diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 76aa429b..31cc431c 100755
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -59,4 +59,4 @@ jobs:
run: |
rm src/pyfmi/__init__.py
cp -rv src/pyfmi/tests/files tests
- python3 -m nose --verbose tests/*
+ python3 -m nose --verbose tests/*.py
diff --git a/setup.py b/setup.py
index 99ece78b..cda00370 100644
--- a/setup.py
+++ b/setup.py
@@ -18,7 +18,7 @@
import distutils
import os
import shutil
-import numpy as N
+import numpy as np
import ctypes.util
import sys
@@ -244,9 +244,14 @@ def check_extensions():
compile_time_env=compile_time_env,
compiler_directives={'language_level' : "3str"})
+ # Test utilities
+ ext_list += cythonize([os.path.join("src", "pyfmi", "tests", "test_util.pyx")],
+ include_path = incl_path,
+ compiler_directives={'language_level' : "3str"})
+
for i in range(len(ext_list)):
- ext_list[i].include_dirs = [N.get_include(), "src", os.path.join("src", "pyfmi"), incdirs]
+ ext_list[i].include_dirs = [np.get_include(), "src", os.path.join("src", "pyfmi"), incdirs]
ext_list[i].library_dirs = [libdirs]
ext_list[i].language = "c"
ext_list[i].libraries = ["fmilib_shared"] if sys.platform.startswith("win") else ["fmilib"] #If windows shared, else static
diff --git a/src/common/__init__.py b/src/common/__init__.py
index f7078232..7d2d2e27 100644
--- a/src/common/__init__.py
+++ b/src/common/__init__.py
@@ -21,25 +21,17 @@
__all__ = ['algorithm_drivers', 'core', 'diagnostics', 'io', 'plotting']
-import sys
-python3_flag = True if sys.hexversion > 0x03000000 else False
## for backwards compatibility, to not break 'from pyfmi.common import diagnostics_prefix'
## TODO: Future: remove this
from .diagnostics import DIAGNOSTICS_PREFIX as diagnostics_prefix
-if python3_flag:
- def encode(x):
- if isinstance(x, str):
- return x.encode()
- else:
- return x
- def decode(x):
- if isinstance(x, bytes):
- return x.decode()
- else:
- return x
-else:
- def encode(x):
+def encode(x):
+ if isinstance(x, str):
+ return x.encode()
+ else:
return x
- def decode(x):
+def decode(x):
+ if isinstance(x, bytes):
+ return x.decode()
+ else:
return x
diff --git a/src/common/algorithm_drivers.py b/src/common/algorithm_drivers.py
index fc69c50e..209abc86 100644
--- a/src/common/algorithm_drivers.py
+++ b/src/common/algorithm_drivers.py
@@ -18,11 +18,11 @@
Module containing optimization, simulation and initialization algorithms.
"""
-import numpy as N
+import numpy as np
default_int = int
-int = N.int32
-N.int = N.int32
+int = np.int32
+np.int = np.int32
class AlgorithmBase(object):
"""
@@ -33,16 +33,20 @@ class AlgorithmBase(object):
# __metaclass__=ABCMeta
# @abstractmethod
- def __init__(self, model, alg_args): pass
+ def __init__(self, model, alg_args):
+ pass
# @abstractmethod
- def solve(self): pass
+ def solve(self):
+ pass
# @abstractmethod
- def get_result(self): pass
+ def get_result(self):
+ pass
@classmethod
- def get_default_options(self): pass
+ def get_default_options(self):
+ pass
class ResultBase(object):
"""
diff --git a/src/common/core.py b/src/common/core.py
index b391d56e..0cfb3f52 100644
--- a/src/common/core.py
+++ b/src/common/core.py
@@ -20,12 +20,12 @@
import zipfile
import tempfile
-import platform as PL
+import platform as plat
import os
import sys
import shutil
-import numpy as N
+import numpy as np
# location for temporary JModelica files
def get_temp_location():
@@ -261,7 +261,7 @@ def get_platform_dir():
else:
platform = 'linux'
- if PL.architecture()[0].startswith('32'):
+ if plat.architecture()[0].startswith('32'):
platform += '32'
else:
platform += '64'
@@ -490,20 +490,20 @@ def __init__(self, abscissa, ordinate, tol=1e-8):
"""
self._abscissa = abscissa.astype('float')
self._ordinate = ordinate
- self._n = N.size(abscissa)
- self._n_ordinate = N.size(self.ordinate,1)
+ self._n = np.size(abscissa)
+ self._n_ordinate = np.size(self.ordinate,1)
self._x0 = abscissa[0]
self._xf = abscissa[-1]
- if not N.all(N.diff(self.abscissa) >= 0):
+ if not np.all(np.diff(self.abscissa) >= 0):
raise Exception("The abscissae must be increasing.")
- [double_point_indices] = N.nonzero(N.abs(N.diff(self.abscissa)) <= tol)
+ [double_point_indices] = np.nonzero(np.abs(np.diff(self.abscissa)) <= tol)
while (len(double_point_indices) > 0):
for i in double_point_indices:
self.abscissa[i+1] = self.abscissa[i+1] + tol
- [double_point_indices] = N.nonzero(
- N.abs(N.diff(self.abscissa)) <= tol)
+ [double_point_indices] = np.nonzero(
+ np.abs(np.diff(self.abscissa)) <= tol)
def eval(self,x):
"""
@@ -561,9 +561,9 @@ def eval(self,x):
Two dimensional n x m matrix containing the ordinate values
corresponding to the argument x.
"""
- y = N.zeros([N.size(x),self._n_ordinate])
+ y = np.zeros([np.size(x),self._n_ordinate])
for i in range(self._n_ordinate):
- y[:,i] = N.interp(x,self.abscissa,self.ordinate[:,i])
+ y[:,i] = np.interp(x,self.abscissa,self.ordinate[:,i])
return y
class TrajectoryLinearInterpolationExtrapolation(Trajectory):
@@ -590,11 +590,11 @@ def eval(self, x):
See http://stackoverflow.com/questions/2745329/how-to-make-scipy-interpolate-give-a-an-extrapolated-result-beyond-the-input-ran
"""
- y = N.zeros([N.size(x),N.size(self.ordinate,1)])
- for i in range(N.size(y,1)):
- y[:,i] = N.interp(x,self.abscissa,self.ordinate[:,i])
- y[:,i] = N.where(x < self.abscissa[0], self.ordinate[0,i]+(x-self.abscissa[0])*(self.ordinate[0,i]-self.ordinate[1,i])/(self.abscissa[0]-self.abscissa[1]), y[:,i])
- y[:,i] = N.where(x > self.abscissa[-1], self.ordinate[-1,i]+(x-self.abscissa[-1])*(self.ordinate[-1,i]-self.ordinate[-2,i])/(self.abscissa[-1]-self.abscissa[-2]), y[:,i])
+ y = np.zeros([np.size(x),np.size(self.ordinate,1)])
+ for i in range(np.size(y,1)):
+ y[:,i] = np.interp(x,self.abscissa,self.ordinate[:,i])
+ y[:,i] = np.where(x < self.abscissa[0], self.ordinate[0,i]+(x-self.abscissa[0])*(self.ordinate[0,i]-self.ordinate[1,i])/(self.abscissa[0]-self.abscissa[1]), y[:,i])
+ y[:,i] = np.where(x > self.abscissa[-1], self.ordinate[-1,i]+(x-self.abscissa[-1])*(self.ordinate[-1,i]-self.ordinate[-2,i])/(self.abscissa[-1]-self.abscissa[-2]), y[:,i])
return y
class TrajectoryConstantInterpolationExtrapolation(Trajectory):
@@ -634,27 +634,27 @@ def eval(self, x):
See http://stackoverflow.com/questions/2745329/how-to-make-scipy-interpolate-give-a-an-extrapolated-result-beyond-the-input-ran
"""
- y = N.zeros([N.size(x),N.size(self.ordinate,1)])
- x = N.array([x]).flatten()
+ y = np.zeros([np.size(x),np.size(self.ordinate,1)])
+ x = np.array([x]).flatten()
if self._mode == 1:
- for i in range(N.size(y,1)):
- for j in range(N.size(x)):
+ for i in range(np.size(y,1)):
+ for j in range(np.size(x)):
try:
y[j,i] = self.ordinate[self.abscissa<=x[j],i][-1]
except IndexError:
pass
- y[:,i] = N.where(x < self.abscissa[0], self.ordinate[0,i], y[:,i])
- y[:,i] = N.where(x > self.abscissa[-1], self.ordinate[-1,i], y[:,i])
+ y[:,i] = np.where(x < self.abscissa[0], self.ordinate[0,i], y[:,i])
+ y[:,i] = np.where(x > self.abscissa[-1], self.ordinate[-1,i], y[:,i])
else:
- for i in range(N.size(y,1)):
- for j in range(N.size(x)):
+ for i in range(np.size(y,1)):
+ for j in range(np.size(x)):
try:
y[j,i] = self.ordinate[self.abscissa>=x[j],i][0]
except IndexError:
pass
- y[:,i] = N.where(x < self.abscissa[0], self.ordinate[0,i], y[:,i])
- y[:,i] = N.where(x > self.abscissa[-1], self.ordinate[-1,i], y[:,i])
+ y[:,i] = np.where(x < self.abscissa[0], self.ordinate[0,i], y[:,i])
+ y[:,i] = np.where(x > self.abscissa[-1], self.ordinate[-1,i], y[:,i])
return y
class TrajectoryUserFunction(Trajectory):
@@ -686,9 +686,9 @@ def eval(self, x):
corresponding to the argument x.
"""
try:
- y = N.array(N.matrix(self.traj(float(x))))
+ y = np.array(np.matrix(self.traj(float(x))))
except TypeError:
- y = N.array(N.matrix(self.traj(x)).transpose())
+ y = np.array(np.matrix(self.traj(x)).transpose())
#In order to guarantee that the
#return values are on the correct
#form. May need to be evaluated
diff --git a/src/common/io.py b/src/common/io.py
index 736f786f..2f3b4c8a 100644
--- a/src/common/io.py
+++ b/src/common/io.py
@@ -24,11 +24,8 @@
import os
from functools import reduce
-import numpy as N
import numpy as np
import scipy
-import scipy.io
-from scipy import interpolate
scipy_minmaj = tuple(map(int, scipy.__version__.split('.')[:2]))
if scipy_minmaj >= (1, 8):
# due to a DeprecationWarning, we do below, this will likely need another change in a future update of scipy.
@@ -38,7 +35,7 @@
import pyfmi.fmi as fmi
import pyfmi.fmi_util as fmi_util
-from pyfmi.common import python3_flag, encode, decode
+from pyfmi.common import encode, decode
from pyfmi.common.diagnostics import DIAGNOSTICS_PREFIX, DiagnosticsBase
SYS_LITTLE_ENDIAN = sys.byteorder == 'little'
@@ -160,7 +157,7 @@ def get_variable_index(self,name):
name = name.replace(" ", "")
try:
- if python3_flag and isinstance(self, ResultDymolaBinary):
+ if isinstance(self, ResultDymolaBinary):
return self.name_lookup[encode(name)]
else:
return self.name_lookup[name]
@@ -171,7 +168,7 @@ def get_variable_index(self,name):
if self._check_if_derivative_variable(name):
try:
#First do a simple search for the other naming convention
- if python3_flag and isinstance(self, ResultDymolaBinary):
+ if isinstance(self, ResultDymolaBinary):
return self.name_lookup[encode(self._convert_dx_name(name))]
else:
return self.name_lookup[self._convert_dx_name(name)]
@@ -202,7 +199,7 @@ def _exhaustive_search_for_derivatives(self, name):
state = self._find_underlying_state(name)
index = self.get_variable_index(state)
- alias_index = N.where(self.dataInfo[:,1]==self.dataInfo[index,1])[0]
+ alias_index = np.where(self.dataInfo[:,1]==self.dataInfo[index,1])[0]
#Loop through all alias
for ind in alias_index:
@@ -210,19 +207,19 @@ def _exhaustive_search_for_derivatives(self, name):
trial_name = list(self.name_lookup.keys())[ind]
#Create the derivative name
- if python3_flag and isinstance(self, ResultDymolaBinary):
+ if isinstance(self, ResultDymolaBinary):
der_trial_name = self._create_derivative_from_state(decode(trial_name))
else:
der_trial_name = self._create_derivative_from_state(trial_name)
try:
- if python3_flag and isinstance(self, ResultDymolaBinary):
+ if isinstance(self, ResultDymolaBinary):
return self.name_lookup[encode(der_trial_name)]
else:
return self.name_lookup[der_trial_name]
except KeyError:
try:
- if python3_flag and isinstance(self, ResultDymolaBinary):
+ if isinstance(self, ResultDymolaBinary):
return self.name_lookup[encode(self._convert_dx_name(der_trial_name))]
else:
return self.name_lookup[self._convert_dx_name(der_trial_name)]
@@ -328,7 +325,7 @@ def __init__(self, filename, delimiter=";"):
data.append([float(d) for d in row])
- self.data = N.array(data)
+ self.data = np.array(data)
def get_variable_data(self,name):
"""
@@ -606,9 +603,9 @@ def write_header(self, file_name='', parameters=None):
f.write('int dataInfo(%d,%d)\n' % (num_vars+len(names_sens) + 1, 4))
f.write('0 1 0 -1 # time\n')
- list_of_continuous_states = N.append(self.model._save_real_variables_val,
+ list_of_continuous_states = np.append(self.model._save_real_variables_val,
self.model._save_int_variables_val)
- list_of_continuous_states = N.append(list_of_continuous_states,
+ list_of_continuous_states = np.append(list_of_continuous_states,
self.model._save_bool_variables_val).tolist()
list_of_continuous_states = dict(zip(list_of_continuous_states,
range(len(list_of_continuous_states))))
@@ -714,7 +711,7 @@ def write_point(self, data=None, parameter_data=[]):
if data is None:
#Retrieves the time-point
[r,i,b] = self.model.save_time_point()
- data = N.append(N.append(N.append(self.model.time,r),i),b)
+ data = np.append(np.append(np.append(self.model.time,r),i),b)
#Write the point
str_text = (" %.14E" % data[0])
@@ -752,7 +749,6 @@ def write_finalize(self):
self._file_open = False
-
class ResultStorageMemory(ResultDymola):
"""
Class representing a simulation result that is kept in MEMORY.
@@ -809,7 +805,7 @@ def get_variable_data(self,name):
factor = -1 if var.alias == fmi.FMI_NEGATED_ALIAS else 1
if var.variability == fmi.FMI_CONSTANT or var.variability == fmi.FMI_PARAMETER:
- return Trajectory([self.time[0],self.time[-1]],N.array([self.model.get(name),self.model.get(name)]).ravel())
+ return Trajectory([self.time[0],self.time[-1]],np.array([self.model.get(name),self.model.get(name)]).ravel())
else:
return Trajectory(self.time,factor*self.data[var.value_reference])
@@ -905,38 +901,24 @@ def __init__(self,fname):
fid = fname
fid.seek(0,0) # Needs to start from beginning of file
- result = []
-
# Read Aclass section
nLines = self._find_phrase(fid, 'char Aclass')
nLines = int(nLines[0])
- Aclass = [fid.readline().strip() for i in range(nLines)]
- #Aclass = []
- #for i in range(0,nLines):
- # Aclass.append(fid.readline().strip())
- self.Aclass = Aclass
+ self.Aclass = [fid.readline().strip() for i in range(nLines)]
# Read name section
nLines = self._find_phrase(fid, 'char name')
nLines = int(nLines[0])
- name = [fid.readline().strip().replace(" ","") for i in range(nLines)]
- #name = []
- #for i in range(0,nLines):
- # name.append(fid.readline().strip().replace(" ",""))
- self._name = name
+ self._name = [fid.readline().strip().replace(" ","") for i in range(nLines)]
self.name_lookup = {key:ind for ind,key in enumerate(self._name)}
# Read description section
nLines = self._find_phrase(fid, 'char description')
nLines = int(nLines[0])
- description = [fid.readline().strip() for i in range(nLines)]
- #description = []
- #for i in range(0,nLines):
- # description.append(fid.readline().strip())
- self.description = description
+ self.description = [fid.readline().strip() for i in range(nLines)]
# Read dataInfo section
nLines = self._find_phrase(fid, 'int dataInfo')
@@ -945,26 +927,22 @@ def __init__(self,fname):
nLines = int(nLines[0])
nCols = int(nCols[0])
- if python3_flag:
- dataInfo = [list(map(int,fid.readline().split()[0:nCols])) for i in range(nLines)]
- else:
- dataInfo = [map(int,fid.readline().split()[0:nCols]) for i in range(nLines)]
- self.dataInfo = N.array(dataInfo)
+ self.dataInfo = np.array([list(map(int,fid.readline().split()[0:nCols])) for i in range(nLines)])
# Find out how many data matrices there are
- if len(name) == 1: #Only time
+ if len(self._name) == 1: #Only time
nData = 2
else:
nData = max(self.dataInfo[:,0])
self.data = []
for i in range(0,nData):
- l = fid.readline()
- tmp = l.partition(' ')
- while tmp[0]!='float' and tmp[0]!='double' and l!='':
- l = fid.readline()
- tmp = l. partition(' ')
- if l=='':
+ line = fid.readline()
+ tmp = line.partition(' ')
+ while tmp[0]!='float' and tmp[0]!='double' and line!='':
+ line = fid.readline()
+ tmp = line.partition(' ')
+ if line=='':
raise JIOError('The result does not seem to be of a supported format.')
tmp = tmp[2].partition('(')
nLines = tmp[2].partition(',')
@@ -974,34 +952,28 @@ def __init__(self,fname):
data = []
for i in range(0,nLines):
info = []
- while len(info) < nCols and l != '':
- l = fid.readline()
- info.extend(l.split())
+ while len(info) < nCols and line != '':
+ line = fid.readline()
+ info.extend(line.split())
try:
- if python3_flag:
- data.append(list(map(float,info[0:nCols])))
- else:
- data.append(map(float,info[0:nCols]))
+ data.append(list(map(float,info[0:nCols])))
except ValueError: #Handle 1.#INF's and such
- if python3_flag:
- data.append(list(map(robust_float,info[0:nCols])))
- else:
- data.append(map(robust_float,info[0:nCols]))
+ data.append(list(map(robust_float,info[0:nCols])))
if len(info) == 0 and i < nLines-1:
raise JIOError("Inconsistent number of lines in the result data.")
del(info)
- self.data.append(N.array(data))
+ self.data.append(np.array(data))
if len(self.data) == 0:
raise JIOError('Could not find any variable data in the result file.')
def _find_phrase(self,fid, phrase):
- l = fid.readline()
- tmp = l.partition('(')
- while tmp[0]!=phrase and l!='':
- l = fid.readline()
- tmp = l. partition('(')
- if l=='':
+ line = fid.readline()
+ tmp = line.partition('(')
+ while tmp[0]!=phrase and line!='':
+ line = fid.readline()
+ tmp = line.partition('(')
+ if line=='':
raise JIOError("The result does not seem to be of a supported format.")
return tmp[2].partition(',')
@@ -1136,7 +1108,7 @@ def shift_time(self,time_shift):
The time shift offset.
"""
for i in range(len(self.data)):
- for j in range(N.shape(self.data[i])[0]):
+ for j in range(np.shape(self.data[i])[0]):
self.data[i][j,0] = self.data[i][j,0] + time_shift
def append(self, res):
@@ -1149,9 +1121,9 @@ def append(self, res):
res --
A simulation result object of type DymolaResultTextual.
"""
- n_points = N.size(res.data[1],0)
+ n_points = np.size(res.data[1],0)
time_shift = self.data[1][-1,0]
- self.data[1] = N.vstack((self.data[1],res.data[1]))
+ self.data[1] = np.vstack((self.data[1],res.data[1]))
self.data[1][n_points:,0] = self.data[1][n_points:,0] + time_shift
#Overriding SCIPYs default reader for MATLAB v4 format
@@ -1349,7 +1321,7 @@ def _get_name_dict(self):
dict_names = list(name_dict.keys())
name_dict[DiagnosticsBase.calculated_diagnostics['nbr_steps']['name']] = None
for name in dict_names:
- if python3_flag and isinstance(name, bytes):
+ if isinstance(name, bytes):
name = decode(name)
if name == f'{DIAGNOSTICS_PREFIX}event_data.event_info.event_type':
name_dict[DiagnosticsBase.calculated_diagnostics['nbr_time_events']['name']] = None
@@ -1430,7 +1402,7 @@ def _get_interpolated_trajectory(self, data_index):
time_vector = self._read_trajectory_data(0, False)
data = self._read_trajectory_data(data_index, False)
- f = interpolate.interp1d(time_vector, data, fill_value="extrapolate")
+ f = scipy.interpolate.interp1d(time_vector, data, fill_value="extrapolate")
self._data_2[data_index] = f(diag_time_vector)
@@ -1440,7 +1412,7 @@ def _get_interpolated_trajectory(self, data_index):
def _get_description(self):
if not self._description:
description = scipy.io.loadmat(self._fname,chars_as_strings=False, variable_names=["description"])["description"]
- self._description = ["".join(description[:,i]).rstrip() for i in range(description[0,:].size)]
+ self._description = ["".join(description[:,i]).rstrip() for i in range(np.size(description[0,:]))]
return self._description
@@ -1463,7 +1435,7 @@ def get_variable_data(self, name):
A Trajectory object containing the time vector and the data vector
of the variable.
"""
- if python3_flag and isinstance(name, bytes):
+ if isinstance(name, bytes):
name = decode(name)
if name == 'time' or name== 'Time':
@@ -1476,7 +1448,7 @@ def get_variable_data(self, name):
elif '{}.'.format(DiagnosticsBase.calculated_diagnostics['nbr_state_limits_step']['name']) in name:
return Trajectory(self._get_diagnostics_trajectory(0), self._calculate_nbr_state_limits_step(name))
elif name == f'{DIAGNOSTICS_PREFIX}cpu_time':
- return Trajectory(self._get_diagnostics_trajectory(0), N.cumsum(self.get_variable_data(f'{DIAGNOSTICS_PREFIX}cpu_time_per_step').x))
+ return Trajectory(self._get_diagnostics_trajectory(0), np.cumsum(self.get_variable_data(f'{DIAGNOSTICS_PREFIX}cpu_time_per_step').x))
else:
varInd = self.get_variable_index(name)
@@ -1515,12 +1487,12 @@ def _calculate_events_and_steps(self, name):
event_type_data = self.get_variable_data(f'{DIAGNOSTICS_PREFIX}event_data.event_info.event_type')
except Exception:
if name == steps_name:
- self._data_3[steps_name] = N.array(range(len(self._get_diagnostics_trajectory(0))))
+ self._data_3[steps_name] = np.array(range(len(self._get_diagnostics_trajectory(0))))
return self._data_3[name]
- self._data_3[all_events_name] = N.zeros(len(event_type_data.x))
- self._data_3[time_events_name] = N.zeros(len(event_type_data.x))
- self._data_3[state_events_name] = N.zeros(len(event_type_data.x))
- self._data_3[steps_name] = N.zeros(len(event_type_data.x))
+ self._data_3[all_events_name] = np.zeros(len(event_type_data.x))
+ self._data_3[time_events_name] = np.zeros(len(event_type_data.x))
+ self._data_3[state_events_name] = np.zeros(len(event_type_data.x))
+ self._data_3[steps_name] = np.zeros(len(event_type_data.x))
nof_events = 0
nof_time_events = 0
nof_state_events = 0
@@ -1547,7 +1519,7 @@ def _calculate_nbr_state_limits_step(self, name):
state_name = name.replace(step_limitation_name, '')
state_error_data = self.get_variable_data(f'{DIAGNOSTICS_PREFIX}state_errors.'+state_name)
event_type_data = self.get_variable_data(f'{DIAGNOSTICS_PREFIX}event_data.event_info.event_type')
- self._data_3[name] = N.zeros(len(event_type_data.x))
+ self._data_3[name] = np.zeros(len(event_type_data.x))
nof_times_state_limits_step = 0
for ind, state_error in enumerate(state_error_data.x):
if event_type_data.x[ind] == -1 and state_error >= 1.0:
@@ -1697,7 +1669,7 @@ def integration_point(self, solver = None):
#Sets the parameters, if any
if solver and self.options["sensitivities"]:
- self.param_sol += [N.array(solver.interpolate_sensitivity(model.time, 0)).flatten()]
+ self.param_sol += [np.array(solver.interpolate_sensitivity(model.time, 0)).flatten()]
def simulation_end(self):
"""
@@ -1712,16 +1684,16 @@ def get_result(self):
result of an instance of ResultBase or of an instance of a
subclass of ResultBase.
"""
- t = N.array(self.time_sol)
- r = N.array(self.real_sol)
- data = N.c_[t,r]
+ t = np.array(self.time_sol)
+ r = np.array(self.real_sol)
+ data = np.c_[t,r]
if len(self.int_sol) > 0 and len(self.int_sol[0]) > 0:
- i = N.array(self.int_sol)
- data = N.c_[data,i]
+ i = np.array(self.int_sol)
+ data = np.c_[data,i]
if len(self.bool_sol) > 0 and len(self.bool_sol[0]) > 0:
- b = N.array(self.bool_sol)
- data = N.c_[data,b]
+ b = np.array(self.bool_sol)
+ data = np.c_[data,b]
return ResultStorageMemory(self.model, data, [self.real_var_ref,self.int_var_ref,self.bool_var_ref], self.vars)
@@ -1849,18 +1821,18 @@ def simulation_start(self):
for i,val in enumerate(const_val_bool):
const_str += "%.14E"%(const_alias_bool[i]*val)+delimiter
- #for val in N.append(const_val_real,N.append(const_val_int,const_val_boolean)):
+ #for val in np.append(const_val_real,np.append(const_val_int,const_val_boolean)):
# const_str += "%.14E"%val+delimiter
self.const_str = const_str
self._file = f
self.cont_valref_real = cont_valref_real
- self.cont_alias_real = N.array(cont_alias_real)
+ self.cont_alias_real = np.array(cont_alias_real)
self.cont_valref_int = cont_valref_int
- self.cont_alias_int = N.array(cont_alias_int)
+ self.cont_alias_int = np.array(cont_alias_int)
self.cont_valref_bool = cont_valref_bool
- self.cont_alias_bool = N.array(cont_alias_bool)
+ self.cont_alias_bool = np.array(cont_alias_bool)
def integration_point(self, solver = None):
"""
@@ -1886,7 +1858,7 @@ def integration_point(self, solver = None):
i = model.get_integer(self.cont_valref_int)*self.cont_alias_int
b = model.get_boolean(self.cont_valref_bool)*self.cont_alias_bool
- data = N.append(N.append(r,i),b)
+ data = np.append(np.append(r,i),b)
cont_str = ""
for val in data:
@@ -2078,10 +2050,7 @@ def simulation_start(self):
if isinstance(self.model, fmi.FMUModelME2):
vars = self.model.get_model_variables(type=fmi.FMI2_REAL,include_alias=False,variability=fmi.FMI2_CONTINUOUS,filter=self.options["filter"])
- if python3_flag:
- state_vars = [v.value_reference for i,v in self.model.get_states_list().items()]
- else:
- state_vars = [v.value_reference for i,v in self.model.get_states_list().iteritems()]
+ state_vars = [v.value_reference for i,v in self.model.get_states_list().items()]
else:
vars = self.model.get_model_variables(type=fmi.FMI_REAL,include_alias=False,variability=fmi.FMI_CONTINUOUS,filter=self.options["filter"])
state_vars = self.model.get_state_value_references()
@@ -2289,10 +2258,10 @@ def simulation_start(self):
#f.write('%s,%d)\n' % (' '*14, self._nvariables))
self._file = f
- self._data_order = N.array(valueref_of_continuous_states)
- self.real_var_ref = N.array(self.real_var_ref)
- self.int_var_ref = N.array(self.int_var_ref)
- self.bool_var_ref = N.array(self.bool_var_ref)
+ self._data_order = np.array(valueref_of_continuous_states)
+ self.real_var_ref = np.array(self.real_var_ref)
+ self.int_var_ref = np.array(self.int_var_ref)
+ self.bool_var_ref = np.array(self.bool_var_ref)
def integration_point(self, solver = None):#parameter_data=[]):
"""
@@ -2317,14 +2286,14 @@ def integration_point(self, solver = None):#parameter_data=[]):
i = model.get_integer(self.int_var_ref)
b = model.get_boolean(self.bool_var_ref)
- data = N.append(N.append(r,i),b)
+ data = np.append(np.append(r,i),b)
#Write the point
str_text = (" %.14E" % self.model.time) + ''.join([" %.14E" % (data[data_order[j]]) for j in range(self._nvariables-1)])
#Sets the parameters, if any
if solver and self.options["sensitivities"]:
- parameter_data = N.array(solver.interpolate_sensitivity(model.time, 0)).flatten()
+ parameter_data = np.array(solver.interpolate_sensitivity(model.time, 0)).flatten()
for j in range(len(parameter_data)):
str_text = str_text + (" %.14E" % (parameter_data[j]))
@@ -2427,11 +2396,11 @@ def robust_float(value):
return float(value)
except ValueError:
if value.startswith("1.#INF"):
- return float(N.inf)
+ return float(np.inf)
elif value.startswith("-1.#INF"):
- return float(-N.inf)
+ return float(-np.inf)
elif value.startswith("1.#QNAN") or value.startswith("-1.#IND"):
- return float(N.nan)
+ return float(np.nan)
else:
raise ValueError
@@ -2639,7 +2608,7 @@ def simulation_start(self, diagnostics_params={}, diagnostics_vars={}):
self.dump_data_internal = fmi_util.DumpData(self.model, self._file, self.real_var_ref, self.int_var_ref, self.bool_var_ref, self._with_diagnostics)
if self._with_diagnostics:
- diag_data = N.array([val[0] for val in diagnostics_vars.values()], dtype=float)
+ diag_data = np.array([val[0] for val in diagnostics_vars.values()], dtype=float)
self.diagnostics_point(diag_data)
def integration_point(self, solver = None):
diff --git a/src/common/log/parser.py b/src/common/log/parser.py
index b2a8627e..47ca85b9 100644
--- a/src/common/log/parser.py
+++ b/src/common/log/parser.py
@@ -20,11 +20,9 @@
from xml import sax
import re
-import os
import numpy as np
from distutils.util import strtobool
-from pyfmi.common.log.tree import *
-from pyfmi.fmi_util import python3_flag
+from pyfmi.common.log.tree import Node, Comment
from pyfmi.fmi import FMUException
## Leaf parser ##
@@ -59,8 +57,7 @@ def parse_value(text):
text = text[1:-1].replace('""','"')
else:
assert '"' not in text
- # for python 2 we need to avoid printing all strings as u'...'
- return text if python3_flag else text.encode('ascii', 'xmlcharrefreplace')
+ return text
def parse_vector(text):
@@ -206,7 +203,7 @@ def extract_xml_log(dest, log, modulename = 'Model'):
dest --
Name of the file which holds the extracted log, or a stream to write to
- that supports the function 'write'. Default behaviour is to write to a file.
+ that supports the function 'write'. Default behavior is to write to a file.
Default: get_log_filename() + xml
log --
String of filename to extract log from or a stream. The support for stream
diff --git a/src/common/log/prettyprinter.py b/src/common/log/prettyprinter.py
index ac463772..a42d2133 100644
--- a/src/common/log/prettyprinter.py
+++ b/src/common/log/prettyprinter.py
@@ -19,7 +19,7 @@
"""
from numpy import ndarray
-from pyfmi.common.log.tree import *
+from pyfmi.common.log.tree import Node, Comment
def prettyprint(write, node):
"""Prettyprint a log node to the write callback write."""
diff --git a/src/common/log/tree.py b/src/common/log/tree.py
index 1dc85a5e..043b4e4a 100644
--- a/src/common/log/tree.py
+++ b/src/common/log/tree.py
@@ -19,7 +19,6 @@
Each node is represented as a Node, Comment, or leaf (other types)
"""
-from pyfmi.fmi_util import python3_flag
class Comment(object):
"""Log comment node.
@@ -89,7 +88,7 @@ def find(self, types):
types may be a string or list of strings.
"""
- if isinstance(types, str if python3_flag else basestring):
+ if isinstance(types, str):
types = [types]
nodes = []
diff --git a/src/common/plotting/plot_gui.py b/src/common/plotting/plot_gui.py
index 5064fd28..7c3cf89e 100644
--- a/src/common/plotting/plot_gui.py
+++ b/src/common/plotting/plot_gui.py
@@ -25,6 +25,7 @@
from matplotlib import rcParams
import fnmatch
import re
+import os
#GUI modules
try:
@@ -49,8 +50,6 @@
except ImportError:
print("JModelica Python package was not found.")
-#Import general modules
-import os as O
ID_GRID = 15001
ID_LICENSE = 15002
@@ -290,7 +289,7 @@ def OnMenuOpen(self, event):
#If OK load the results
if dlg.ShowModal() == wx.ID_OK:
for n in dlg.GetFilenames():
- self._OpenFile(O.path.join(dlg.GetDirectory(),n))
+ self._OpenFile(os.path.join(dlg.GetDirectory(),n))
dlg.Destroy() #Destroy the popup window
diff --git a/src/pyfmi/__init__.py b/src/pyfmi/__init__.py
index 05b87784..49d628c6 100644
--- a/src/pyfmi/__init__.py
+++ b/src/pyfmi/__init__.py
@@ -26,13 +26,13 @@
from pyfmi.fmi_coupled import CoupledFMUModelME2
from pyfmi.master import Master
from pyfmi.fmi_extended import FMUModelME1Extended
-import numpy as N
+import numpy as np
import os.path
import sys
import time
-int = N.int32
-N.int = N.int32
+int = np.int32
+np.int = np.int32
def testattr(**kwargs):
"""Add attributes to a test function/method/class.
diff --git a/src/pyfmi/debug.py b/src/pyfmi/debug.py
index c742c5f2..3e1b8837 100644
--- a/src/pyfmi/debug.py
+++ b/src/pyfmi/debug.py
@@ -19,8 +19,8 @@
This file contains methods for helping with debugging a simulation.
"""
-import numpy as N
-import scipy as S
+import numpy as np
+import pylab as pl
class DebugInformation:
@@ -49,7 +49,7 @@ def _load_data(self):
if len(row_data) > 2:
event_indicators = row_data[2].strip().replace("\n","")
event_indicators = event_indicators.split(" ")
- self.event_indicators.append(N.array([abs(float(i)) for i in event_indicators]))
+ self.event_indicators.append(np.array([abs(float(i)) for i in event_indicators]))
row_data = file.readline()
elif row_data.startswith("Solver"):
self.solver = row_data.split(" ")[-1]
@@ -61,80 +61,71 @@ def _load_data(self):
break
def plot_time_distribution(self, normalized=False):
- import pylab as P
if normalized:
- total_time = N.sum(self.real_time)
- P.plot(self.simulated_time,self.real_time/total_time)
- P.ylabel("Real Time (normalized)")
+ total_time = np.sum(self.real_time)
+ pl.plot(self.simulated_time,self.real_time/total_time)
+ pl.ylabel("Real Time (normalized)")
else:
- P.plot(self.simulated_time,self.real_time)
- P.ylabel("Real Time [s]")
- P.xlabel("Time [s]")
+ pl.plot(self.simulated_time,self.real_time)
+ pl.ylabel("Real Time [s]")
+ pl.xlabel("Time [s]")
self._plot_events()
- P.legend(("Time","Events"))
+ pl.legend(("Time","Events"))
- P.grid()
- P.show()
+ pl.grid()
+ pl.show()
def plot_cumulative_time_elapsed(self, log_scale=False):
- import pylab as P
-
- cumulative_sum = N.cumsum(self.real_time)
+ cumulative_sum = np.cumsum(self.real_time)
if log_scale:
- P.semilogy(self.simulated_time, cumulative_sum)
+ pl.semilogy(self.simulated_time, cumulative_sum)
else:
- P.plot(self.simulated_time, cumulative_sum)
- P.xlabel("Time [s]")
- P.ylabel("Real Time [s]")
+ pl.plot(self.simulated_time, cumulative_sum)
+ pl.xlabel("Time [s]")
+ pl.ylabel("Real Time [s]")
self._plot_events()
- P.legend(("Time","Events"))
+ pl.legend(("Time","Events"))
- P.grid()
- P.show()
+ pl.grid()
+ pl.show()
def plot_step_size(self):
- import pylab as P
-
- P.semilogy(self.simulated_time,N.diff([0.0]+self.simulated_time),drawstyle="steps-pre")
- P.ylabel("Step-size")
- P.xlabel("Time [s]")
- P.title("Step-size history")
- P.grid()
- P.show()
+ pl.semilogy(self.simulated_time,np.diff([0.0]+self.simulated_time),drawstyle="steps-pre")
+ pl.ylabel("Step-size")
+ pl.xlabel("Time [s]")
+ pl.title("Step-size history")
+ pl.grid()
+ pl.show()
def _plot_events(self):
- import pylab as P
-
for ev in self.events:
- P.axvline(x=ev,color='r')
+ pl.axvline(x=ev,color='r')
def plot_event_indicators(self, mask=None, region=None):
- import pylab as P
-
- ev_ind = N.array(self.event_indicators)
- time = N.array(self.simulated_time)
- ev_ind_name = N.array(["event_ind_%d"%i for i in range(len(ev_ind[0,:]))])
+ ev_ind = np.array(self.event_indicators)
+ time = np.array(self.simulated_time)
+ ev_ind_name = np.array(["event_ind_%d"%i for i in range(len(ev_ind[0,:]))])
if region:
lw = time > region[0]
up = time < region[1]
- time = time[N.logical_and(lw,up)]
- ev_ind = ev_ind[N.logical_and(lw,up), :]
+ time = time[np.logical_and(lw,up)]
+ ev_ind = ev_ind[np.logical_and(lw,up), :]
if mask:
- P.plot(time, ev_ind[:,mask])
- P.legend(ev_ind_name[mask])
+ pl.plot(time, ev_ind[:,mask])
+ pl.legend(ev_ind_name[mask])
else:
- P.plot(time, ev_ind)
- P.legend(ev_ind_name)
- P.grid()
- P.xlabel("Time [s]")
- P.title("Event Indicators")
- P.show()
+ pl.plot(time, ev_ind)
+ pl.legend(ev_ind_name)
+ pl.grid()
+ pl.xlabel("Time [s]")
+ pl.title("Event Indicators")
+ pl.show()
class ImplicitEulerDebugInformation(DebugInformation):
pass
@@ -166,11 +157,11 @@ def _load_data(self):
self.order.append(int(row_data[2].strip()))
error_data = row_data[3].strip().replace("\n","")
error_data = error_data.split(" ")
- self.weighted_error.append(N.array([abs(float(i)) for i in error_data]))
+ self.weighted_error.append(np.array([abs(float(i)) for i in error_data]))
if len(row_data) > 4:
event_indicators = row_data[4].strip().replace("\n","")
event_indicators = event_indicators.split(" ")
- self.event_indicators.append(N.array([abs(float(i)) for i in event_indicators]))
+ self.event_indicators.append(np.array([abs(float(i)) for i in event_indicators]))
row_data = file.readline()
elif row_data.startswith("Solver"):
self.solver = row_data.split(" ")[-1]
@@ -183,48 +174,44 @@ def _load_data(self):
def plot_order(self):
- import pylab as P
-
- P.plot(self.simulated_time, self.order,drawstyle="steps-pre")
- P.grid()
- P.xlabel("Time [s]")
- P.ylabel("Order")
- P.title("Order evolution")
+ pl.plot(self.simulated_time, self.order,drawstyle="steps-pre")
+ pl.grid()
+ pl.xlabel("Time [s]")
+ pl.ylabel("Order")
+ pl.title("Order evolution")
self._plot_events()
- P.legend(("Order","Events"))
+ pl.legend(("Order","Events"))
- P.show()
+ pl.show()
def plot_error(self, threshold=None, region=None, legend=True):
- import pylab as P
-
- err = N.array(self.weighted_error)
- time = N.array(self.simulated_time)
+ err = np.array(self.weighted_error)
+ time = np.array(self.simulated_time)
if region:
lw = time > region[0]
up = time < region[1]
- time = time[N.logical_and(lw,up)]
- err = err[N.logical_and(lw,up), :]
+ time = time[np.logical_and(lw,up)]
+ err = err[np.logical_and(lw,up), :]
if threshold:
time_points, nbr_vars = err.shape
- mask = N.ones(nbr_vars,dtype=bool)
+ mask = np.ones(nbr_vars,dtype=bool)
for i in range(nbr_vars):
- if N.max(err[:,i]) < threshold:
+ if np.max(err[:,i]) < threshold:
mask[i] = False
- P.semilogy(time, err[:,mask])
+ pl.semilogy(time, err[:,mask])
if legend:
- P.legend(N.array(self.state_variables)[mask],loc="lower right")
+ pl.legend(np.array(self.state_variables)[mask],loc="lower right")
else:
- P.semilogy(time, err)
+ pl.semilogy(time, err)
if legend:
- P.legend(self.state_variables, loc="lower right")
- P.xlabel("Time [s]")
- P.ylabel("Error")
- P.title("Error evolution")
- P.grid()
- P.show()
+ pl.legend(self.state_variables, loc="lower right")
+ pl.xlabel("Time [s]")
+ pl.ylabel("Error")
+ pl.title("Error evolution")
+ pl.grid()
+ pl.show()
class Radau5ODEDebugInformation(CVodeDebugInformation):
pass
diff --git a/src/pyfmi/examples/fmi20_bouncing_ball_native.py b/src/pyfmi/examples/fmi20_bouncing_ball_native.py
index b9d9240c..22fc59fc 100644
--- a/src/pyfmi/examples/fmi20_bouncing_ball_native.py
+++ b/src/pyfmi/examples/fmi20_bouncing_ball_native.py
@@ -14,16 +14,16 @@
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program. If not, see .
-import os as O
-import pylab as P
-import numpy as N
+import os
+import pylab as pl
+import numpy as np
from pyfmi import load_fmu
-curr_dir = O.path.dirname(O.path.abspath(__file__));
-path_to_fmus = O.path.join(curr_dir, 'files', 'FMUs')
-path_to_fmus_me2 = O.path.join(path_to_fmus,"ME2.0")
+curr_dir = os.path.dirname(os.path.abspath(__file__))
+path_to_fmus = os.path.join(curr_dir, 'files', 'FMUs')
+path_to_fmus_me2 = os.path.join(path_to_fmus,"ME2.0")
def run_demo(with_plots=True):
"""
@@ -39,7 +39,7 @@ def run_demo(with_plots=True):
"""
#Load the FMU by specifying the fmu and the directory
- bouncing_fmu = load_fmu(O.path.join(path_to_fmus_me2, 'bouncingBall.fmu'))
+ bouncing_fmu = load_fmu(os.path.join(path_to_fmus_me2, 'bouncingBall.fmu'))
Tstart = 0.5 #The start time.
Tend = 3.0 #The final simulation time.
@@ -155,18 +155,18 @@ def run_demo(with_plots=True):
#Plot the solution
if with_plots:
#Plot the height
- P.figure(1)
- P.plot(t_sol,N.array(sol)[:,0])
- P.title(bouncing_fmu.get_name())
- P.ylabel('Height (m)')
- P.xlabel('Time (s)')
+ pl.figure(1)
+ pl.plot(t_sol,np.array(sol)[:,0])
+ pl.title(bouncing_fmu.get_name())
+ pl.ylabel('Height (m)')
+ pl.xlabel('Time (s)')
#Plot the velocity
- P.figure(2)
- P.plot(t_sol,N.array(sol)[:,1])
- P.title(bouncing_fmu.get_name())
- P.ylabel('Velocity (m/s)')
- P.xlabel('Time (s)')
- P.show()
+ pl.figure(2)
+ pl.plot(t_sol,np.array(sol)[:,1])
+ pl.title(bouncing_fmu.get_name())
+ pl.ylabel('Velocity (m/s)')
+ pl.xlabel('Time (s)')
+ pl.show()
if __name__ == "__main__":
run_demo()
diff --git a/src/pyfmi/examples/fmi_bouncing_ball.py b/src/pyfmi/examples/fmi_bouncing_ball.py
index 0245dc80..d7b4b658 100644
--- a/src/pyfmi/examples/fmi_bouncing_ball.py
+++ b/src/pyfmi/examples/fmi_bouncing_ball.py
@@ -14,16 +14,16 @@
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program. If not, see .
-import os as O
-import pylab as P
-import numpy as N
+import os
+import pylab as pl
+import numpy as np
from pyfmi import load_fmu
-curr_dir = O.path.dirname(O.path.abspath(__file__));
-path_to_fmus = O.path.join(curr_dir, 'files', 'FMUs','ME1.0')
-path_to_fmus2 = O.path.join(curr_dir, 'files', 'FMUs','ME2.0')
+curr_dir = os.path.dirname(os.path.abspath(__file__));
+path_to_fmus = os.path.join(curr_dir, 'files', 'FMUs','ME1.0')
+path_to_fmus2 = os.path.join(curr_dir, 'files', 'FMUs','ME2.0')
def run_demo(with_plots=True, version="2.0"):
"""
@@ -31,9 +31,9 @@ def run_demo(with_plots=True, version="2.0"):
ME FMUs version 1.0 and 2.0.
"""
if version == '1.0':
- fmu_name = O.path.join(path_to_fmus,'bouncingBall.fmu')
+ fmu_name = os.path.join(path_to_fmus,'bouncingBall.fmu')
else:
- fmu_name = O.path.join(path_to_fmus2,'bouncingBall.fmu')
+ fmu_name = os.path.join(path_to_fmus2,'bouncingBall.fmu')
model = load_fmu(fmu_name)
@@ -44,24 +44,24 @@ def run_demo(with_plots=True, version="2.0"):
v_res = res['v']
t = res['time']
- assert N.abs(res.final('h') - (0.0424044)) < 1e-4
+ assert np.abs(res.final('h') - (0.0424044)) < 1e-4
# Plot the solution
if with_plots:
# Plot the height
- fig = P.figure()
- P.clf()
- P.subplot(2,1,1)
- P.plot(t, h_res)
- P.ylabel('Height (m)')
- P.xlabel('Time (s)')
+ pl.figure()
+ pl.clf()
+ pl.subplot(2,1,1)
+ pl.plot(t, h_res)
+ pl.ylabel('Height (m)')
+ pl.xlabel('Time (s)')
# Plot the velocity
- P.subplot(2,1,2)
- P.plot(t, v_res)
- P.ylabel('Velocity (m/s)')
- P.xlabel('Time (s)')
- P.suptitle('FMI Bouncing Ball')
- P.show()
+ pl.subplot(2,1,2)
+ pl.plot(t, v_res)
+ pl.ylabel('Velocity (m/s)')
+ pl.xlabel('Time (s)')
+ pl.suptitle('FMI Bouncing Ball')
+ pl.show()
if __name__ == "__main__":
diff --git a/src/pyfmi/examples/fmi_bouncing_ball_cs.py b/src/pyfmi/examples/fmi_bouncing_ball_cs.py
index 236e3cf8..5008adbc 100644
--- a/src/pyfmi/examples/fmi_bouncing_ball_cs.py
+++ b/src/pyfmi/examples/fmi_bouncing_ball_cs.py
@@ -14,16 +14,16 @@
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program. If not, see .
-import os as O
-import pylab as P
-import numpy as N
+import os
+import pylab as pl
+import numpy as np
from pyfmi import load_fmu
-curr_dir = O.path.dirname(O.path.abspath(__file__));
-path_to_fmus = O.path.join(curr_dir, 'files', 'FMUs', 'CS1.0')
-path_to_fmus2 = O.path.join(curr_dir, 'files', 'FMUs', 'CS2.0')
+curr_dir = os.path.dirname(os.path.abspath(__file__));
+path_to_fmus = os.path.join(curr_dir, 'files', 'FMUs', 'CS1.0')
+path_to_fmus2 = os.path.join(curr_dir, 'files', 'FMUs', 'CS2.0')
def run_demo(with_plots=True, version='2.0'):
"""
@@ -32,9 +32,9 @@ def run_demo(with_plots=True, version='2.0'):
"""
if version == '1.0':
- fmu_name = O.path.join(path_to_fmus,'bouncingBall.fmu')
+ fmu_name = os.path.join(path_to_fmus,'bouncingBall.fmu')
else:
- fmu_name = O.path.join(path_to_fmus2,'bouncingBall.fmu')
+ fmu_name = os.path.join(path_to_fmus2,'bouncingBall.fmu')
model = load_fmu(fmu_name)
res = model.simulate(final_time=2.)
@@ -44,24 +44,24 @@ def run_demo(with_plots=True, version='2.0'):
v_res = res['v']
t = res['time']
- assert N.abs(res.final('h') - (0.0424044)) < 1e-2
+ assert np.abs(res.final('h') - (0.0424044)) < 1e-2
# Plot the solution
if with_plots:
# Plot the height
- fig = P.figure()
- P.clf()
- P.subplot(2,1,1)
- P.plot(t, h_res)
- P.ylabel('Height (m)')
- P.xlabel('Time (s)')
+ pl.figure()
+ pl.clf()
+ pl.subplot(2,1,1)
+ pl.plot(t, h_res)
+ pl.ylabel('Height (m)')
+ pl.xlabel('Time (s)')
# Plot the velocity
- P.subplot(2,1,2)
- P.plot(t, v_res)
- P.ylabel('Velocity (m/s)')
- P.xlabel('Time (s)')
- P.suptitle('FMI Bouncing Ball')
- P.show()
+ pl.subplot(2,1,2)
+ pl.plot(t, v_res)
+ pl.ylabel('Velocity (m/s)')
+ pl.xlabel('Time (s)')
+ pl.suptitle('FMI Bouncing Ball')
+ pl.show()
if __name__ == "__main__":
diff --git a/src/pyfmi/examples/fmi_bouncing_ball_native.py b/src/pyfmi/examples/fmi_bouncing_ball_native.py
index e00a81f4..b1dd78ef 100644
--- a/src/pyfmi/examples/fmi_bouncing_ball_native.py
+++ b/src/pyfmi/examples/fmi_bouncing_ball_native.py
@@ -16,12 +16,12 @@
# along with this program. If not, see .
import os
-import pylab as P
-import numpy as N
+import pylab as pl
+import numpy as np
from pyfmi import load_fmu
-curr_dir = os.path.dirname(os.path.abspath(__file__));
+curr_dir = os.path.dirname(os.path.abspath(__file__))
path_to_fmus = os.path.join(curr_dir, 'files', 'FMUs')
path_to_fmus_me1 = os.path.join(path_to_fmus,"ME1.0")
path_to_fmus_cs1 = os.path.join(path_to_fmus,"CS1.0")
@@ -144,18 +144,18 @@ def run_demo(with_plots=True):
#Plot the solution
if with_plots:
#Plot the height
- P.figure(1)
- P.plot(t_sol,N.array(sol)[:,0])
- P.title(bouncing_fmu.get_name())
- P.ylabel('Height (m)')
- P.xlabel('Time (s)')
+ pl.figure(1)
+ pl.plot(t_sol,np.array(sol)[:,0])
+ pl.title(bouncing_fmu.get_name())
+ pl.ylabel('Height (m)')
+ pl.xlabel('Time (s)')
#Plot the velocity
- P.figure(2)
- P.plot(t_sol,N.array(sol)[:,1])
- P.title(bouncing_fmu.get_name())
- P.ylabel('Velocity (m/s)')
- P.xlabel('Time (s)')
- P.show()
+ pl.figure(2)
+ pl.plot(t_sol,np.array(sol)[:,1])
+ pl.title(bouncing_fmu.get_name())
+ pl.ylabel('Velocity (m/s)')
+ pl.xlabel('Time (s)')
+ pl.show()
if __name__ == "__main__":
run_demo()
diff --git a/src/pyfmi/examples/fmu_with_input.py b/src/pyfmi/examples/fmu_with_input.py
index 2f7684f3..985233f5 100644
--- a/src/pyfmi/examples/fmu_with_input.py
+++ b/src/pyfmi/examples/fmu_with_input.py
@@ -15,16 +15,16 @@
# You should have received a copy of the GNU Lesser General Public License
# along with this program. If not, see .
-import os as O
-import numpy as N
-import pylab as p
+import os
+import numpy as np
+import pylab as pl
from pyfmi import load_fmu
-curr_dir = O.path.dirname(O.path.abspath(__file__));
-path_to_fmus = O.path.join(curr_dir, 'files', 'FMUs')
-path_to_fmus_me1 = O.path.join(path_to_fmus,"ME1.0")
-path_to_fmus_cs1 = O.path.join(path_to_fmus,"CS1.0")
+curr_dir = os.path.dirname(os.path.abspath(__file__))
+path_to_fmus = os.path.join(curr_dir, 'files', 'FMUs')
+path_to_fmus_me1 = os.path.join(path_to_fmus,"ME1.0")
+path_to_fmus_cs1 = os.path.join(path_to_fmus,"CS1.0")
def run_demo(with_plots=True):
"""
@@ -32,12 +32,12 @@ def run_demo(with_plots=True):
See also simulation_with_input.py
"""
- fmu_name = O.path.join(path_to_fmus_me1,'SecondOrder.fmu')
+ fmu_name = os.path.join(path_to_fmus_me1,'SecondOrder.fmu')
# Generate input
- t = N.linspace(0.,10.,100)
- u = N.cos(t)
- u_traj = N.transpose(N.vstack((t,u)))
+ t = np.linspace(0.,10.,100)
+ u = np.cos(t)
+ u_traj = np.transpose(np.vstack((t,u)))
# Create input object
input_object = ('u', u_traj)
@@ -56,17 +56,17 @@ def run_demo(with_plots=True):
u_sim = res['u']
time_sim = res['time']
- assert N.abs(res.final('x1')*1.e1 - (-8.3999640)) < 1e-3
- assert N.abs(res.final('x2')*1.e1 - (-5.0691179)) < 1e-3
- assert N.abs(res.final('u')*1.e1 - (-8.3907153)) < 1e-3
+ assert np.abs(res.final('x1')*1.e1 - (-8.3999640)) < 1e-3
+ assert np.abs(res.final('x2')*1.e1 - (-5.0691179)) < 1e-3
+ assert np.abs(res.final('u')*1.e1 - (-8.3907153)) < 1e-3
if with_plots:
- fig = p.figure()
- p.subplot(2,1,1)
- p.plot(time_sim, x1_sim, time_sim, x2_sim)
- p.subplot(2,1,2)
- p.plot(time_sim, u_sim,'x-',t, u[:],'x-')
- p.show()
+ pl.figure()
+ pl.subplot(2,1,1)
+ pl.plot(time_sim, x1_sim, time_sim, x2_sim)
+ pl.subplot(2,1,2)
+ pl.plot(time_sim, u_sim,'x-',t, u[:],'x-')
+ pl.show()
if __name__=="__main__":
run_demo()
diff --git a/src/pyfmi/examples/fmu_with_input_function.py b/src/pyfmi/examples/fmu_with_input_function.py
index c97db89e..2e4c42f5 100644
--- a/src/pyfmi/examples/fmu_with_input_function.py
+++ b/src/pyfmi/examples/fmu_with_input_function.py
@@ -15,16 +15,16 @@
# You should have received a copy of the GNU Lesser General Public License
# along with this program. If not, see .
-import os as O
-import numpy as N
-import pylab as p
+import os
+import numpy as np
+import pylab as pl
from pyfmi import load_fmu
-curr_dir = O.path.dirname(O.path.abspath(__file__));
-path_to_fmus = O.path.join(curr_dir, 'files', 'FMUs')
-path_to_fmus_me1 = O.path.join(path_to_fmus,"ME1.0")
-path_to_fmus_cs1 = O.path.join(path_to_fmus,"CS1.0")
+curr_dir = os.path.dirname(os.path.abspath(__file__))
+path_to_fmus = os.path.join(curr_dir, 'files', 'FMUs')
+path_to_fmus_me1 = os.path.join(path_to_fmus,"ME1.0")
+path_to_fmus_cs1 = os.path.join(path_to_fmus,"CS1.0")
def run_demo(with_plots=True):
"""
@@ -32,10 +32,10 @@ def run_demo(with_plots=True):
See also simulation_with_input.py
"""
- fmu_name = O.path.join(path_to_fmus_me1,'SecondOrder.fmu')
+ fmu_name = os.path.join(path_to_fmus_me1,'SecondOrder.fmu')
# Create input object
- input_object = ('u', N.cos)
+ input_object = ('u', np.cos)
# Load the dynamic library and XML data
model = load_fmu(fmu_name)
@@ -48,17 +48,17 @@ def run_demo(with_plots=True):
u_sim = res['u']
time_sim = res['time']
- assert N.abs(res.final('x1') - (-1.646485144)) < 1e-3
- assert N.abs(res.final('x2')*1.e1 - (-7.30591626709)) < 1e-3
- assert N.abs(res.final('u')*1.e1 - (1.54251449888)) < 1e-3
+ assert np.abs(res.final('x1') - (-1.646485144)) < 1e-3
+ assert np.abs(res.final('x2')*1.e1 - (-7.30591626709)) < 1e-3
+ assert np.abs(res.final('u')*1.e1 - (1.54251449888)) < 1e-3
if with_plots:
- fig = p.figure()
- p.subplot(2,1,1)
- p.plot(time_sim, x1_sim, time_sim, x2_sim)
- p.subplot(2,1,2)
- p.plot(time_sim, u_sim)
- p.show()
+ pl.figure()
+ pl.subplot(2,1,1)
+ pl.plot(time_sim, x1_sim, time_sim, x2_sim)
+ pl.subplot(2,1,2)
+ pl.plot(time_sim, u_sim)
+ pl.show()
if __name__=="__main__":
run_demo()
diff --git a/src/pyfmi/fmi.pxd b/src/pyfmi/fmi.pxd
index b4caf933..b110a24c 100644
--- a/src/pyfmi/fmi.pxd
+++ b/src/pyfmi/fmi.pxd
@@ -17,17 +17,8 @@
"""
Module containing the FMI interface Python wrappers.
"""
-import os
-import sys
-import logging
-import fnmatch
-import re
-from collections import OrderedDict
-
-import numpy as N
-cimport numpy as N
-
-N.import_array()
+import numpy as np
+cimport numpy as np
cimport pyfmi.fmil_import as FMIL
@@ -161,10 +152,6 @@ cdef class FMUModelME1(FMUModelBase):
cdef int _get_nominal_continuous_states_fmil(self, FMIL.fmi1_real_t* xnominal, size_t nx)
cdef public object _preinit_nominal_continuous_states
-cdef class _ForTestingFMUModelME1(FMUModelME1):
- cdef int _get_nominal_continuous_states_fmil(self, FMIL.fmi1_real_t* xnominal, size_t nx)
- cpdef set_allocated_fmu(self, int value)
-
cdef class FMUModelBase2(ModelBase):
"""
FMI Model loaded from a dll.
@@ -232,22 +219,22 @@ cdef class FMUModelBase2(ModelBase):
cpdef serialized_fmu_state_size(self, state)
cdef _add_scalar_variables(self, FMIL.fmi2_import_variable_list_t* variable_list)
cdef _add_scalar_variable(self, FMIL.fmi2_import_variable_t* variable)
- cdef int _get_directional_derivative(self, N.ndarray v_ref, N.ndarray z_ref, N.ndarray dv, N.ndarray dz) except -1
+ cdef int _get_directional_derivative(self, np.ndarray v_ref, np.ndarray z_ref, np.ndarray dv, np.ndarray dz) except -1
cpdef set_real(self, valueref, values)
- cpdef N.ndarray get_real(self, valueref)
- cdef int _set_real(self, FMIL.fmi2_value_reference_t* vrefs, FMIL.fmi2_real_t* values, size_t size)
- cdef int _get_real_by_ptr(self, FMIL.fmi2_value_reference_t* vrefs, size_t size, FMIL.fmi2_real_t* values)
- cdef int _get_real_by_list(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_real_t[:] values)
- cdef int _get_integer(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_integer_t[:] values)
- cdef int _get_boolean(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_real_t[:] values)
+ cpdef np.ndarray get_real(self, valueref)
+ cdef int _set_real(self, FMIL.fmi2_value_reference_t* vrefs, FMIL.fmi2_real_t* values, size_t _size)
+ cdef int _get_real_by_ptr(self, FMIL.fmi2_value_reference_t* vrefs, size_t _size, FMIL.fmi2_real_t* values)
+ cdef int _get_real_by_list(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_real_t[:] values)
+ cdef int _get_integer(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_integer_t[:] values)
+ cdef int _get_boolean(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_real_t[:] values)
cdef class FMUModelCS2(FMUModelBase2):
cpdef _get_time(self)
cpdef _set_time(self, FMIL.fmi2_real_t t)
cpdef int do_step(self, FMIL.fmi2_real_t current_t, FMIL.fmi2_real_t step_size, new_step=*)
- cdef int _set_input_derivatives(self, N.ndarray value_refs, N.ndarray values, N.ndarray orders)
- cdef int _get_output_derivatives(self, N.ndarray value_refs, N.ndarray values, N.ndarray orders)
+ cdef int _set_input_derivatives(self, np.ndarray value_refs, np.ndarray values, np.ndarray orders)
+ cdef int _get_output_derivatives(self, np.ndarray value_refs, np.ndarray values, np.ndarray orders)
cdef class FMUModelME2(FMUModelBase2):
@@ -266,20 +253,11 @@ cdef class FMUModelME2(FMUModelBase2):
cdef class WorkerClass2:
cdef int _dim
- cdef N.ndarray _tmp1_val, _tmp2_val, _tmp3_val, _tmp4_val
- cdef N.ndarray _tmp1_ref, _tmp2_ref, _tmp3_ref, _tmp4_ref
+ cdef np.ndarray _tmp1_val, _tmp2_val, _tmp3_val, _tmp4_val
+ cdef np.ndarray _tmp1_ref, _tmp2_ref, _tmp3_ref, _tmp4_ref
cdef FMIL.fmi2_real_t* get_real_vector(self, int index)
cdef FMIL.fmi2_value_reference_t* get_value_reference_vector(self, int index)
- cdef N.ndarray get_value_reference_numpy_vector(self, int index)
- cdef N.ndarray get_real_numpy_vector(self, int index)
+ cdef np.ndarray get_value_reference_numpy_vector(self, int index)
+ cdef np.ndarray get_real_numpy_vector(self, int index)
cpdef verify_dimensions(self, int dim)
-
-cdef class _ForTestingFMUModelME2(FMUModelME2):
- cdef int _get_real_by_ptr(self, FMIL.fmi2_value_reference_t* vrefs, size_t size, FMIL.fmi2_real_t* values)
- cdef int _set_real(self, FMIL.fmi2_value_reference_t* vrefs, FMIL.fmi2_real_t* values, size_t size)
- cdef int _get_real_by_list(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_real_t[:] values)
- cdef int _get_integer(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_integer_t[:] values)
- cdef int _get_boolean(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_real_t[:] values)
- cdef int _get_nominal_continuous_states_fmil(self, FMIL.fmi2_real_t* xnominal, size_t nx)
- cpdef set_initialized_fmu(self, int value)
diff --git a/src/pyfmi/fmi.pyx b/src/pyfmi/fmi.pyx
index e60b8268..13263331 100644
--- a/src/pyfmi/fmi.pyx
+++ b/src/pyfmi/fmi.pyx
@@ -27,7 +27,6 @@ For profiling:
# distutils: define_macros=CYTHON_TRACE_NOGIL=1
"""
import os
-import sys
import logging
import fnmatch
import re
@@ -35,21 +34,20 @@ from collections import OrderedDict
cimport cython
from io import UnsupportedOperation
-import scipy.sparse as sp
-import numpy as N
-cimport numpy as N
+import scipy.sparse as sps
+import numpy as np
+cimport numpy as np
from numpy cimport PyArray_DATA
cimport pyfmi.fmil_import as FMIL
-from pyfmi.common.core import create_temp_dir, delete_temp_dir
-from pyfmi.common.core import create_temp_file, delete_temp_file
+from pyfmi.common.core import create_temp_dir
-from pyfmi.fmi_util import cpr_seed, enable_caching, python3_flag
+from pyfmi.fmi_util import cpr_seed, enable_caching
from pyfmi.fmi_util cimport encode, decode
-int = N.int32
-N.int = N.int32
+int = np.int32
+np.int = np.int32
"""Basic flags related to FMI"""
@@ -143,8 +141,8 @@ FMI2_INITIAL_UNKNOWN = 3
DEF FORWARD_DIFFERENCE = 1
DEF CENTRAL_DIFFERENCE = 2
-FORWARD_DIFFERENCE_EPS = (N.finfo(float).eps)**0.5
-CENTRAL_DIFFERENCE_EPS = (N.finfo(float).eps)**(1/3.0)
+FORWARD_DIFFERENCE_EPS = (np.finfo(float).eps)**0.5
+CENTRAL_DIFFERENCE_EPS = (np.finfo(float).eps)**(1/3.0)
"""Flags for evaluation of FMI Jacobians"""
"""Evaluate Jacobian w.r.t. states."""
@@ -1158,7 +1156,7 @@ cdef class IntegerType2(DeclaredType2):
"""
Class defining data structure based on the XML element Enumeration.
"""
- def __init__(self, name, description = "", quantity = "", min = -N.inf, max = N.inf):
+ def __init__(self, name, description = "", quantity = "", min = -np.inf, max = np.inf):
DeclaredType2.__init__(self, name, description, quantity)
self._min = min
@@ -1190,7 +1188,7 @@ cdef class RealType2(DeclaredType2):
"""
Class defining data structure based on the XML element Enumeration.
"""
- def __init__(self, name, description = "", quantity = "", min = -N.inf, max = N.inf, nominal = 1.0, unbounded = False,
+ def __init__(self, name, description = "", quantity = "", min = -np.inf, max = np.inf, nominal = 1.0, unbounded = False,
relative_quantity = False, display_unit = "", unit = ""):
DeclaredType2.__init__(self, name, description, quantity)
@@ -1544,9 +1542,9 @@ cdef class FMUModelBase(ModelBase):
Calls the low-level FMI function: fmiGetReal
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = N.array(valueref, copy=False, dtype=N.uint32).ravel()
- cdef FMIL.size_t nref = N.size(val_ref)
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] val = N.array([0.0]*nref, dtype=float, ndmin=1)
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = np.array(valueref, copy=False, dtype=np.uint32).ravel()
+ cdef FMIL.size_t nref = np.size(val_ref)
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] val = np.array([0.0]*nref, dtype=float, ndmin=1)
if nref == 0: ## get_real([])
return val
@@ -1577,11 +1575,11 @@ cdef class FMUModelBase(ModelBase):
Calls the low-level FMI function: fmiSetReal
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = N.array(valueref, copy=False, dtype=N.uint32).ravel()
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] val = N.array(values, copy=False, dtype=float).ravel()
- cdef FMIL.size_t nref = N.size(val_ref)
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = np.array(valueref, copy=False, dtype=np.uint32).ravel()
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] val = np.array(values, copy=False, dtype=float).ravel()
+ cdef FMIL.size_t nref = np.size(val_ref)
- if nref != N.size(val):
+ if nref != np.size(val):
raise FMUException(
'The length of valueref and values are inconsistent.')
@@ -1611,9 +1609,9 @@ cdef class FMUModelBase(ModelBase):
Calls the low-level FMI function: fmiGetInteger
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = N.array(valueref, dtype=N.uint32,ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(val_ref)
- cdef N.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] val = N.array([0]*nref, dtype=int,ndmin=1)
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = np.array(valueref, dtype=np.uint32,ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(val_ref)
+ cdef np.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] val = np.array([0]*nref, dtype=int,ndmin=1)
if nref == 0: ## get_integer([])
return val
@@ -1644,11 +1642,11 @@ cdef class FMUModelBase(ModelBase):
Calls the low-level FMI function: fmiSetInteger
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = N.array(valueref, dtype=N.uint32,ndmin=1).ravel()
- cdef N.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] val = N.array(values, dtype=int,ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(val_ref)
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = np.array(valueref, dtype=np.uint32,ndmin=1).ravel()
+ cdef np.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] val = np.array(values, dtype=int,ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(val_ref)
- if nref != N.size(val):
+ if nref != np.size(val):
raise FMUException(
'The length of valueref and values are inconsistent.')
@@ -1679,11 +1677,11 @@ cdef class FMUModelBase(ModelBase):
Calls the low-level FMI function: fmiGetBoolean
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = N.array(valueref, dtype=N.uint32,ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(val_ref)
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = np.array(valueref, dtype=np.uint32,ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(val_ref)
if nref == 0: ## get_boolean([])
- return N.array([])
+ return np.array([])
cdef void *val = FMIL.malloc(sizeof(FMIL.fmi1_boolean_t)*nref)
@@ -1699,7 +1697,7 @@ cdef class FMUModelBase(ModelBase):
if status != 0:
raise FMUException('Failed to get the Boolean values.')
- return N.array(return_values)
+ return np.array(return_values)
def set_boolean(self, valueref, values):
"""
@@ -1720,19 +1718,19 @@ cdef class FMUModelBase(ModelBase):
Calls the low-level FMI function: fmiSetBoolean
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = N.array(valueref, dtype=N.uint32,ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(val_ref)
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = np.array(valueref, dtype=np.uint32,ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(val_ref)
cdef void *val = FMIL.malloc(sizeof(FMIL.fmi1_boolean_t)*nref)
- values = N.array(values,ndmin=1).ravel()
+ values = np.array(values,ndmin=1).ravel()
for i in range(nref):
if values[i]:
(val)[i] = 1
else:
(val)[i] = 0
- if nref != N.size(values):
+ if nref != np.size(values):
raise FMUException(
'The length of valueref and values are inconsistent.')
@@ -1764,8 +1762,8 @@ cdef class FMUModelBase(ModelBase):
Calls the low-level FMI function: fmiGetString
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1, mode='c'] input_valueref = N.array(valueref, dtype=N.uint32, ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(input_valueref)
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1, mode='c'] input_valueref = np.array(valueref, dtype=np.uint32, ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(input_valueref)
if nref == 0: ## get_string([])
return []
@@ -1803,21 +1801,21 @@ cdef class FMUModelBase(ModelBase):
Calls the low-level FMI function: fmiSetString
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = N.array(valueref, dtype=N.uint32,ndmin=1).ravel()
- cdef FMIL.fmi1_string_t* val = FMIL.malloc(sizeof(FMIL.fmi1_string_t)*N.size(val_ref))
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] val_ref = np.array(valueref, dtype=np.uint32,ndmin=1).ravel()
+ cdef FMIL.fmi1_string_t* val = FMIL.malloc(sizeof(FMIL.fmi1_string_t)*np.size(val_ref))
if not isinstance(values, list):
raise FMUException(
'The values needs to be a list of values.')
- if len(values) != N.size(val_ref):
+ if len(values) != np.size(val_ref):
raise FMUException(
'The length of valueref and values are inconsistent.')
values = [encode(item) for item in values]
- for i in range(N.size(val_ref)):
+ for i in range(np.size(val_ref)):
val[i] = values[i]
- status = FMIL.fmi1_import_set_string(self._fmu, val_ref.data, N.size(val_ref), val)
+ status = FMIL.fmi1_import_set_string(self._fmu, val_ref.data, np.size(val_ref), val)
FMIL.free(val)
@@ -2888,9 +2886,9 @@ cdef class FMUModelCS1(FMUModelBase):
cdef int status
cdef unsigned int max_output_derivative
cdef FMIL.size_t nref
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] values
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] value_refs
- cdef N.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] orders
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] values
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] value_refs
+ cdef np.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] orders
cdef FMIL.fmi1_import_capabilities_t *fmu_capabilities
fmu_capabilities = FMIL.fmi1_import_get_capabilities(self._fmu)
@@ -2901,20 +2899,20 @@ cdef class FMUModelCS1(FMUModelBase):
if isinstance(variables,str):
nref = 1
- value_refs = N.array([0], dtype=N.uint32,ndmin=1).ravel()
- orders = N.array(order, dtype=N.int32)
+ value_refs = np.array([0], dtype=np.uint32,ndmin=1).ravel()
+ orders = np.array(order, dtype=np.int32)
value_refs[0] = self.get_variable_valueref(variables)
elif isinstance(variables,list) and isinstance(variables[-1],str):
nref = len(variables)
- value_refs = N.array([0]*nref, dtype=N.uint32,ndmin=1).ravel()
- orders = N.array([0]*nref, dtype=N.int32)
+ value_refs = np.array([0]*nref, dtype=np.uint32,ndmin=1).ravel()
+ orders = np.array([0]*nref, dtype=np.int32)
for i in range(nref):
value_refs[i] = self.get_variable_valueref(variables[i])
orders[i] = order
else:
raise FMUException("The variables must either be a string or a list of strings")
- values = N.array([0.0]*nref,dtype=float, ndmin=1)
+ values = np.array([0.0]*nref,dtype=float, ndmin=1)
status = FMIL.fmi1_import_get_real_output_derivatives(self._fmu, value_refs.data, nref, orders.data, values.data)
@@ -2976,30 +2974,30 @@ cdef class FMUModelCS1(FMUModelBase):
cdef int status
cdef int can_interpolate_inputs
cdef FMIL.fmi1_import_capabilities_t *fmu_capabilities
- cdef N.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] np_orders = N.array(orders, dtype=N.int32, ndmin=1).ravel()
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] value_refs
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] val = N.array(values, dtype=float, ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(val)
- orders = N.array([0]*nref, dtype=N.int32)
+ cdef np.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] np_orders = np.array(orders, dtype=np.int32, ndmin=1).ravel()
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] value_refs
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] val = np.array(values, dtype=float, ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(val)
+ orders = np.array([0]*nref, dtype=np.int32)
- if nref != N.size(np_orders):
+ if nref != np.size(np_orders):
raise FMUException("The number of variables must be the same as the number of orders.")
fmu_capabilities = FMIL.fmi1_import_get_capabilities(self._fmu)
can_interpolate_inputs = FMIL.fmi1_import_get_canInterpolateInputs(fmu_capabilities)
#NOTE IS THIS THE HIGHEST ORDER OF INTERPOLATION OR SIMPLY IF IT CAN OR NOT?
- for i in range(N.size(np_orders)):
+ for i in range(np.size(np_orders)):
if np_orders[i] < 1:
raise FMUException("The order must be greater than zero.")
if not can_interpolate_inputs:
raise FMUException("The FMU does not support input derivatives.")
if isinstance(variables,str):
- value_refs = N.array([0], dtype=N.uint32,ndmin=1).ravel()
+ value_refs = np.array([0], dtype=np.uint32,ndmin=1).ravel()
value_refs[0] = self.get_variable_valueref(variables)
elif isinstance(variables,list) and isinstance(variables[-1],str):
- value_refs = N.array([0]*nref, dtype=N.uint32,ndmin=1).ravel()
+ value_refs = np.array([0]*nref, dtype=np.uint32,ndmin=1).ravel()
for i in range(nref):
value_refs[i] = self.get_variable_valueref(variables[i])
else:
@@ -3404,7 +3402,7 @@ cdef class FMUModelME1(FMUModelBase):
def _get_continuous_states(self):
cdef int status
- cdef N.ndarray[double, ndim=1,mode='c'] ndx = N.zeros(self._nContinuousStates, dtype=N.double)
+ cdef np.ndarray[double, ndim=1,mode='c'] ndx = np.zeros(self._nContinuousStates, dtype=np.double)
status = FMIL.fmi1_import_get_continuous_states(self._fmu, ndx.data ,self._nContinuousStates)
if status != 0:
@@ -3412,11 +3410,11 @@ cdef class FMUModelME1(FMUModelBase):
return ndx
- def _set_continuous_states(self, N.ndarray[FMIL.fmi1_real_t] values):
+ def _set_continuous_states(self, np.ndarray[FMIL.fmi1_real_t] values):
cdef int status
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] ndx = values
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] ndx = values
- if N.size(ndx) != self._nContinuousStates:
+ if np.size(ndx) != self._nContinuousStates:
raise FMUException(
'Failed to set the new continuous states. ' \
'The number of values are not consistent with the number of '\
@@ -3446,7 +3444,7 @@ cdef class FMUModelME1(FMUModelBase):
The nominal values.
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1, mode='c'] xn = N.zeros(self._nContinuousStates, dtype=N.double)
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1, mode='c'] xn = np.zeros(self._nContinuousStates, dtype=np.double)
status = self._get_nominal_continuous_states_fmil( xn.data, self._nContinuousStates)
if status != 0:
@@ -3496,7 +3494,7 @@ cdef class FMUModelME1(FMUModelBase):
Calls the low-level FMI function: fmiGetDerivatives
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] values = N.empty(self._nContinuousStates,dtype=N.double)
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] values = np.empty(self._nContinuousStates,dtype=np.double)
if self._nContinuousStates > 0:
status = FMIL.fmi1_import_get_derivatives(self._fmu, values.data, self._nContinuousStates)
@@ -3524,7 +3522,7 @@ cdef class FMUModelME1(FMUModelBase):
Calls the low-level FMI function: fmiGetEventIndicators
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] values = N.empty(self._nEventIndicators,dtype=N.double)
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] values = np.empty(self._nEventIndicators,dtype=np.double)
status = FMIL.fmi1_import_get_event_indicators(self._fmu, values.data, self._nEventIndicators)
@@ -3681,7 +3679,7 @@ cdef class FMUModelME1(FMUModelBase):
Calls the low-level FMI function: fmiGetStateValueReferences
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] values = N.zeros(self._nContinuousStates,dtype=N.uint32)
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] values = np.zeros(self._nContinuousStates,dtype=np.uint32)
status = FMIL.fmi1_import_get_state_value_references(
self._fmu, values.data, self._nContinuousStates)
@@ -3945,27 +3943,6 @@ cdef class FMUModelME1(FMUModelBase):
self._instantiated_fmu = 0
-cdef class _ForTestingFMUModelME1(FMUModelME1):
-
- cdef int _get_nominal_continuous_states_fmil(self, FMIL.fmi1_real_t* xnominal, size_t nx):
- for i in range(nx):
- if self._allocated_fmu == 1: # If initialized
- # Set new values to test that atol gets auto-corrected.
- xnominal[i] = 3.0
- else:
- # Set some illegal values in order to test the fallback/auto-correction.
- xnominal[i] = ((( i) % 3) - 1) * 2.0 # -2.0, 0.0, 2.0,
- return FMIL.fmi1_status_ok
-
- cpdef set_allocated_fmu(self, int value):
- self._allocated_fmu = value
-
- def __dealloc__(self):
- # Avoid segfaults in dealloc. The FMU binaries should never be loaded for this
- # test class, so we should never try to terminate or deallocate the FMU instance.
- self._allocated_fmu = 0
-
-
cdef class FMUModelBase2(ModelBase):
"""
FMI Model loaded from a dll.
@@ -4189,7 +4166,7 @@ cdef class FMUModelBase2(ModelBase):
self._log = []
- cpdef N.ndarray get_real(self, valueref):
+ cpdef np.ndarray get_real(self, valueref):
"""
Returns the real-values from the valuereference(s).
@@ -4210,9 +4187,9 @@ cdef class FMUModelBase2(ModelBase):
Calls the low-level FMI function: fmi2GetReal
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = N.array(valueref, copy=False, dtype=N.uint32).ravel()
- cdef FMIL.size_t nref = N.size(input_valueref)
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1,mode='c'] output_value = N.zeros(nref)
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = np.array(valueref, copy=False, dtype=np.uint32).ravel()
+ cdef FMIL.size_t nref = np.size(input_valueref)
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1,mode='c'] output_value = np.zeros(nref)
if nref == 0: ## get_real([])
return output_value
@@ -4244,28 +4221,28 @@ cdef class FMUModelBase2(ModelBase):
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = N.array(valueref, copy=False, dtype=N.uint32).ravel()
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1,mode='c'] set_value = N.array(values, copy=False, dtype=float).ravel()
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = np.array(valueref, copy=False, dtype=np.uint32).ravel()
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1,mode='c'] set_value = np.array(values, copy=False, dtype=float).ravel()
- if N.size(input_valueref) != N.size(set_value):
+ if np.size(input_valueref) != np.size(set_value):
raise FMUException('The length of valueref and values are inconsistent.')
- status = FMIL.fmi2_import_set_real(self._fmu, input_valueref.data, N.size(input_valueref), set_value.data)
+ status = FMIL.fmi2_import_set_real(self._fmu, input_valueref.data, np.size(input_valueref), set_value.data)
if status != 0:
raise FMUException('Failed to set the Real values. See the log for possibly more information.')
- cdef int _get_real_by_list(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_real_t[:] values):
- return FMIL.fmi2_import_get_real(self._fmu, &valueref[0], size, &values[0])
+ cdef int _get_real_by_list(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_real_t[:] values):
+ return FMIL.fmi2_import_get_real(self._fmu, &valueref[0], _size, &values[0])
- cdef int _get_real_by_ptr(self, FMIL.fmi2_value_reference_t* vrefs, size_t size, FMIL.fmi2_real_t* values):
- return FMIL.fmi2_import_get_real(self._fmu, vrefs, size, values)
+ cdef int _get_real_by_ptr(self, FMIL.fmi2_value_reference_t* vrefs, size_t _size, FMIL.fmi2_real_t* values):
+ return FMIL.fmi2_import_get_real(self._fmu, vrefs, _size, values)
- cdef int _set_real(self, FMIL.fmi2_value_reference_t* vrefs, FMIL.fmi2_real_t* values, size_t size):
- return FMIL.fmi2_import_set_real(self._fmu, vrefs, size, values)
+ cdef int _set_real(self, FMIL.fmi2_value_reference_t* vrefs, FMIL.fmi2_real_t* values, size_t _size):
+ return FMIL.fmi2_import_set_real(self._fmu, vrefs, _size, values)
- cdef int _get_integer(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_integer_t[:] values):
- return FMIL.fmi2_import_get_integer(self._fmu, &valueref[0], size, &values[0])
+ cdef int _get_integer(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_integer_t[:] values):
+ return FMIL.fmi2_import_get_integer(self._fmu, &valueref[0], _size, &values[0])
def get_integer(self, valueref):
"""
@@ -4288,9 +4265,9 @@ cdef class FMUModelBase2(ModelBase):
Calls the low-level FMI function: fmi2GetInteger
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = N.array(valueref, dtype=N.uint32,ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(input_valueref)
- cdef N.ndarray[FMIL.fmi2_integer_t, ndim=1,mode='c'] output_value = N.zeros(nref, dtype=int)
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = np.array(valueref, dtype=np.uint32,ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(input_valueref)
+ cdef np.ndarray[FMIL.fmi2_integer_t, ndim=1,mode='c'] output_value = np.zeros(nref, dtype=int)
if nref == 0: ## get_integer([])
return output_value
@@ -4321,11 +4298,11 @@ cdef class FMUModelBase2(ModelBase):
Calls the low-level FMI function: fmi2SetInteger
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = N.array(valueref, dtype=N.uint32,ndmin=1).ravel()
- cdef N.ndarray[FMIL.fmi2_integer_t, ndim=1,mode='c'] set_value = N.array(values, dtype=int,ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(input_valueref)
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = np.array(valueref, dtype=np.uint32,ndmin=1).ravel()
+ cdef np.ndarray[FMIL.fmi2_integer_t, ndim=1,mode='c'] set_value = np.array(values, dtype=int,ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(input_valueref)
- if nref != N.size(set_value):
+ if nref != np.size(set_value):
raise FMUException('The length of valueref and values are inconsistent.')
status = FMIL.fmi2_import_set_integer(self._fmu, input_valueref.data, nref, set_value.data)
@@ -4333,13 +4310,13 @@ cdef class FMUModelBase2(ModelBase):
if status != 0:
raise FMUException('Failed to set the Integer values. See the log for possibly more information.')
- cdef int _get_boolean(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_real_t[:] values):
+ cdef int _get_boolean(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_real_t[:] values):
cdef int status
- cdef void* output_value = FMIL.malloc(sizeof(FMIL.fmi2_boolean_t)*size)
+ cdef void* output_value = FMIL.malloc(sizeof(FMIL.fmi2_boolean_t)*_size)
- status = FMIL.fmi2_import_get_boolean(self._fmu, &valueref[0], size, output_value)
+ status = FMIL.fmi2_import_get_boolean(self._fmu, &valueref[0], _size, output_value)
- for i in range(size):
+ for i in range(_size):
values[i] = (output_value)[i]==1
FMIL.free(output_value)
@@ -4367,11 +4344,11 @@ cdef class FMUModelBase2(ModelBase):
Calls the low-level FMI function: fmi2GetBoolean
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = N.array(valueref, dtype=N.uint32, ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(input_valueref)
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = np.array(valueref, dtype=np.uint32, ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(input_valueref)
if nref == 0: ## get_boolean([])
- return N.array([])
+ return np.array([])
cdef void* output_value = FMIL.malloc(sizeof(FMIL.fmi2_boolean_t)*nref)
@@ -4387,7 +4364,7 @@ cdef class FMUModelBase2(ModelBase):
if status != 0:
raise FMUException('Failed to get the Boolean values.')
- return N.array(return_values)
+ return np.array(return_values)
def set_boolean(self, valueref, values):
"""
@@ -4409,12 +4386,12 @@ cdef class FMUModelBase2(ModelBase):
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = N.array(valueref, dtype=N.uint32,ndmin=1).flatten()
- cdef FMIL.size_t nref = N.size(input_valueref)
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] input_valueref = np.array(valueref, dtype=np.uint32,ndmin=1).flatten()
+ cdef FMIL.size_t nref = np.size(input_valueref)
cdef void* set_value = FMIL.malloc(sizeof(FMIL.fmi2_boolean_t)*nref)
- values = N.array(values,ndmin=1).ravel()
+ values = np.array(values,ndmin=1).ravel()
for i in range(nref):
if values[i]:
( set_value)[i] = 1
@@ -4452,8 +4429,8 @@ cdef class FMUModelBase2(ModelBase):
Calls the low-level FMI function: fmi2GetString
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] input_valueref = N.array(valueref, dtype=N.uint32, ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(input_valueref)
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] input_valueref = np.array(valueref, dtype=np.uint32, ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(input_valueref)
if nref == 0: ## get_string([])
return []
@@ -4492,21 +4469,21 @@ cdef class FMUModelBase2(ModelBase):
Calls the low-level FMI function: fmi2SetString
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] val_ref = N.array(valueref, dtype=N.uint32,ndmin=1).ravel()
- cdef FMIL.fmi2_string_t* val = FMIL.malloc(sizeof(FMIL.fmi2_string_t)*N.size(val_ref))
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1,mode='c'] val_ref = np.array(valueref, dtype=np.uint32,ndmin=1).ravel()
+ cdef FMIL.fmi2_string_t* val = FMIL.malloc(sizeof(FMIL.fmi2_string_t)*np.size(val_ref))
if not isinstance(values, list):
raise FMUException(
'The values needs to be a list of values.')
- if len(values) != N.size(val_ref):
+ if len(values) != np.size(val_ref):
raise FMUException(
'The length of valueref and values are inconsistent.')
values = [encode(item) for item in values]
- for i in range(N.size(val_ref)):
+ for i in range(np.size(val_ref)):
val[i] = values[i]
- status = FMIL.fmi2_import_set_string(self._fmu, val_ref.data, N.size(val_ref), val)
+ status = FMIL.fmi2_import_set_string(self._fmu, val_ref.data, np.size(val_ref), val)
FMIL.free(val)
@@ -6119,7 +6096,7 @@ cdef class FMUModelBase2(ModelBase):
cdef FMUState2 internal_state = state
cdef FMIL.size_t n_bytes
- cdef N.ndarray[FMIL.fmi2_byte_t, ndim=1, mode='c'] serialized_fmu
+ cdef np.ndarray[FMIL.fmi2_byte_t, ndim=1, mode='c'] serialized_fmu
cap1 = FMIL.fmi2_import_get_capability(self._fmu, FMIL.fmi2_me_canSerializeFMUstate)
cap2 = FMIL.fmi2_import_get_capability(self._fmu, FMIL.fmi2_cs_canSerializeFMUstate)
@@ -6127,7 +6104,7 @@ cdef class FMUModelBase2(ModelBase):
raise FMUException('This FMU dos not support serialisation of FMU-state')
n_bytes = self.serialized_fmu_state_size(state)
- serialized_fmu = N.empty(n_bytes, dtype=N.byte)
+ serialized_fmu = np.empty(n_bytes, dtype=np.byte)
status = FMIL.fmi2_import_serialize_fmu_state(self._fmu, internal_state.fmu_state, serialized_fmu.data, n_bytes)
@@ -6159,7 +6136,7 @@ cdef class FMUModelBase2(ModelBase):
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_byte_t, ndim=1, mode='c'] ser_fmu = serialized_fmu[0]
+ cdef np.ndarray[FMIL.fmi2_byte_t, ndim=1, mode='c'] ser_fmu = serialized_fmu[0]
cdef FMUState2 state = FMUState2()
cdef FMIL.size_t n_byte = len(ser_fmu)
@@ -6327,18 +6304,11 @@ cdef class FMUModelBase2(ModelBase):
cdef FMIL.fmi2_import_variable_t *variable
cdef FMIL.fmi2_import_variable_list_t *variable_list
- if python3_flag:
- outputs = list(self.get_output_list().keys())
- states_dict = self.get_states_list()
- states_list = list(states_dict.keys())
- inputs_dict = self.get_input_list()
- inputs_list = list(inputs_dict.keys())
- else:
- outputs = self.get_output_list().keys()
- states_dict = self.get_states_list()
- states_list = states_dict.keys()
- inputs_dict = self.get_input_list()
- inputs_list = inputs_dict.keys()
+ outputs = list(self.get_output_list().keys())
+ states_dict = self.get_states_list()
+ states_list = list(states_dict.keys())
+ inputs_dict = self.get_input_list()
+ inputs_list = list(inputs_dict.keys())
states = OrderedDict()
states_kind = OrderedDict()
@@ -6435,14 +6405,9 @@ cdef class FMUModelBase2(ModelBase):
cdef FMIL.fmi2_import_variable_t *variable
cdef FMIL.fmi2_import_variable_list_t *variable_list
- if python3_flag:
- derivatives = list(self.get_derivatives_list().keys())
- states_list = list(self.get_states_list().keys())
- inputs_list = list(self.get_input_list().keys())
- else:
- derivatives = self.get_derivatives_list().keys()
- states_list = self.get_states_list().keys()
- inputs_list = self.get_input_list().keys()
+ derivatives = list(self.get_derivatives_list().keys())
+ states_list = list(self.get_states_list().keys())
+ inputs_list = list(self.get_input_list().keys())
states = OrderedDict()
states_kind = OrderedDict()
@@ -6520,8 +6485,8 @@ cdef class FMUModelBase2(ModelBase):
cdef list data = [], row = [], col = []
cdef list local_group
cdef int nbr_var_ref = len(var_ref), nbr_func_ref = len(func_ref)
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] v = N.zeros(nbr_var_ref, dtype = N.double)
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] data_local
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] v = np.zeros(nbr_var_ref, dtype = np.double)
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] data_local
cdef int ind_local = 5 if add_diag else 4
if not self._has_entered_init_mode:
@@ -6530,7 +6495,7 @@ cdef class FMUModelBase2(ModelBase):
if group is not None:
if output_matrix is not None:
- if not isinstance(output_matrix, sp.csc_matrix):
+ if not isinstance(output_matrix, sps.csc_matrix):
output_matrix = None
else:
data_local = output_matrix.data
@@ -6561,16 +6526,16 @@ cdef class FMUModelBase2(ModelBase):
A = output_matrix
else:
if len(data) == 0:
- A = sp.csc_matrix((nbr_func_ref,nbr_var_ref))
+ A = sps.csc_matrix((nbr_func_ref,nbr_var_ref))
else:
- A = sp.csc_matrix((data, (row, col)), (nbr_func_ref,nbr_var_ref))
+ A = sps.csc_matrix((data, (row, col)), (nbr_func_ref,nbr_var_ref))
return A
else:
if output_matrix is None or \
- (not isinstance(output_matrix, N.ndarray)) or \
- (isinstance(output_matrix, N.ndarray) and (output_matrix.shape[0] != nbr_func_ref or output_matrix.shape[1] != nbr_var_ref)):
- A = N.zeros((nbr_func_ref,nbr_var_ref))
+ (not isinstance(output_matrix, np.ndarray)) or \
+ (isinstance(output_matrix, np.ndarray) and (output_matrix.shape[0] != nbr_func_ref or output_matrix.shape[1] != nbr_var_ref)):
+ A = np.zeros((nbr_func_ref,nbr_var_ref))
else:
A = output_matrix
@@ -6583,10 +6548,7 @@ cdef class FMUModelBase2(ModelBase):
def _get_A(self, use_structure_info=True, add_diag=True, output_matrix=None):
if self._group_A is None and use_structure_info:
[derv_state_dep, derv_input_dep] = self.get_derivatives_dependencies()
- if python3_flag:
- self._group_A = cpr_seed(derv_state_dep, list(self.get_states_list().keys()))
- else:
- self._group_A = cpr_seed(derv_state_dep, self.get_states_list().keys())
+ self._group_A = cpr_seed(derv_state_dep, list(self.get_states_list().keys()))
if self._states_references is None:
states = self.get_states_list()
self._states_references = [s.value_reference for s in states.values()]
@@ -6604,10 +6566,7 @@ cdef class FMUModelBase2(ModelBase):
def _get_B(self, use_structure_info=True, add_diag=False, output_matrix=None):
if self._group_B is None and use_structure_info:
[derv_state_dep, derv_input_dep] = self.get_derivatives_dependencies()
- if python3_flag:
- self._group_B = cpr_seed(derv_input_dep, list(self.get_input_list().keys()))
- else:
- self._group_B = cpr_seed(derv_input_dep, self.get_input_list().keys())
+ self._group_B = cpr_seed(derv_input_dep, list(self.get_input_list().keys()))
if self._inputs_references is None:
inputs = self.get_input_list()
self._inputs_references = [s.value_reference for s in inputs.values()]
@@ -6625,10 +6584,7 @@ cdef class FMUModelBase2(ModelBase):
def _get_C(self, use_structure_info=True, add_diag=False, output_matrix=None):
if self._group_C is None and use_structure_info:
[out_state_dep, out_input_dep] = self.get_output_dependencies()
- if python3_flag:
- self._group_C = cpr_seed(out_state_dep, list(self.get_states_list().keys()))
- else:
- self._group_C = cpr_seed(out_state_dep, self.get_states_list().keys())
+ self._group_C = cpr_seed(out_state_dep, list(self.get_states_list().keys()))
if self._states_references is None:
states = self.get_states_list()
self._states_references = [s.value_reference for s in states.values()]
@@ -6646,10 +6602,7 @@ cdef class FMUModelBase2(ModelBase):
def _get_D(self, use_structure_info=True, add_diag=False, output_matrix=None):
if self._group_D is None and use_structure_info:
[out_state_dep, out_input_dep] = self.get_output_dependencies()
- if python3_flag:
- self._group_D = cpr_seed(out_input_dep, list(self.get_input_list().keys()))
- else:
- self._group_D = cpr_seed(out_input_dep, self.get_input_list().keys())
+ self._group_D = cpr_seed(out_input_dep, list(self.get_input_list().keys()))
if self._inputs_references is None:
inputs = self.get_input_list()
self._inputs_references = [s.value_reference for s in inputs.values()]
@@ -6841,11 +6794,11 @@ cdef class FMUModelBase2(ModelBase):
cdef FMIL.size_t nv, nz
#input arrays
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] v_ref = N.zeros(len(var_ref), dtype = N.uint32)
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] z_ref = N.zeros(len(func_ref), dtype = N.uint32)
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] dv = N.zeros(len(v), dtype = N.double)
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] v_ref = np.zeros(len(var_ref), dtype = np.uint32)
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] z_ref = np.zeros(len(func_ref), dtype = np.uint32)
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] dv = np.zeros(len(v), dtype = np.double)
#output array
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] dz = N.zeros(len(func_ref), dtype = N.double)
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] dz = np.zeros(len(func_ref), dtype = np.double)
if not self._provides_directional_derivatives():
raise FMUException('This FMU does not provide directional derivatives')
@@ -6870,20 +6823,20 @@ cdef class FMUModelBase2(ModelBase):
return dz
- cdef int _get_directional_derivative(self, N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode="c"] v_ref,
- N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode="c"] z_ref,
- N.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] dv,
- N.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] dz) except -1:
+ cdef int _get_directional_derivative(self, np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode="c"] v_ref,
+ np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode="c"] z_ref,
+ np.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] dv,
+ np.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] dz) except -1:
cdef int status
- assert N.size(dv) >= N.size(v_ref) and N.size(dz) >= N.size(z_ref)
+ assert np.size(dv) >= np.size(v_ref) and np.size(dz) >= np.size(z_ref)
if not self._provides_directional_derivatives():
raise FMUException('This FMU does not provide directional derivatives')
status = FMIL.fmi2_import_get_directional_derivative(self._fmu,
- v_ref.data, N.size(v_ref),
- z_ref.data, N.size(z_ref),
+ v_ref.data, np.size(v_ref),
+ z_ref.data, np.size(z_ref),
dv.data,
dz.data)
@@ -7194,11 +7147,11 @@ cdef class FMUModelCS2(FMUModelBase2):
"""
cdef int status
cdef unsigned int can_interpolate_inputs
- cdef N.ndarray[FMIL.fmi2_integer_t, ndim=1, mode='c'] orders
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] value_refs
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] val = N.array(values, dtype=float, ndmin=1).ravel()
- cdef FMIL.size_t nref = N.size(val)
- orders = N.array([0]*nref, dtype=N.int32)
+ cdef np.ndarray[FMIL.fmi2_integer_t, ndim=1, mode='c'] orders
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] value_refs
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] val = np.array(values, dtype=float, ndmin=1).ravel()
+ cdef FMIL.size_t nref = np.size(val)
+ orders = np.array([0]*nref, dtype=np.int32)
can_interpolate_inputs = FMIL.fmi2_import_get_capability(self._fmu, FMIL.fmi2_cs_canInterpolateInputs)
#NOTE IS THIS THE HIGHEST ORDER OF INTERPOLATION OR SIMPLY IF IT CAN OR NOT?
@@ -7209,10 +7162,10 @@ cdef class FMUModelCS2(FMUModelBase2):
raise FMUException("The FMU does not support input derivatives.")
if isinstance(variables,str):
- value_refs = N.array([0], dtype=N.uint32, ndmin=1).ravel()
+ value_refs = np.array([0], dtype=np.uint32, ndmin=1).ravel()
value_refs[0] = self.get_variable_valueref(variables)
- elif isinstance(variables,list) and N.prod([int(isinstance(v,str)) for v in variables]): #prod equals 0 or 1
- value_refs = N.array([0]*nref, dtype=N.uint32,ndmin=1).ravel()
+ elif isinstance(variables,list) and np.prod([int(isinstance(v,str)) for v in variables]): #prod equals 0 or 1
+ value_refs = np.array([0]*nref, dtype=np.uint32,ndmin=1).ravel()
for i in range(nref):
value_refs[i] = self.get_variable_valueref(variables[i])
orders[i] = order
@@ -7226,16 +7179,16 @@ cdef class FMUModelCS2(FMUModelBase2):
if status != 0:
raise FMUException('Failed to set the Real input derivatives.')
- cdef int _set_input_derivatives(self, N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode="c"] value_refs,
- N.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] values,
- N.ndarray[FMIL.fmi2_integer_t, ndim=1, mode="c"] orders):
+ cdef int _set_input_derivatives(self, np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode="c"] value_refs,
+ np.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] values,
+ np.ndarray[FMIL.fmi2_integer_t, ndim=1, mode="c"] orders):
cdef int status
- assert N.size(values) >= N.size(value_refs) and N.size(orders) >= N.size(value_refs)
+ assert np.size(values) >= np.size(value_refs) and np.size(orders) >= np.size(value_refs)
status = FMIL.fmi2_import_set_real_input_derivatives(self._fmu,
value_refs.data,
- N.size(value_refs), orders.data,
+ np.size(value_refs), orders.data,
values.data)
return status
@@ -7261,9 +7214,9 @@ cdef class FMUModelCS2(FMUModelBase2):
cdef int status
cdef unsigned int max_output_derivative
cdef FMIL.size_t nref
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] values
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] value_refs
- cdef N.ndarray[FMIL.fmi2_integer_t, ndim=1, mode='c'] orders
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] values
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] value_refs
+ cdef np.ndarray[FMIL.fmi2_integer_t, ndim=1, mode='c'] orders
max_output_derivative = FMIL.fmi2_import_get_capability(self._fmu, FMIL.fmi2_cs_maxOutputDerivativeOrder)
@@ -7272,20 +7225,20 @@ cdef class FMUModelCS2(FMUModelBase2):
if isinstance(variables,str):
nref = 1
- value_refs = N.array([0], dtype=N.uint32, ndmin=1).ravel()
- orders = N.array([order], dtype=N.int32)
+ value_refs = np.array([0], dtype=np.uint32, ndmin=1).ravel()
+ orders = np.array([order], dtype=np.int32)
value_refs[0] = self.get_variable_valueref(variables)
- elif isinstance(variables,list) and N.prod([int(isinstance(v,str)) for v in variables]): #prod equals 0 or 1
+ elif isinstance(variables,list) and np.prod([int(isinstance(v,str)) for v in variables]): #prod equals 0 or 1
nref = len(variables)
- value_refs = N.array([0]*nref, dtype=N.uint32, ndmin=1).ravel()
- orders = N.array([0]*nref, dtype=N.int32)
+ value_refs = np.array([0]*nref, dtype=np.uint32, ndmin=1).ravel()
+ orders = np.array([0]*nref, dtype=np.int32)
for i in range(nref):
value_refs[i] = self.get_variable_valueref(variables[i])
orders[i] = order
else:
raise FMUException("The variables must either be a string or a list of strings")
- values = N.array([0.0]*nref, dtype=float, ndmin=1)
+ values = np.array([0.0]*nref, dtype=float, ndmin=1)
#status = FMIL.fmi2_import_get_real_output_derivatives(self._fmu, value_refs.data, nref,
# orders.data, values.data)
@@ -7296,15 +7249,15 @@ cdef class FMUModelCS2(FMUModelBase2):
return values
- cdef int _get_output_derivatives(self, N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode="c"] value_refs,
- N.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] values,
- N.ndarray[FMIL.fmi2_integer_t, ndim=1, mode="c"] orders):
+ cdef int _get_output_derivatives(self, np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode="c"] value_refs,
+ np.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] values,
+ np.ndarray[FMIL.fmi2_integer_t, ndim=1, mode="c"] orders):
cdef int status
- assert N.size(values) >= N.size(value_refs) and N.size(orders) >= N.size(value_refs)
+ assert np.size(values) >= np.size(value_refs) and np.size(orders) >= np.size(value_refs)
status = FMIL.fmi2_import_get_real_output_derivatives(self._fmu,
- value_refs.data, N.size(value_refs),
+ value_refs.data, np.size(value_refs),
orders.data, values.data)
return status
@@ -7813,7 +7766,7 @@ cdef class FMUModelME2(FMUModelBase2):
cdef int _get_event_indicators(self, FMIL.fmi2_real_t[:] values):
#if not values.flags['C_CONTIGUOUS']:
- # values = N.ascontiguousarray(values)
+ # values = np.ascontiguousarray(values)
if self._nEventIndicators > 0:
return FMIL.fmi2_import_get_event_indicators(self._fmu, &values[0], self._nEventIndicators)
else:
@@ -7835,7 +7788,7 @@ cdef class FMUModelME2(FMUModelBase2):
Calls the low-level FMI function: fmiGetEventIndicators
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] values = N.empty(self._nEventIndicators, dtype=N.double)
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] values = np.empty(self._nEventIndicators, dtype=np.double)
status = self._get_event_indicators(values)
@@ -8009,7 +7962,7 @@ cdef class FMUModelME2(FMUModelBase2):
The continuous states.
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] ndx = N.zeros(self._nContinuousStates, dtype=N.double)
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] ndx = np.zeros(self._nContinuousStates, dtype=np.double)
status = self._get_continuous_states_fmil(ndx)
if status != 0:
@@ -8023,7 +7976,7 @@ cdef class FMUModelME2(FMUModelBase2):
else:
return FMIL.fmi2_status_ok
- def _set_continuous_states(self, N.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] values):
+ def _set_continuous_states(self, np.ndarray[FMIL.fmi2_real_t, ndim=1, mode="c"] values):
"""
Set the values of the continuous states.
@@ -8033,9 +7986,9 @@ cdef class FMUModelME2(FMUModelBase2):
The new values of the continuous states.
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1,mode='c'] ndx = values
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1,mode='c'] ndx = values
- if N.size(ndx) != self._nContinuousStates:
+ if np.size(ndx) != self._nContinuousStates:
raise FMUException(
'Failed to set the new continuous states. ' \
'The number of values are not consistent with the number of '\
@@ -8064,7 +8017,7 @@ cdef class FMUModelME2(FMUModelBase2):
The nominal values.
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] xn = N.zeros(self._nContinuousStates, dtype=N.double)
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] xn = np.zeros(self._nContinuousStates, dtype=np.double)
status = self._get_nominal_continuous_states_fmil( xn.data, self._nContinuousStates)
if status != 0:
@@ -8118,7 +8071,7 @@ cdef class FMUModelME2(FMUModelBase2):
Calls the low-level FMI function: fmi2GetDerivatives
"""
cdef int status
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] values = N.empty(self._nContinuousStates, dtype = N.double)
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] values = np.empty(self._nContinuousStates, dtype = np.double)
status = self._get_derivatives(values)
@@ -8283,9 +8236,9 @@ cdef class FMUModelME2(FMUModelBase2):
cdef double tmp_nominal, fac, tmp
cdef int method = FORWARD_DIFFERENCE if self.force_finite_differences is True or self.force_finite_differences == 0 else CENTRAL_DIFFERENCE
cdef double RUROUND = FORWARD_DIFFERENCE_EPS if method == FORWARD_DIFFERENCE else CENTRAL_DIFFERENCE_EPS
- cdef N.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] dfpert, df, eps, nominals
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] v_ref = N.array(var_ref, copy=False, dtype = N.uint32)
- cdef N.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] z_ref = N.array(func_ref, copy=False, dtype = N.uint32)
+ cdef np.ndarray[FMIL.fmi2_real_t, ndim=1, mode='c'] dfpert, df, eps, nominals
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] v_ref = np.array(var_ref, copy=False, dtype = np.uint32)
+ cdef np.ndarray[FMIL.fmi2_value_reference_t, ndim=1, mode='c'] z_ref = np.array(func_ref, copy=False, dtype = np.uint32)
cdef int ind_local = 5 if add_diag else 4
cdef list local_group
@@ -8330,11 +8283,11 @@ cdef class FMUModelME2(FMUModelBase2):
else: # First time extraction of nominals
#If we are using the states, then the nominals should instead be picked up from the C callback function for nominals
if self._states_references and len_v == len(self._states_references) and (self._states_references[i] == var_ref[i] for i in range(len_v)):
- group["nominals"] = N.array(self.nominal_continuous_states, dtype=float)
+ group["nominals"] = np.array(self.nominal_continuous_states, dtype=float)
nominals = group["nominals"]
nominals_pt = PyArray_DATA(nominals)
else:
- group["nominals"] = N.empty(len_v, dtype=float)
+ group["nominals"] = np.empty(len_v, dtype=float)
nominals = group["nominals"]
nominals_pt = PyArray_DATA(nominals)
for i in range(len_v):
@@ -8349,7 +8302,7 @@ cdef class FMUModelME2(FMUModelBase2):
if group is not None:
if output_matrix is not None:
- if not isinstance(output_matrix, sp.csc_matrix):
+ if not isinstance(output_matrix, sps.csc_matrix):
output_matrix = None
else:
output_matrix_data_pt = PyArray_DATA(output_matrix.data)
@@ -8442,23 +8395,23 @@ cdef class FMUModelME2(FMUModelBase2):
A = output_matrix
else:
if len(data) == 0:
- A = sp.csc_matrix((len_f,len_v))
+ A = sps.csc_matrix((len_f,len_v))
else:
- A = sp.csc_matrix((data, (row, col)), (len_f,len_v))
+ A = sps.csc_matrix((data, (row, col)), (len_f,len_v))
return A
else:
if output_matrix is None or \
- (not isinstance(output_matrix, N.ndarray)) or \
- (isinstance(output_matrix, N.ndarray) and (output_matrix.shape[0] != len_f or output_matrix.shape[1] != len_v)):
- A = N.zeros((len_f,len_v))
+ (not isinstance(output_matrix, np.ndarray)) or \
+ (isinstance(output_matrix, np.ndarray) and (output_matrix.shape[0] != len_f or output_matrix.shape[1] != len_v)):
+ A = np.zeros((len_f,len_v))
else:
A = output_matrix
if len_v == 0 or len_f == 0:
return A
- dfpert = N.zeros(len_f, dtype = N.double)
+ dfpert = np.zeros(len_f, dtype = np.double)
df = df[:len_f] #Should be removed in the future
for i in range(len_v):
tmp = v_pt[i]
@@ -8497,80 +8450,6 @@ cdef class FMUModelME2(FMUModelBase2):
return A
-cdef class _ForTestingFMUModelME2(FMUModelME2):
- cdef int _get_real_by_ptr(self, FMIL.fmi2_value_reference_t* vrefs, size_t size, FMIL.fmi2_real_t* values):
- vr = N.zeros(size)
- for i in range(size):
- vr[i] = vrefs[i]
-
- try:
- vv = self.get_real(vr)
- except Exception:
- return FMIL.fmi2_status_error
-
- for i in range(size):
- values[i] = vv[i]
-
- return FMIL.fmi2_status_ok
-
- cdef int _set_real(self, FMIL.fmi2_value_reference_t* vrefs, FMIL.fmi2_real_t* values, size_t size):
- vr = N.zeros(size)
- vv = N.zeros(size)
- for i in range(size):
- vr[i] = vrefs[i]
- vv[i] = values[i]
-
- try:
- self.set_real(vr, vv)
- except Exception:
- return FMIL.fmi2_status_error
-
- return FMIL.fmi2_status_ok
-
- cdef int _get_real_by_list(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_real_t[:] values):
- try:
- tmp = self.get_real(valueref)
- for i in range(size):
- values[i] = tmp[i]
- except Exception:
- return FMIL.fmi2_status_error
- return FMIL.fmi2_status_ok
-
- cdef int _get_integer(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_integer_t[:] values):
- try:
- tmp = self.get_integer(valueref)
- for i in range(size):
- values[i] = tmp[i]
- except Exception:
- return FMIL.fmi2_status_error
- return FMIL.fmi2_status_ok
-
- cdef int _get_boolean(self, FMIL.fmi2_value_reference_t[:] valueref, size_t size, FMIL.fmi2_real_t[:] values):
- try:
- tmp = self.get_boolean(valueref)
- for i in range(size):
- values[i] = tmp[i]
- except Exception:
- return FMIL.fmi2_status_error
- return FMIL.fmi2_status_ok
-
- cdef int _get_nominal_continuous_states_fmil(self, FMIL.fmi2_real_t* xnominal, size_t nx):
- for i in range(nx):
- if self._initialized_fmu == 1:
- # Set new values to test that atol gets auto-corrected.
- xnominal[i] = 3.0
- else:
- # Set some illegal values in order to test the fallback/auto-correction.
- xnominal[i] = ((( i) % 3) - 1) * 2.0 # -2.0, 0.0, 2.0,
- return FMIL.fmi2_status_ok
-
- cpdef set_initialized_fmu(self, int value):
- self._initialized_fmu = value
-
- def __dealloc__(self):
- # Avoid segfaults in dealloc. The FMU binaries should never be loaded for this
- # test class, so we should never try to terminate or deallocate the FMU instance.
- self._initialized_fmu = 0
def _handle_load_fmu_exception(fmu, log_data):
for log in log_data:
@@ -8856,22 +8735,22 @@ cdef class WorkerClass2:
self._dim = 0
def _update_work_vectors(self, dim):
- self._tmp1_val = N.zeros(dim, dtype = N.double)
- self._tmp2_val = N.zeros(dim, dtype = N.double)
- self._tmp3_val = N.zeros(dim, dtype = N.double)
- self._tmp4_val = N.zeros(dim, dtype = N.double)
+ self._tmp1_val = np.zeros(dim, dtype = np.double)
+ self._tmp2_val = np.zeros(dim, dtype = np.double)
+ self._tmp3_val = np.zeros(dim, dtype = np.double)
+ self._tmp4_val = np.zeros(dim, dtype = np.double)
- self._tmp1_ref = N.zeros(dim, dtype = N.uint32)
- self._tmp2_ref = N.zeros(dim, dtype = N.uint32)
- self._tmp3_ref = N.zeros(dim, dtype = N.uint32)
- self._tmp4_ref = N.zeros(dim, dtype = N.uint32)
+ self._tmp1_ref = np.zeros(dim, dtype = np.uint32)
+ self._tmp2_ref = np.zeros(dim, dtype = np.uint32)
+ self._tmp3_ref = np.zeros(dim, dtype = np.uint32)
+ self._tmp4_ref = np.zeros(dim, dtype = np.uint32)
cpdef verify_dimensions(self, int dim):
if dim > self._dim:
self._update_work_vectors(dim)
- cdef N.ndarray get_real_numpy_vector(self, int index):
- cdef N.ndarray ret = None
+ cdef np.ndarray get_real_numpy_vector(self, int index):
+ cdef np.ndarray ret = None
if index == 0:
ret = self._tmp1_val
@@ -8897,8 +8776,8 @@ cdef class WorkerClass2:
return ret
- cdef N.ndarray get_value_reference_numpy_vector(self, int index):
- cdef N.ndarray ret = None
+ cdef np.ndarray get_value_reference_numpy_vector(self, int index):
+ cdef np.ndarray ret = None
if index == 0:
ret = self._tmp1_ref
diff --git a/src/pyfmi/fmi_algorithm_drivers.py b/src/pyfmi/fmi_algorithm_drivers.py
index d68065ab..1f0f4869 100644
--- a/src/pyfmi/fmi_algorithm_drivers.py
+++ b/src/pyfmi/fmi_algorithm_drivers.py
@@ -19,10 +19,10 @@
pyfmi.fmi.FMUModel*.simulate.
"""
-#from abc import ABCMeta, abstractmethod
import logging as logging_module
import time
-import numpy as N
+import numpy as np
+import scipy.optimize as spopt
import pyfmi.fmi as fmi
import pyfmi.fmi_coupled as fmi_coupled
@@ -36,8 +36,8 @@
from timeit import default_timer as timer
default_int = int
-int = N.int32
-N.int = N.int32
+int = np.int32
+np.int = np.int32
PYFMI_JACOBIAN_LIMIT = 10
PYFMI_JACOBIAN_SPARSE_SIZE_LIMIT = 100
@@ -584,10 +584,10 @@ def _set_options(self):
self.solver_options['rtol'] = rtol
#rtol was provided as a vector
- if isinstance(self.solver_options["rtol"], N.ndarray) or isinstance(self.solver_options["rtol"], list):
+ if isinstance(self.solver_options["rtol"], np.ndarray) or isinstance(self.solver_options["rtol"], list):
#rtol all are all equal -> set it as scalar and use that
- if N.all(N.isclose(self.solver_options["rtol"], self.solver_options["rtol"][0])):
+ if np.all(np.isclose(self.solver_options["rtol"], self.solver_options["rtol"][0])):
self.solver_options["rtol"] = self.solver_options["rtol"][0]
self.rtol = self.solver_options["rtol"]
@@ -640,7 +640,7 @@ def _set_options(self):
except KeyError:
#Need to calculate the nnz.
[derv_state_dep, derv_input_dep] = self.model.get_derivatives_dependencies()
- nnz = N.sum([len(derv_state_dep[key]) for key in derv_state_dep.keys()])+fnbr
+ nnz = np.sum([len(derv_state_dep[key]) for key in derv_state_dep.keys()])+fnbr
if nnz/float(fnbr*fnbr) <= PYFMI_JACOBIAN_SPARSE_NNZ_LIMIT:
self.solver_options["linear_solver"] = "SPARSE"
else:
@@ -666,7 +666,7 @@ def _set_absolute_tolerance_options(self):
self.solver_options["atol"] = 0.01*self.rtol
else:
self.solver_options["atol"] = 0.01*self.rtol*self.model.nominal_continuous_states
- elif isinstance(preinit_nominals, N.ndarray) and (N.size(preinit_nominals) > 0):
+ elif isinstance(preinit_nominals, np.ndarray) and (np.size(preinit_nominals) > 0):
# Heuristic:
# Try to find if atol was specified as "atol = factor * model.nominal_continuous_states",
# and if that's the case, recompute atol with nominals from after initialization.
@@ -713,7 +713,7 @@ def _set_solver_options(self):
solver_options["maxh"] = float(self.final_time - self.start_time) / float(self.options["ncp"])
if "rtol" in solver_options:
- rtol_is_vector = (isinstance(self.solver_options["rtol"], N.ndarray) or isinstance(self.solver_options["rtol"], list))
+ rtol_is_vector = (isinstance(self.solver_options["rtol"], np.ndarray) or isinstance(self.solver_options["rtol"], list))
rtol_vector_support = self.simulator.supports.get("rtol_as_vector", False)
if rtol_is_vector and not rtol_vector_support and self._rtol_as_scalar_fallback:
@@ -1095,7 +1095,7 @@ def solve(self):
"""
result_handler = self.result_handler
h = (self.final_time-self.start_time)/self.ncp
- grid = N.linspace(self.start_time,self.final_time,self.ncp+1)[:-1]
+ grid = np.linspace(self.start_time,self.final_time,self.ncp+1)[:-1]
status = 0
final_time = self.start_time
@@ -1277,7 +1277,7 @@ def _set_options(self):
scale = []
for parameter in self.parameters:
scale.append(self.model.get_variable_nominal(parameter))
- self.options["scaling"] = N.array(scale)
+ self.options["scaling"] = np.array(scale)
if self.options["simulate_options"] == "Default":
self.options["simulate_options"] = self.model.simulate_options()
@@ -1302,8 +1302,6 @@ def solve(self):
"""
Runs the estimation.
"""
- import scipy as sci
- import scipy.optimize as sciopt
from pyfmi.fmi_util import parameter_estimation_f
#Define callback
@@ -1323,13 +1321,13 @@ def parameter_estimation_callback(y):
p0 = []
for i,parameter in enumerate(self.parameters):
p0.append(self.model.get(parameter)/self.options["scaling"][i])
- p0 = N.array(p0).flatten()
+ p0 = np.array(p0).flatten()
print('\nRunning solver: ' + self.options["method"])
print(' Initial parameters (scaled): ' + str(p0))
print(' ')
- res = sciopt.minimize(parameter_estimation_f, p0,
+ res = spopt.minimize(parameter_estimation_f, p0,
args=(self.parameters, self.measurements, self.model, self.input, self.options),
method=self.options["method"],
bounds=None,
diff --git a/src/pyfmi/fmi_coupled.pyx b/src/pyfmi/fmi_coupled.pyx
index debfb55f..c821917b 100644
--- a/src/pyfmi/fmi_coupled.pyx
+++ b/src/pyfmi/fmi_coupled.pyx
@@ -17,25 +17,18 @@
# distutils: define_macros=NPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION
+import time
+import numpy as np
+cimport numpy as np
+
import pyfmi.fmi as fmi
from pyfmi.fmi cimport FMUModelME2
cimport fmil_import as FMIL
-from pyfmi.fmi_util import cpr_seed, enable_caching, Graph
+from pyfmi.fmi_util import enable_caching, Graph
from collections import OrderedDict
-import time
-import warnings
-import numpy as np
-cimport numpy as np
-import scipy.optimize as sopt
-import scipy
-
-try:
- from numpy.lib import NumpyVersion
- USE_ROOT = NumpyVersion(scipy.version.version) >= "0.11.0"
-except ImportError: #Numpy version is < 1.9.0 so assume scipy version is the same
- USE_ROOT = False
+import scipy.optimize as spopt
def init_f_block(u, coupled, block):
@@ -1986,12 +1979,8 @@ cdef class CoupledFMUModelME2(CoupledFMUModelBase):
u = np.array(u).ravel()
success = False
- if USE_ROOT:
- res = sopt.root(init_f_block, u, args=(self,block))
- success = res["success"]
- else:
- [res, info, ier, msg] = sopt.fsolve(init_f_block, u, args=(self,block), full_output=True)
- success = True if ier == 1 else False
+ res = spopt.root(init_f_block, u, args=(self,block))
+ success = res["success"]
if not success:
raise fmi.FMUException("Failed to converge the block.")
@@ -2000,10 +1989,7 @@ cdef class CoupledFMUModelME2(CoupledFMUModelBase):
for model in block["outputs"].keys():
self.get_specific_connection_outputs(model, block["outputs_mask"][model], y)
- if USE_ROOT:
- res = sopt.root(init_f_block, y[block["global_outputs_mask"]], args=(self,block))
- else:
- res = sopt.fsolve(init_f_block, y[block["global_outputs_mask"]], args=(self,block))
+ res = spopt.root(init_f_block, y[block["global_outputs_mask"]], args=(self,block))
if not res["success"]:
print res
raise Exception("Failed to converge the initialization system.")
diff --git a/src/pyfmi/fmi_extended.pyx b/src/pyfmi/fmi_extended.pyx
index 01ee7045..894e5693 100644
--- a/src/pyfmi/fmi_extended.pyx
+++ b/src/pyfmi/fmi_extended.pyx
@@ -20,22 +20,15 @@
"""
Module containing the FMI interface Python wrappers.
"""
-import os
-import sys
-import logging
-import fnmatch
-import re
-from collections import OrderedDict
-
-import numpy as N
-cimport numpy as N
-N.import_array()
+import logging
+import numpy as np
+cimport numpy as np
cimport fmil_import as FMIL
from pyfmi.fmi cimport FMUModelME1
from pyfmi.fmi import FMUException
-from pyfmi.fmi import FMI_OK, FMI_DEFAULT_LOG_LEVEL, FMI_ME
+from pyfmi.fmi import FMI_OK, FMI_DEFAULT_LOG_LEVEL
cdef class FMUModelME1Extended(FMUModelME1):
@@ -45,7 +38,7 @@ cdef class FMUModelME1Extended(FMUModelME1):
cdef public list _input_value_refs, _input_alias_type, _input_factorials
cdef public int _input_active, _input_order
cdef public dict _input_derivatives, _options
- cdef public N.ndarray _input_tmp
+ cdef public np.ndarray _input_tmp
def __init__(self, fmu, log_file_name="", log_level=FMI_DEFAULT_LOG_LEVEL, _connect_dll=True):
#Instantiate the FMU
@@ -59,7 +52,7 @@ cdef class FMUModelME1Extended(FMUModelME1):
for name in vars.keys():
input_value_refs.append(self.get_variable_valueref(name))
input_alias_type.append(-1.0 if self.get_variable_alias(name)[name] == -1 else 1.0)
- assert not N.any(input_alias_type == -1)
+ assert not np.any(input_alias_type == -1)
self._input_derivatives = {}
for val_ref in input_value_refs:
@@ -104,7 +97,7 @@ cdef class FMUModelME1Extended(FMUModelME1):
cdef void _eval_input(self, double time):
cdef int i,j
- cdef N.ndarray input_tmp = self._input_tmp.copy()
+ cdef np.ndarray input_tmp = self._input_tmp.copy()
for i,ref in enumerate(self._input_value_refs):
for j in range(self._input_order):
@@ -133,7 +126,7 @@ cdef class FMUModelME1Extended(FMUModelME1):
Calls the low-level FMI function: fmiGetDerivatives
"""
cdef int status
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] values = N.empty(self._nContinuousStates,dtype=N.double)
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] values = np.empty(self._nContinuousStates,dtype=np.double)
if self._input_active:
self._eval_input(self.time)
@@ -288,12 +281,12 @@ cdef class FMUModelME1Extended(FMUModelME1):
"""
cdef int status
cdef FMIL.size_t nref
- cdef N.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] np_orders = N.array(orders, dtype=N.int32, ndmin=1).flatten()
- cdef N.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] value_refs
- cdef N.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] val = N.array(values, dtype=float, ndmin=1).flatten()
+ cdef np.ndarray[FMIL.fmi1_integer_t, ndim=1,mode='c'] np_orders = np.array(orders, dtype=np.int32, ndmin=1).flatten()
+ cdef np.ndarray[FMIL.fmi1_value_reference_t, ndim=1,mode='c'] value_refs
+ cdef np.ndarray[FMIL.fmi1_real_t, ndim=1,mode='c'] val = np.array(values, dtype=float, ndmin=1).flatten()
nref = len(val)
- orders = N.array([0]*nref, dtype=N.int32)
+ orders = np.array([0]*nref, dtype=np.int32)
if nref != len(np_orders):
raise FMUException("The number of variables must be the same as the number of orders.")
@@ -305,10 +298,10 @@ cdef class FMUModelME1Extended(FMUModelME1):
self._input_order = np_orders[i]
if isinstance(variables,str):
- value_refs = N.array([0], dtype=N.uint32,ndmin=1).flatten()
+ value_refs = np.array([0], dtype=np.uint32,ndmin=1).flatten()
value_refs[0] = self.get_variable_valueref(variables)
elif isinstance(variables,list) and isinstance(variables[-1],str):
- value_refs = N.array([0]*nref, dtype=N.uint32,ndmin=1).flatten()
+ value_refs = np.array([0]*nref, dtype=np.uint32,ndmin=1).flatten()
for i in range(nref):
value_refs[i] = self.get_variable_valueref(variables[i])
else:
diff --git a/src/pyfmi/fmi_util.pyx b/src/pyfmi/fmi_util.pyx
index e126eb57..deae039b 100644
--- a/src/pyfmi/fmi_util.pyx
+++ b/src/pyfmi/fmi_util.pyx
@@ -21,44 +21,29 @@
Module containing the FMI interface Python wrappers.
"""
import collections
-from collections import OrderedDict
import itertools
-from operator import attrgetter
-import numpy as np
-from numpy.compat import asbytes
-
-from pyfmi.common import encode
+import numpy as np
cimport numpy as np
-cimport fmil_import as FMIL
-from cpython cimport array
-from pyfmi.fmi cimport FMUModelME2, FMUModelBase
+cimport fmil_import as FMIL
+from pyfmi.fmi cimport FMUModelME2
import functools
import marshal
import pyfmi.fmi as fmi
-import sys
-
-python3_flag = True if sys.hexversion > 0x03000000 else False
cpdef decode(x):
- if python3_flag:
- if isinstance(x, bytes):
- return x.decode(errors="replace")
- else:
- return x
+ if isinstance(x, bytes):
+ return x.decode(errors="replace")
else:
return x
cpdef encode(x):
- if python3_flag:
- if isinstance(x, str):
- return x.encode()
- else:
- return x
+ if isinstance(x, str):
+ return x.encode()
else:
- return x.encode("utf-8")
+ return x
def enable_caching(obj):
@functools.wraps(obj, ('__name__', '__doc__'))
@@ -97,10 +82,7 @@ cpdef cpr_seed(dependencies, list column_keys, dict interested_columns = None):
data_index = {}
data_index_with_diag = {}
for i in range(n_col):
- if python3_flag:
- data_index[i] = list(range(k, k + len(column_dict[i])))
- else:
- data_index[i] = range(k, k + len(column_dict[i]))
+ data_index[i] = list(range(k, k + len(column_dict[i])))
k = k + len(column_dict[i])
data_index_with_diag[i] = []
@@ -224,17 +206,11 @@ cpdef list convert_array_names_list_names(np.ndarray names):
cpdef list convert_array_names_list_names_int(np.ndarray[int, ndim=2] names):
cdef int max_length = names.shape[0]
cdef int nbr_items = names.shape[1]
- cdef int i, py3, j = 0, ch
+ cdef int i, j = 0, ch
cdef char *tmp = FMIL.calloc(max_length,sizeof(char))
cdef list output = []
cdef bytes py_str
- # This if-statement is contributes to a performance gain within the for-loop that follows
- if python3_flag:
- py3 = 1
- else:
- py3 = 0
-
for i in range(nbr_items):
for j in range(max_length):
ch = names[j,i]
@@ -245,10 +221,7 @@ cpdef list convert_array_names_list_names_int(np.ndarray[int, ndim=2] names):
py_str = tmp[:j]
if j == max_length - 1:
- if py3:
- py_str = py_str.replace(b" ", b"")
- else:
- py_str = py_str.replace(" ", "")
+ py_str = py_str.replace(b" ", b"")
output.append(py_str)
FMIL.free(tmp)
@@ -667,7 +640,7 @@ class Graph:
if self.graph_info[node]["type"] == GRAPH_OUTPUT:
model = self.graph_info[node]["model"]
if not (model in trees):
- trees[model] = OrderedDict()
+ trees[model] = collections.OrderedDict()
trees[model][node] = self.dfs(node)
joined_nodes[node] = [node]
else:
@@ -1029,14 +1002,14 @@ class Graph:
cdef class DumpData:
def __init__(self, model, filep, real_var_ref, int_var_ref, bool_var_ref, with_diagnostics):
- if type(model) != FMUModelME2:
- self.real_var_ref = np.array(real_var_ref, ndmin=1).ravel()
- self.int_var_ref = np.array(int_var_ref, ndmin=1).ravel()
- self.bool_var_ref = np.array(bool_var_ref, ndmin=1).ravel()
- else:
+ if type(model) == FMUModelME2:
self.real_var_ref = np.array(real_var_ref, dtype=np.uint32, ndmin=1).ravel()
self.int_var_ref = np.array(int_var_ref, dtype=np.uint32, ndmin=1).ravel()
self.bool_var_ref = np.array(bool_var_ref, dtype=np.uint32, ndmin=1).ravel()
+ else:
+ self.real_var_ref = np.array(real_var_ref, ndmin=1).ravel()
+ self.int_var_ref = np.array(int_var_ref, ndmin=1).ravel()
+ self.bool_var_ref = np.array(bool_var_ref, ndmin=1).ravel()
self.real_size = np.size(self.real_var_ref)
self.int_size = np.size(self.int_var_ref)
@@ -1065,7 +1038,7 @@ cdef class DumpData:
if self._with_diagnostics:
self.dump_data(np.array(float(1.0)))
if self.model_me2_instance:
- self.time_tmp[0] = self.model_me2._get_time()
+ self.time_tmp[0] = self.model_me2.time
self.dump_data(self.time_tmp)
if self.real_size > 0:
@@ -1099,7 +1072,7 @@ cdef class DumpData:
""" Saves a point of diagnostics data to the result. """
self.dump_data(np.array(float(2.0)))
if self.model_me2_instance:
- self.time_tmp[0] = self.model_me2._get_time()
+ self.time_tmp[0] = self.model_me2.time
self.dump_data(self.time_tmp)
else:
self.dump_data(np.array(float(self.model.time)))
@@ -1330,17 +1303,12 @@ def read_name_list(file_name, int file_position, int nbr_variables, int max_leng
A dict with the names as key and an index as value
"""
- cdef int i = 0, j = 0, py3, need_replace = 0
+ cdef int i = 0, j = 0, need_replace = 0
cdef FILE* cfile
cdef char *tmp = FMIL.calloc(max_length,sizeof(char))
cdef bytes py_str
cdef dict data = {}
- # This if-statement contributes to a performance gain within the for-loop that follows
- if python3_flag:
- py3 = 1
- else:
- py3 = 0
if tmp == NULL:
raise fmi.IOException("Couldn't allocate memory to read name list.")
@@ -1355,10 +1323,7 @@ def read_name_list(file_name, int file_position, int nbr_variables, int max_leng
need_replace = 1
if need_replace:
- if py3:
- py_str = py_str.replace(b" ", b"")
- else:
- py_str = py_str.replace(" ", "")
+ py_str = py_str.replace(b" ", b"")
data[py_str] = i
fclose(cfile)
diff --git a/src/pyfmi/master.pyx b/src/pyfmi/master.pyx
index 4d0a9a89..29e205d8 100644
--- a/src/pyfmi/master.pyx
+++ b/src/pyfmi/master.pyx
@@ -17,33 +17,28 @@
# distutils: define_macros=NPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION
-import pyfmi.fmi as fmi
-from pyfmi.common.algorithm_drivers import OptionBase, InvalidAlgorithmOptionException, AssimuloSimResult
-from pyfmi.common.io import ResultDymolaTextual, ResultHandlerFile, ResultHandlerDummy, ResultHandlerBinaryFile, ResultDymolaBinary
-from pyfmi.common.core import TrajectoryLinearInterpolation
-from pyfmi.common.core import TrajectoryUserFunction
-
-from timeit import default_timer as timer
-
import fnmatch
import sys
-import re
-from collections import OrderedDict
import time
-import numpy as np
import warnings
+from collections import OrderedDict
+from timeit import default_timer as timer
+from cpython cimport bool
+from cython.parallel import prange, parallel
+
+import numpy as np
cimport numpy as np
-import scipy.sparse as sp
-import scipy.linalg as lin
-import scipy.sparse.linalg as splin
-import scipy.optimize as sopt
-import scipy.version
+import scipy as sp
+import scipy.sparse as sps
+import scipy.optimize as spopt
+import pyfmi.fmi as fmi
+from pyfmi.common.algorithm_drivers import OptionBase, InvalidAlgorithmOptionException, AssimuloSimResult
+from pyfmi.common.io import ResultHandlerFile, ResultHandlerDummy, ResultHandlerBinaryFile
+from pyfmi.common.core import TrajectoryLinearInterpolation, TrajectoryUserFunction
from pyfmi.fmi cimport FMUModelCS2
-from cpython cimport bool
cimport fmil_import as FMIL
from pyfmi.fmi_util import Graph
-from cython.parallel import prange, parallel
IF WITH_OPENMP:
cimport openmp
@@ -51,12 +46,6 @@ IF WITH_OPENMP:
DEF SERIAL = 0
DEF PARALLEL = 1
-try:
- from numpy.lib import NumpyVersion
- USE_ROOT = NumpyVersion(scipy.version.version) >= "0.11.0"
-except ImportError: #Numpy version is < 1.9.0 so assume scipy version is the same
- USE_ROOT = False
-
cdef reset_models(list models):
for model in models:
model.reset()
@@ -469,7 +458,7 @@ cdef class Master:
self.y_prev = None
self.input_traj = None
- self._ident_matrix = sp.eye(self._len_inputs, self._len_outputs, format="csr") #y = Cx + Du , u = Ly -> DLy DL[inputsXoutputs]
+ self._ident_matrix = sps.eye(self._len_inputs, self._len_outputs, format="csr") #y = Cx + Du , u = Ly -> DLy DL[inputsXoutputs]
self._error_data = {"time":[], "error":[], "step-size":[], "rejected":[]}
@@ -568,8 +557,8 @@ cdef class Master:
col_discrete.append(self.models_dict[src]["global_index_outputs_discrete"]+self.models_dict[src]["local_output_discrete"].index(src_var))
len_connections_discrete = len_connections_discrete + 1
- self.L = sp.csr_matrix((data, (row, col)), (len_connections,len_connections), dtype=np.float64)
- self.L_discrete = sp.csr_matrix((data_discrete, (row_discrete, col_discrete)), (len_connections_discrete,len_connections_discrete), dtype=np.float64)
+ self.L = sps.csr_matrix((data, (row, col)), (len_connections,len_connections), dtype=np.float64)
+ self.L_discrete = sps.csr_matrix((data_discrete, (row_discrete, col_discrete)), (len_connections_discrete,len_connections_discrete), dtype=np.float64)
cpdef compute_global_D(self):
cdef list data = []
@@ -610,7 +599,7 @@ cdef class Master:
col = self._storedDcol
if self._D is None:
- self._D = sp.csr_matrix((data, (row, col)))#, (len(col),len(row)))
+ self._D = sps.csr_matrix((data, (row, col)))#, (len(col),len(row)))
else:
self._D.data = np.array(data, dtype=np.float64)
@@ -631,7 +620,7 @@ cdef class Master:
data.extend(local_C)
col.extend([self.models_dict[model]["global_index_states"]+i]*len(local_C))
row.extend(np.array([self.models_dict[model]["global_index_outputs"]]*len(self.models_dict[model]["local_output_vref"]))+np.array(range(len(self.models_dict[model]["local_output_vref"]))))
- return sp.csr_matrix((data, (row, col)))
+ return sps.csr_matrix((data, (row, col)))
def compute_global_A(self):
cdef list data = []
@@ -647,7 +636,7 @@ cdef class Master:
data.extend(local_A)
col.extend([self.models_dict[model]["global_index_states"]+i]*len(local_A))
row.extend(np.array([self.models_dict[model]["global_index_derivatives"]]*len(self.models_dict[model]["local_derivative_vref"]))+np.array(range(len(self.models_dict[model]["local_derivative_vref"]))))
- return sp.csr_matrix((data, (row, col)))
+ return sps.csr_matrix((data, (row, col)))
def compute_global_B(self):
cdef list data = []
@@ -663,7 +652,7 @@ cdef class Master:
data.extend(local_B)
col.extend([self.models_dict[model]["global_index_inputs"]+i]*len(local_B))
row.extend(np.array([self.models_dict[model]["global_index_derivatives"]]*len(self.models_dict[model]["local_derivative_vref"]))+np.array(range(len(self.models_dict[model]["local_derivative_vref"]))))
- return sp.csr_matrix((data, (row, col)))
+ return sps.csr_matrix((data, (row, col)))
def connection_setup(self, connections):
for connection in connections:
@@ -854,7 +843,7 @@ cdef class Master:
else:
return C.dot(xd)+D.dot(ud)
else: #First step
- return splin.spsolve((self._ident_matrix-D.dot(self.L)),C.dot(xd)).reshape((-1,1))
+ return sps.linalg.spsolve((self._ident_matrix-D.dot(self.L)),C.dot(xd)).reshape((-1,1))
y_last = self.get_last_y()
if y_last is not None:
@@ -899,7 +888,7 @@ cdef class Master:
if ud is not None and udd is not None:
return C.dot(A.dot(xd))+C.dot(B.dot(ud+self.get_current_step_size()*udd))+D.dot(udd)
else: #First step
- return splin.spsolve((self._ident_matrix-D.dot(self.L)),C.dot(A.dot(xd)+B.dot(self.L.dot(yd_cur)))).reshape((-1,1))
+ return sps.linalg.spsolve((self._ident_matrix-D.dot(self.L)),C.dot(A.dot(xd)+B.dot(self.L.dot(yd_cur)))).reshape((-1,1))
yd_last = self.get_last_yd()
if yd_last is not None:
@@ -966,7 +955,7 @@ cdef class Master:
z = yd - D.dot(uhat)
- yd = splin.spsolve((self._ident_matrix-DL),z).reshape((-1,1))
+ yd = sps.linalg.spsolve((self._ident_matrix-DL),z).reshape((-1,1))
"""
return ydd
@@ -981,7 +970,7 @@ cdef class Master:
z = yd - D.dot(uhat)
- yd = splin.spsolve((self._ident_matrix-DL),z).reshape((-1,1))
+ yd = sps.linalg.spsolve((self._ident_matrix-DL),z).reshape((-1,1))
return yd
@@ -993,10 +982,7 @@ cdef class Master:
JM_FMUS = False
break
if JM_FMUS:
- if USE_ROOT:
- res = sopt.root(init_f, y, args=(self))
- else:
- res = sopt.fsolve(init_f, y, args=(self))
+ res = spopt.root(init_f, y, args=(self))
if not res["success"]:
print(res)
raise fmi.FMUException("Failed to converge the output system.")
@@ -1009,16 +995,11 @@ cdef class Master:
if self.opts["extrapolation_order"] > 0:
uold, udold, uddold = self.get_last_us()
uhat = uold + (self.get_current_step_size()*udold if udold is not None else 0.0)
-
z = y - D.dot(uhat)
- #z = y - matvec(D,uhat.ravel())
else:
-
z = y - DL.dot(y_prev)
- #z = y - matvec(DL, y_prev.ravel())
- y = splin.spsolve((self._ident_matrix-DL),z).reshape((-1,1))
- #y = splin.lsqr((sp.eye(*DL.shape)-DL),z)[0].reshape((-1,1))
+ y = sps.linalg.spsolve((self._ident_matrix-DL),z).reshape((-1,1))
elif self.algebraic_loops and self.support_directional_derivatives:
pass
@@ -1125,10 +1106,7 @@ cdef class Master:
for model in block["outputs"].keys():
self.get_specific_connection_outputs(model, block["outputs_mask"][model], y)
- if USE_ROOT:
- res = sopt.root(init_f_block, y[block["global_outputs_mask"]], args=(self,block))
- else:
- res = sopt.fsolve(init_f_block, y[block["global_outputs_mask"]], args=(self,block))
+ res = spopt.root(init_f_block, y[block["global_outputs_mask"]], args=(self,block))
if not res["success"]:
print(res)
raise fmi.FMUException("Failed to converge the initialization system.")
@@ -1150,15 +1128,9 @@ cdef class Master:
if self.algebraic_loops: #If there is an algebraic loop, solve the resulting system
if self.support_directional_derivatives:
- if USE_ROOT:
- res = sopt.root(init_f, self.get_connection_outputs(), args=(self), jac=init_jac)
- else:
- res = sopt.fsolve(init_f, self.get_connection_outputs(), args=(self), jac=init_jac)
+ res = spopt.root(init_f, self.get_connection_outputs(), args=(self), jac=init_jac)
else:
- if USE_ROOT:
- res = sopt.root(init_f, self.get_connection_outputs(), args=(self))
- else:
- res = sopt.fsolve(init_f, self.get_connection_outputs(), args=(self))
+ res = spopt.root(init_f, self.get_connection_outputs(), args=(self))
if not res["success"]:
print(res)
raise fmi.FMUException("Failed to converge the initialization system.")
@@ -1334,27 +1306,25 @@ cdef class Master:
if opts["logging"]:
D = self.compute_global_D()
DL = D.dot(self.L)
- import numpy.linalg
- import scipy.linalg as slin
- print("At time: %E , rho(DL)=%s"%(tcur + step_size, str(numpy.linalg.eig(DL.todense())[0])))
+ print("At time: %E , rho(DL)=%s"%(tcur + step_size, str(np.linalg.eig(DL.todense())[0])))
C = self.compute_global_C()
if C is not None:
C = C.todense()
_ident_matrix = np.eye(*DL.shape)
- LIDLC = self.L.dot(lin.solve(_ident_matrix-DL,C))
- print(" , rho(L(I-DL)^(-1)C)=%s"%(str(numpy.linalg.eig(LIDLC)[0])))
+ LIDLC = self.L.dot(np.linalg.solve(_ident_matrix-DL,C))
+ print(" , rho(L(I-DL)^(-1)C)=%s"%(str(np.linalg.eig(LIDLC)[0])))
A = self.compute_global_A()
B = self.compute_global_B()
if C is not None and A is not None and B is not None:
A = A.todense(); B = B.todense()
- eAH = slin.expm(A*step_size)
- K1 = lin.solve(_ident_matrix-DL,C)
- K2 = lin.solve(A,(eAH-np.eye(*eAH.shape)).dot(B.dot(self.L.todense())))
+ eAH = sp.linalg.expm(A*step_size)
+ K1 = np.linalg.solve(_ident_matrix-DL,C)
+ K2 = np.linalg.solve(A,(eAH-np.eye(*eAH.shape)).dot(B.dot(self.L.todense())))
R1 = np.hstack((eAH, K1))
R2 = np.hstack((K2.dot(eAH), K2.dot(K1)))
G = np.vstack((R1,R2))
G1 = K2.dot(K1)
- print(" , rho(G)=%s"%(str(numpy.linalg.eig(G1)[0])))
+ print(" , rho(G)=%s"%(str(np.linalg.eig(G1)[0])))
def specify_external_input(self, input):
diff --git a/src/pyfmi/simulation/assimulo_interface.pxd b/src/pyfmi/simulation/assimulo_interface.pxd
index 91f7c0d6..531615e7 100644
--- a/src/pyfmi/simulation/assimulo_interface.pxd
+++ b/src/pyfmi/simulation/assimulo_interface.pxd
@@ -16,8 +16,8 @@
# along with this program. If not, see .
-import numpy as N
-cimport numpy as N
+import numpy as np
+cimport numpy as np
import logging
from pyfmi.fmi cimport FMUModelME2
@@ -49,16 +49,16 @@ cdef class FMIODE2(cExplicit_Problem):
cdef public object _model, problem_name, result_file_name, __input, _A, debug_file_name, debug_file_object
cdef public object export, _sparse_representation, _with_jacobian, _logging, _write_header, _start_time
cdef public dict timings
- cdef public N.ndarray y0, input_real_mask, input_other_mask
+ cdef public np.ndarray y0, input_real_mask, input_other_mask
cdef public list input_names, input_real_value_refs, input_other, _logg_step_event
cdef public double t0, _synchronize_factor
cdef public jac_use, state_events_use, time_events_use
cdef public FMUModelME2 model_me2
cdef public int model_me2_instance
- cdef public N.ndarray _state_temp_1, _event_temp_1
+ cdef public np.ndarray _state_temp_1, _event_temp_1
cdef int _logging_as_dynamic_diagnostics
cdef int _number_of_diagnostics_variables
cpdef _set_input_values(self, double t)
- cdef _update_model(self, double t, N.ndarray[double, ndim=1, mode="c"] y)
- cdef int _compare(self, double t, N.ndarray[double, ndim=1, mode="c"] y)
+ cdef _update_model(self, double t, np.ndarray[double, ndim=1, mode="c"] y)
+ cdef int _compare(self, double t, np.ndarray[double, ndim=1, mode="c"] y)
diff --git a/src/pyfmi/simulation/assimulo_interface.pyx b/src/pyfmi/simulation/assimulo_interface.pyx
index 62d82610..db7debea 100644
--- a/src/pyfmi/simulation/assimulo_interface.pyx
+++ b/src/pyfmi/simulation/assimulo_interface.pyx
@@ -24,24 +24,17 @@ required by Assimulo.
import logging as logging_module
from operator import index
-import numpy as N
-from numpy.core.einsumfunc import einsum
-
-from pyfmi.fmi import FMUException
-
-cimport numpy as N
-import numpy.linalg as LIN
-import scipy.sparse as sp
+import numpy as np
+cimport numpy as np
+import scipy.sparse as sps
import time
-from pyfmi.common.io import ResultWriterDymola, ResultHandlerBinaryFile
+from pyfmi.common.io import ResultWriterDymola
import pyfmi.fmi as fmi
+from pyfmi.fmi import FMUException
from pyfmi.fmi cimport FMUModelME2
-from pyfmi.common import python3_flag
-from pyfmi.common.core import TrajectoryLinearInterpolation
from timeit import default_timer as timer
-import time
cimport fmil_import as FMIL
try:
@@ -79,17 +72,17 @@ def write_data(simulator,write_scaled_result=False, result_file_name=''):
model = simulator.problem._model
- t = N.array(simulator.problem._sol_time)
- r = N.array(simulator.problem._sol_real)
- data = N.c_[t,r]
+ t = np.array(simulator.problem._sol_time)
+ r = np.array(simulator.problem._sol_real)
+ data = np.c_[t,r]
if len(simulator.problem._sol_int) > 0 and len(simulator.problem._sol_int[0]) > 0:
- i = N.array(simulator.problem._sol_int)
- data = N.c_[data,i]
+ i = np.array(simulator.problem._sol_int)
+ data = np.c_[data,i]
if len(simulator.problem._sol_bool) > 0 and len(simulator.problem._sol_bool[0]) > 0:
- #b = N.array(simulator.problem._sol_bool).reshape(
+ #b = np.array(simulator.problem._sol_bool).reshape(
# -1,len(model._save_bool_variables_val))
- b = N.array(simulator.problem._sol_bool)
- data = N.c_[data,b]
+ b = np.array(simulator.problem._sol_bool)
+ data = np.c_[data,b]
export = ResultWriterDymola(model)
export.write_header(file_name=result_file_name)
@@ -151,7 +144,7 @@ class FMIODE(Explicit_Problem):
#If there is no state in the model, add a dummy
#state der(y)=0
if f_nbr == 0:
- self.y0 = N.array([0.0])
+ self.y0 = np.array([0.0])
#Determine the result file name
if result_file_name == '':
@@ -201,7 +194,7 @@ class FMIODE(Explicit_Problem):
input_value_refs.append(self._model.get_variable_valueref(name))
input_alias_type.append(-1.0 if self._model.get_variable_alias(name)[name] == -1 else 1.0)
self.input_value_refs = input_value_refs
- self.input_alias_type = input_alias_type if N.any(input_alias_type==-1) else 1.0
+ self.input_alias_type = input_alias_type if np.any(input_alias_type==-1) else 1.0
self.input = input
def rhs(self, t, y, sw=None):
@@ -226,7 +219,7 @@ class FMIODE(Explicit_Problem):
#If there is no state, use the dummy
if self._f_nbr == 0:
- rhs = N.array([0.0])
+ rhs = np.array([0.0])
return rhs
@@ -300,7 +293,7 @@ class FMIODE(Explicit_Problem):
#Sets the inputs, if any
if self.input is not None:
- self._model.set_real(self.input_value_refs, self.input[1].eval(N.array([solver.t]))[0,:]*self.input_alias_type)
+ self._model.set_real(self.input_value_refs, self.input[1].eval(np.array([solver.t]))[0,:]*self.input_alias_type)
#Evaluating the rhs (Have to evaluate the values in the model)
rhs = self._model.get_derivatives()
@@ -391,8 +384,8 @@ class FMIODE(Explicit_Problem):
#Sets the inputs, if any
if self.input is not None:
- self._model.set_real(self.input_value_refs, self.input[1].eval(N.array([solver.t]))[0,:]*self.input_alias_type)
- #self._model.set(self.input[0],self.input[1].eval(N.array([solver.t]))[0,:])
+ self._model.set_real(self.input_value_refs, self.input[1].eval(np.array([solver.t]))[0,:]*self.input_alias_type)
+ #self._model.set(self.input[0],self.input[1].eval(np.array([solver.t]))[0,:])
#Evaluating the rhs (Have to evaluate the values in the model)
rhs = self._model.get_derivatives()
@@ -526,8 +519,8 @@ class FMIODESENS(FMIODE):
if parameters is not None:
if not isinstance(parameters,list):
raise FMIModel_Exception("Parameters must be a list of names.")
- self.p0 = N.array(model.get(parameters)).flatten()
- self.pbar = N.array([N.abs(x) if N.abs(x) > 0 else 1.0 for x in self.p0])
+ self.p0 = np.array(model.get(parameters)).flatten()
+ self.pbar = np.array([np.abs(x) if np.abs(x) > 0 else 1.0 for x in self.p0])
self.parameters = parameters
@@ -570,7 +563,7 @@ class FMIODESENS(FMIODE):
#Sets the parameters, if any
if self.parameters is not None:
- p_data = N.array(solver.interpolate_sensitivity(t, 0)).flatten()
+ p_data = np.array(solver.interpolate_sensitivity(t, 0)).flatten()
self.export.integration_point(solver)#parameter_data=p_data)
@@ -594,7 +587,7 @@ cdef class FMIODE2(cExplicit_Problem):
self.input_names = []
self.timings = {"handle_result": 0.0}
- if type(model) == FMUModelME2: #isinstance(model, FMUModelME2):
+ if type(model)==FMUModelME2: #if isinstance(model, FMUModelME2):
self.model_me2 = model
self.model_me2_instance = 1
else:
@@ -620,7 +613,7 @@ cdef class FMIODE2(cExplicit_Problem):
#If there is no state in the model, add a dummy state der(y)=0
if f_nbr == 0:
- self.y0 = N.array([0.0])
+ self.y0 = np.array([0.0])
#Determine the result file name
if result_file_name == '':
@@ -650,12 +643,12 @@ cdef class FMIODE2(cExplicit_Problem):
#Need to calculate the nnz.
[derv_state_dep, derv_input_dep] = model.get_derivatives_dependencies()
- self.jac_nnz = N.sum([len(derv_state_dep[key]) for key in derv_state_dep.keys()])+f_nbr
+ self.jac_nnz = np.sum([len(derv_state_dep[key]) for key in derv_state_dep.keys()])+f_nbr
if extra_equations:
self._extra_f_nbr = extra_equations.get_size()
self._extra_y0 = extra_equations.y0
- self.y0 = N.append(self.y0, self._extra_y0)
+ self.y0 = np.append(self.y0, self._extra_y0)
self._extra_equations = extra_equations
if hasattr(self._extra_equations, "jac"):
@@ -679,8 +672,8 @@ cdef class FMIODE2(cExplicit_Problem):
else:
self._synchronize_factor = 0.0
- self._state_temp_1 = N.empty(f_nbr, dtype = N.double)
- self._event_temp_1 = N.empty(g_nbr, dtype = N.double)
+ self._state_temp_1 = np.empty(f_nbr, dtype = np.double)
+ self._event_temp_1 = np.empty(g_nbr, dtype = np.double)
def _adapt_input(self, input):
if input is not None:
@@ -705,8 +698,8 @@ cdef class FMIODE2(cExplicit_Problem):
self.input_other.append(name)
input_other_mask.append(i)
- self.input_real_mask = N.array(input_real_mask)
- self.input_other_mask = N.array(input_other_mask)
+ self.input_real_mask = np.array(input_real_mask)
+ self.input_other_mask = np.array(input_other_mask)
self._input_activated = 1
else:
@@ -723,7 +716,7 @@ cdef class FMIODE2(cExplicit_Problem):
if self.input_other:
self._model.set(self.input_other, values[self.input_other_mask])
- cdef _update_model(self, double t, N.ndarray[double, ndim=1, mode="c"] y):
+ cdef _update_model(self, double t, np.ndarray[double, ndim=1, mode="c"] y):
if self.model_me2_instance:
#Moving data to the model
self.model_me2._set_time(t)
@@ -740,7 +733,7 @@ cdef class FMIODE2(cExplicit_Problem):
#Sets the inputs, if any
self._set_input_values(t)
- cdef int _compare(self, double t, N.ndarray[double, ndim=1, mode="c"] y):
+ cdef int _compare(self, double t, np.ndarray[double, ndim=1, mode="c"] y):
cdef int res
if self.model_me2_instance:
@@ -760,7 +753,7 @@ cdef class FMIODE2(cExplicit_Problem):
else:
return t != self._model.time or (not self._f_nbr == 0 and not (self._model.continuous_states == y).all())
- def rhs(self, double t, N.ndarray[double, ndim=1, mode="c"] y, sw=None):
+ def rhs(self, double t, np.ndarray[double, ndim=1, mode="c"] y, sw=None):
"""
The rhs (right-hand-side) for an ODE problem.
"""
@@ -790,14 +783,14 @@ cdef class FMIODE2(cExplicit_Problem):
#If there is no state, use the dummy
if self._f_nbr == 0:
- der = N.array([0.0])
+ der = np.array([0.0])
if self._extra_f_nbr > 0:
- der = N.append(der, self._extra_equations.rhs(y_extra))
+ der = np.append(der, self._extra_equations.rhs(y_extra))
return der
- def jac(self, double t, N.ndarray[double, ndim=1, mode="c"] y, sw=None):
+ def jac(self, double t, np.ndarray[double, ndim=1, mode="c"] y, sw=None):
"""
The jacobian function for an ODE problem.
"""
@@ -822,7 +815,7 @@ cdef class FMIODE2(cExplicit_Problem):
msg = preface + ''%(solver_info_tag)
self._model.append_log_message("Model", 6, msg)
- return N.array([[0.0]])
+ return np.array([[0.0]])
A = self._model._get_A(add_diag=True, output_matrix=self._A)
if self._A is None:
@@ -835,16 +828,16 @@ cdef class FMIODE2(cExplicit_Problem):
Jac = A.tocoo() #Convert to COOrdinate
A2 = self._extra_equations.jac(y_extra).tocoo()
- data = N.append(Jac.data, A2.data)
- row = N.append(Jac.row, A2.row+self._f_nbr)
- col = N.append(Jac.col, A2.col+self._f_nbr)
+ data = np.append(Jac.data, A2.data)
+ row = np.append(Jac.row, A2.row+self._f_nbr)
+ col = np.append(Jac.col, A2.col+self._f_nbr)
#Convert to compresssed sparse column
- Jac = sp.coo_matrix((data, (row, col)))
+ Jac = sps.coo_matrix((data, (row, col)))
Jac = Jac.tocsc()
else:
- Jac = N.zeros((self._f_nbr+self._extra_f_nbr,self._f_nbr+self._extra_f_nbr))
- Jac[:self._f_nbr,:self._f_nbr] = A if isinstance(A, N.ndarray) else A.toarray()
+ Jac = np.zeros((self._f_nbr+self._extra_f_nbr,self._f_nbr+self._extra_f_nbr))
+ Jac[:self._f_nbr,:self._f_nbr] = A if isinstance(A, np.ndarray) else A.toarray()
Jac[self._f_nbr:,self._f_nbr:] = self._extra_equations.jac(y_extra)
else:
raise fmi.FMUException("No Jacobian provided for the extra equations")
@@ -857,7 +850,7 @@ cdef class FMIODE2(cExplicit_Problem):
return Jac
- def state_events(self, double t, N.ndarray[double, ndim=1, mode="c"] y, sw=None):
+ def state_events(self, double t, np.ndarray[double, ndim=1, mode="c"] y, sw=None):
"""
The event indicator function for a ODE problem.
"""
@@ -880,7 +873,7 @@ cdef class FMIODE2(cExplicit_Problem):
else:
return self._model.get_event_indicators()
- def time_events(self, double t, N.ndarray[double, ndim=1, mode="c"] y, sw=None):
+ def time_events(self, double t, np.ndarray[double, ndim=1, mode="c"] y, sw=None):
"""
Time event function.
"""
@@ -981,7 +974,7 @@ cdef class FMIODE2(cExplicit_Problem):
msg = preface + ''%(event_info_tag)
self._model.append_log_message("Model", 6, msg)
else:
- diag_data = N.ndarray(self._number_of_diagnostics_variables, dtype=float)
+ diag_data = np.ndarray(self._number_of_diagnostics_variables, dtype=float)
index = 0
diag_data[index] = solver.t
index +=1
@@ -1156,7 +1149,7 @@ cdef class FMIODE2(cExplicit_Problem):
msg = preface + ''%(solver_info_tag)
self._model.append_log_message("Model", 6, msg)
else:
- diag_data = N.ndarray(self._number_of_diagnostics_variables, dtype=float)
+ diag_data = np.ndarray(self._number_of_diagnostics_variables, dtype=float)
index = 0
diag_data[index] = solver.t
index +=1
@@ -1336,8 +1329,8 @@ class FMIODESENS2(FMIODE2):
if parameters is not None:
if not isinstance(parameters,list):
raise FMIModel_Exception("Parameters must be a list of names.")
- self.p0 = N.array(model.get(parameters)).flatten()
- self.pbar = N.array([N.abs(x) if N.abs(x) > 0 else 1.0 for x in self.p0])
+ self.p0 = np.array(model.get(parameters)).flatten()
+ self.pbar = np.array([np.abs(x) if np.abs(x) > 0 else 1.0 for x in self.p0])
self.param_valref = [model.get_variable_valueref(x) for x in parameters]
for param in parameters:
@@ -1346,10 +1339,7 @@ class FMIODESENS2(FMIODE2):
raise FMIModel_Exception("The sensitivity parameters must be specified as inputs!")
self.parameters = parameters
- if python3_flag:
- self.derivatives = [v.value_reference for i,v in model.get_derivatives_list().items()]
- else:
- self.derivatives = [v.value_reference for i,v in model.get_derivatives_list().iteritems()]
+ self.derivatives = [v.value_reference for i,v in model.get_derivatives_list().items()]
if self._model.get_capability_flags()['providesDirectionalDerivatives']:
use_rhs_sens = True
diff --git a/src/pyfmi/tests/__init__.py b/src/pyfmi/tests/__init__.py
new file mode 100644
index 00000000..8962836d
--- /dev/null
+++ b/src/pyfmi/tests/__init__.py
@@ -0,0 +1,16 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+# Copyright (C) 2024 Modelon AB
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU Lesser General Public License as published by
+# the Free Software Foundation, version 3 of the License.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public License
+# along with this program. If not, see .
diff --git a/src/pyfmi/tests/test_util.pxd b/src/pyfmi/tests/test_util.pxd
new file mode 100644
index 00000000..bd175471
--- /dev/null
+++ b/src/pyfmi/tests/test_util.pxd
@@ -0,0 +1,33 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+# Copyright (C) 2014-2024 Modelon AB
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU Lesser General Public License as published by
+# the Free Software Foundation, version 3 of the License.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public License
+# along with this program. If not, see .
+
+""" Collection of classes used for testing purposes."""
+cimport pyfmi.fmil_import as FMIL
+from pyfmi.fmi cimport FMUModelME1, FMUModelME2
+
+cdef class _ForTestingFMUModelME1(FMUModelME1):
+ cdef int _get_nominal_continuous_states_fmil(self, FMIL.fmi1_real_t* xnominal, size_t nx)
+ cpdef set_allocated_fmu(self, int value)
+
+cdef class _ForTestingFMUModelME2(FMUModelME2):
+ cdef int _get_real_by_ptr(self, FMIL.fmi2_value_reference_t* vrefs, size_t _size, FMIL.fmi2_real_t* values)
+ cdef int _set_real(self, FMIL.fmi2_value_reference_t* vrefs, FMIL.fmi2_real_t* values, size_t _size)
+ cdef int _get_real_by_list(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_real_t[:] values)
+ cdef int _get_integer(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_integer_t[:] values)
+ cdef int _get_boolean(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_real_t[:] values)
+ cdef int _get_nominal_continuous_states_fmil(self, FMIL.fmi2_real_t* xnominal, size_t nx)
+ cpdef set_initialized_fmu(self, int value)
diff --git a/tests/test_util.py b/src/pyfmi/tests/test_util.pyx
similarity index 72%
rename from tests/test_util.py
rename to src/pyfmi/tests/test_util.pyx
index b87abf04..95f2ebe9 100644
--- a/tests/test_util.py
+++ b/src/pyfmi/tests/test_util.pyx
@@ -15,15 +15,37 @@
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
+# distutils: define_macros=NPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION
+
import os
import numpy as np
+cimport pyfmi.fmil_import as FMIL
-from pyfmi.fmi import (FMUException, FMUModelME1, _ForTestingFMUModelME1, FMUModelCS1,
- FMUModelCS2, FMUModelME2, _ForTestingFMUModelME2)
+from pyfmi.fmi import FMUException, FMUModelME1, FMUModelCS1, FMUModelCS2, FMUModelME2
def get_examples_folder():
return os.path.join(os.path.dirname(__file__), '..', 'examples')
+cdef class _ForTestingFMUModelME1(FMUModelME1):
+ cdef int _get_nominal_continuous_states_fmil(self, FMIL.fmi1_real_t* xnominal, size_t nx):
+ for i in range(nx):
+ if self._allocated_fmu == 1: # If initialized
+ # Set new values to test that atol gets auto-corrected.
+ xnominal[i] = 3.0
+ else:
+ # Set some illegal values in order to test the fallback/auto-correction.
+ xnominal[i] = ((( i) % 3) - 1) * 2.0 # -2.0, 0.0, 2.0,
+ return FMIL.fmi1_status_ok
+
+ cpdef set_allocated_fmu(self, int value):
+ self._allocated_fmu = value
+
+ def __dealloc__(self):
+ # Avoid segfaults in dealloc. The FMU binaries should never be loaded for this
+ # test class, so we should never try to terminate or deallocate the FMU instance.
+ self._allocated_fmu = 0
+
+
class Dummy_FMUModelME1(_ForTestingFMUModelME1):
# If true, makes use of the real _ForTesting implementation for nominal_continuous_states,
# else just returns 1.0 for each.
@@ -127,6 +149,82 @@ def get_integer(self, vref):
def get_boolean(self, vref):
return self.get_real(vref)
+
+cdef class _ForTestingFMUModelME2(FMUModelME2):
+ cdef int _get_real_by_ptr(self, FMIL.fmi2_value_reference_t* vrefs, size_t _size, FMIL.fmi2_real_t* values):
+ vr = np.zeros(_size)
+ for i in range(_size):
+ vr[i] = vrefs[i]
+
+ try:
+ vv = self.get_real(vr)
+ except Exception:
+ return FMIL.fmi2_status_error
+
+ for i in range(_size):
+ values[i] = vv[i]
+
+ return FMIL.fmi2_status_ok
+
+ cdef int _set_real(self, FMIL.fmi2_value_reference_t* vrefs, FMIL.fmi2_real_t* values, size_t _size):
+ vr = np.zeros(_size)
+ vv = np.zeros(_size)
+ for i in range(_size):
+ vr[i] = vrefs[i]
+ vv[i] = values[i]
+
+ try:
+ self.set_real(vr, vv)
+ except Exception:
+ return FMIL.fmi2_status_error
+
+ return FMIL.fmi2_status_ok
+
+ cdef int _get_real_by_list(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_real_t[:] values):
+ try:
+ tmp = self.get_real(valueref)
+ for i in range(_size):
+ values[i] = tmp[i]
+ except Exception:
+ return FMIL.fmi2_status_error
+ return FMIL.fmi2_status_ok
+
+ cdef int _get_integer(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_integer_t[:] values):
+ try:
+ tmp = self.get_integer(valueref)
+ for i in range(_size):
+ values[i] = tmp[i]
+ except Exception:
+ return FMIL.fmi2_status_error
+ return FMIL.fmi2_status_ok
+
+ cdef int _get_boolean(self, FMIL.fmi2_value_reference_t[:] valueref, size_t _size, FMIL.fmi2_real_t[:] values):
+ try:
+ tmp = self.get_boolean(valueref)
+ for i in range(_size):
+ values[i] = tmp[i]
+ except Exception:
+ return FMIL.fmi2_status_error
+ return FMIL.fmi2_status_ok
+
+ cdef int _get_nominal_continuous_states_fmil(self, FMIL.fmi2_real_t* xnominal, size_t nx):
+ for i in range(nx):
+ if self._initialized_fmu == 1:
+ # Set new values to test that atol gets auto-corrected.
+ xnominal[i] = 3.0
+ else:
+ # Set some illegal values in order to test the fallback/auto-correction.
+ xnominal[i] = ((( i) % 3) - 1) * 2.0 # -2.0, 0.0, 2.0,
+ return FMIL.fmi2_status_ok
+
+ cpdef set_initialized_fmu(self, int value):
+ self._initialized_fmu = value
+
+ def __dealloc__(self):
+ # Avoid segfaults in dealloc. The FMU binaries should never be loaded for this
+ # test class, so we should never try to terminate or deallocate the FMU instance.
+ self._initialized_fmu = 0
+
class Dummy_FMUModelCS2(FMUModelCS2):
#Override properties
time = None
@@ -288,7 +386,7 @@ def get_real(self, vref, evaluate = True):
if evaluate:
self.get_derivatives()
vals = []
- if type(vref) == int:
+ if isinstance(vref, int):
vref = [vref]
for v in vref:
vals.append(self.values[v])
diff --git a/tests/__init__.py b/tests/__init__.py
index 8e501f09..e7c78986 100644
--- a/tests/__init__.py
+++ b/tests/__init__.py
@@ -1,7 +1,7 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
-# Copyright (C) 2018 Modelon AB
+# Copyright (C) 2018-2024 Modelon AB
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
diff --git a/tests/test_fmi_coupled.py b/tests/test_fmi_coupled.py
index d0b26f88..b1b622a8 100644
--- a/tests/test_fmi_coupled.py
+++ b/tests/test_fmi_coupled.py
@@ -17,16 +17,12 @@
import nose
import os
-import numpy as np
from pyfmi import testattr
-from pyfmi.fmi import FMUException, FMUModelME1, FMUModelCS1, load_fmu, FMUModelCS2, FMUModelME2, PyEventInfo
+from pyfmi.fmi import FMUModelME2
from pyfmi.fmi_coupled import CoupledFMUModelME2
-import pyfmi.fmi_util as fmi_util
import pyfmi.fmi as fmi
-import pyfmi.fmi_algorithm_drivers as fmi_algorithm_drivers
from pyfmi.tests.test_util import Dummy_FMUModelME2
-from pyfmi.common.io import ResultHandler
assimulo_installed = True
try:
diff --git a/tests/test_fmi_extended.py b/tests/test_fmi_extended.py
index 884bb1f9..b0655012 100644
--- a/tests/test_fmi_extended.py
+++ b/tests/test_fmi_extended.py
@@ -15,19 +15,11 @@
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
-import nose
import os
import numpy as np
from pyfmi import testattr
-from pyfmi.fmi import FMUException, FMUModelME1, FMUModelCS1, load_fmu, FMUModelCS2, FMUModelME2, PyEventInfo
-from pyfmi.fmi_coupled import CoupledFMUModelME2
from pyfmi.fmi_extended import FMUModelME1Extended
-import pyfmi.fmi_util as fmi_util
-import pyfmi.fmi as fmi
-import pyfmi.fmi_algorithm_drivers as fmi_algorithm_drivers
-from pyfmi.tests.test_util import Dummy_FMUModelME2
-from pyfmi.common.io import ResultHandler
file_path = os.path.dirname(os.path.abspath(__file__))
diff --git a/tests/test_fmi_master.py b/tests/test_fmi_master.py
index 811c4b01..c8f04dc2 100644
--- a/tests/test_fmi_master.py
+++ b/tests/test_fmi_master.py
@@ -19,12 +19,10 @@
import os
import numpy as np
-from pyfmi import testattr
-from pyfmi.fmi import FMUException, FMUModelME1, FMUModelCS1, load_fmu, FMUModelCS2, FMUModelME2
-import pyfmi.fmi_util as fmi_util
-import pyfmi.fmi as fmi
-from pyfmi import Master
-from pyfmi.tests.test_util import Dummy_FMUModelME2, Dummy_FMUModelCS2
+from pyfmi import testattr, Master
+from pyfmi.fmi import FMUException, FMUModelCS2, FMUModelME2
+from pyfmi.tests.test_util import Dummy_FMUModelCS2
+from pyfmi.common.algorithm_drivers import UnrecognizedOptionError
file_path = os.path.dirname(os.path.abspath(__file__))
@@ -169,8 +167,6 @@ def test_basic_simulation_mat_file(self):
@testattr(stddist = True)
def test_basic_simulation_mat_file_naming(self):
- from pyfmi.common.algorithm_drivers import UnrecognizedOptionError
-
opts = {"result_handling":"binary", "result_file_name": "Should fail..."}
try:
@@ -327,151 +323,3 @@ def do_step2(current_t, step_size, new_step=True):
assert abs(res[model_sub1].final("x1")) > 100
assert abs(res[model_sub2].final("x2")) > 100
-
-
-"""
-To be migrated:
-
-
-class Test_Master_Simulation:
- @classmethod
- def setUpClass(cls):
- file_name = os.path.join(get_files_path(), 'Modelica', 'LinearCoSimulation.mo')
-
- cls.linear_full = compile_fmu("LinearCoSimulation.LinearFullSystem", file_name, target="cs", version="2.0")
- cls.linear_sub1 = compile_fmu("LinearCoSimulation.LinearSubSystem1", file_name, target="cs", version="2.0")
- cls.linear_sub2 = compile_fmu("LinearCoSimulation.LinearSubSystem2", file_name, target="cs", version="2.0")
-
- compiler_options={"generate_ode_jacobian": True}
-
- cls.linear_sub1_dir = compile_fmu("LinearCoSimulation.LinearSubSystem1", file_name, target="cs", version="2.0",
- compiler_options={"generate_ode_jacobian": True}, compile_to="LinearSub1Dir.fmu")
- cls.linear_sub2_dir = compile_fmu("LinearCoSimulation.LinearSubSystem2", file_name, target="cs", version="2.0",
- compiler_options={"generate_ode_jacobian": True}, compile_to="LinearSub2Dir.fmu")
-
- @testattr(stddist = True)
- def test_linear_correction_simulation(self):
- model = load_fmu(self.linear_full)
-
- model_sub1 = load_fmu(self.linear_sub1_dir)
- model_sub2 = load_fmu(self.linear_sub2_dir)
-
- models = [model_sub1, model_sub2]
- connections = [(model_sub1,"y1",model_sub2,"u2"),
- (model_sub2,"y2",model_sub1,"u1")]
-
- master = Master(models, connections)
-
- opts = master.simulate_options()
- opts["step_size"] = 0.0005
- opts["extrapolation_order"] = 1
- opts["linear_correction"] = True
-
- res = master.simulate(options=opts)
-
- res_full = model.simulate()
-
- nose.tools.assert_almost_equal(res[model_sub1].final("x1"), res_full.final("p1.x1"), 2)
- nose.tools.assert_almost_equal(res[model_sub2].final("x2"), res_full.final("p2.x2"), 2)
-
- @testattr(stddist = True)
- def test_basic_simulation_extrapolation(self):
- model = load_fmu(self.linear_full)
-
- model.set("p1.d1", 0.1)
-
- model_sub1 = load_fmu(self.linear_sub1)
- model_sub2 = load_fmu(self.linear_sub2)
-
- model_sub1.set("d1", 0.1)
-
- models = [model_sub1, model_sub2]
- connections = [(model_sub1,"y1",model_sub2,"u2"),
- (model_sub2,"y2",model_sub1,"u1")]
-
- master = Master(models, connections)
-
- opts = master.simulate_options()
- opts["step_size"] = 0.0005
- opts["extrapolation_order"] = 1
-
- res = master.simulate(options=opts)
-
- res_full = model.simulate()
-
- nose.tools.assert_almost_equal(res[model_sub1].final("x1"), res_full.final("p1.x1"), 2)
- nose.tools.assert_almost_equal(res[model_sub2].final("x2"), res_full.final("p2.x2"), 2)
-
- @testattr(stddist = True)
- def test_unstable_simulation_extrapolation(self):
- model = load_fmu(self.linear_full)
-
- model_sub1 = load_fmu(self.linear_sub1)
- model_sub2 = load_fmu(self.linear_sub2)
-
- models = [model_sub1, model_sub2]
- connections = [(model_sub1,"y1",model_sub2,"u2"),
- (model_sub2,"y2",model_sub1,"u1")]
-
- master = Master(models, connections)
-
- opts = master.simulate_options()
- opts["step_size"] = 0.0005
- opts["extrapolation_order"] = 1
-
- res = master.simulate(final_time=0.2, options=opts)
-
- res_full = model.simulate()
-
- #The coupled system is unstable with extrapolation 1
- assert abs(res[model_sub1].final("x1")) > 100
- assert abs(res[model_sub2].final("x2")) > 100
-
- #import pylab as plt
- #plt.plot(res[model_sub1]["time"], res[model_sub1]["x1"])
- #plt.plot(res_full["time"], res_full["p1.x1"])
- #plt.show()
-
- @testattr(stddist = True)
- def test_initialize(self):
- model = load_fmu(self.linear_full)
- model.setup_experiment()
- model.initialize()
-
- model_sub1 = load_fmu(self.linear_sub1)
- model_sub2 = load_fmu(self.linear_sub2)
-
- models = [model_sub1, model_sub2]
- connections = [(model_sub1,"y1",model_sub2,"u2"),
- (model_sub2,"y2",model_sub1,"u1")]
-
- master = Master(models, connections)
-
- opts = master.simulate_options()
- opts["step_size"] = 0.0005
- opts["extrapolation_order"] = 1
-
- master.initialize(0, 1, opts)
-
- nose.tools.assert_almost_equal(model_sub1.get("y1"), model.get("p1.y1"), 2)
- nose.tools.assert_almost_equal(model_sub2.get("y2"), model.get("p2.y2"), 2)
-
- model_sub1 = load_fmu(self.linear_sub1)
- model_sub2 = load_fmu(self.linear_sub2)
-
- models = [model_sub1, model_sub2]
- connections = [(model_sub1,"y1",model_sub2,"u2"),
- (model_sub2,"y2",model_sub1,"u1")]
-
- master = Master(models, connections)
-
- opts = master.simulate_options()
- opts["step_size"] = 0.0005
- opts["extrapolation_order"] = 1
- opts["block_initialization"] = True
-
- master.initialize(0, 1, opts)
-
- nose.tools.assert_almost_equal(model_sub1.get("y1"), model.get("p1.y1"), 2)
- nose.tools.assert_almost_equal(model_sub2.get("y2"), model.get("p2.y2"), 2)
-"""
diff --git a/tests/test_fmi_util.py b/tests/test_fmi_util.py
index eb969edb..5c03a930 100644
--- a/tests/test_fmi_util.py
+++ b/tests/test_fmi_util.py
@@ -19,15 +19,11 @@
Module containing the tests for the FMI interface.
"""
-import nose
-import os
import numpy as np
from collections import OrderedDict
from pyfmi import testattr
-from pyfmi.fmi import FMUException, FMUModelME1, FMUModelCS1, load_fmu, FMUModelCS2, FMUModelME2, PyEventInfo
import pyfmi.fmi_util as fmi_util
-import pyfmi.fmi as fmi
class Test_FMIUtil:
diff --git a/tests/test_stream.py b/tests/test_stream.py
index a517eb51..758c7af1 100644
--- a/tests/test_stream.py
+++ b/tests/test_stream.py
@@ -277,4 +277,4 @@ def test_extract_xml_log_into_stream(self):
xml_log = fmu.extract_xml_log()
err_msg = "Unequal xml files, please compare the contents of:\n{}\nand\n{}".format(xml_file1, xml_log)
- nose.tools.assert_true(compare_files(xml_file1, xml_log), err_msg)
\ No newline at end of file
+ nose.tools.assert_true(compare_files(xml_file1, xml_log), err_msg)