]) / (1 + max([np.linalg.norm(x, np.Inf), znorm]))
+ max([gnorm, maxh]) / (1 + max([np.linalg.norm(x, inf), znorm]))
  gradcond = \
- np.linalg.norm(Lx, np.Inf) / (1 + max([lam_norm, mu_norm]))
- compcond = np.dot(z, mu) / (1 + np.linalg.norm(x, np.Inf))
+ np.linalg.norm(Lx, inf) / (1 + max([lam_norm, mu_norm]))
+ compcond = np.dot(z, mu) / (1 + np.linalg.norm(x, inf))
  costcond = float(np.abs(f - f0) / (1 + np.abs(f0)))
 
  hist.append({'feascond': feascond, 'gradcond': gradcond,
@@ -775,8 +777,8 @@ def pipsopf_solver(om, ppopt, out_opt=None):
 
  # try to select an interior initial point
  ll, uu = xmin.copy(), xmax.copy()
- ll[xmin == -np.Inf] = -1e10 # replace Inf with numerical proxies
- uu[xmax == np.Inf] = 1e10
+ ll[xmin == -inf] = -1e10 # replace Inf with numerical proxies
+ uu[xmax == inf] = 1e10
  x0 = (ll + uu) / 2
  Varefs = bus[bus[:, IDX.bus.BUS_TYPE] == IDX.bus.REF, IDX.bus.VA] * deg2rad
  # angles set to first reference angle

ams/pypower/core/ppoption.py

@@ -7,6 +7,8 @@
 
 import numpy as np
 
+from ams.shared import inf
+
 
 PF_OPTIONS = [
  ('pf_alg', 1, '''power flow algorithm:
@@ -184,7 +186,7 @@
 3 - concurrent (LP only)
 4 - deterministic concurrent (LP only)
 '''),
- ('grb_timelimit', np.Inf, 'maximum time allowed for solver (TimeLimit)'),
+ ('grb_timelimit', inf, 'maximum time allowed for solver (TimeLimit)'),
  ('grb_threads', 0, '(auto) maximum number of threads to use (Threads)'),
  ('grb_opt', 0, 'See gurobi_options() for details')
 ]