From d79199fd267d35a4325abd41502cdbfa43e9dde2 Mon Sep 17 00:00:00 2001
From: PeterMeisrimelModelon
<92585725+PeterMeisrimelModelon@users.noreply.github.com>
Date: Fri, 26 Jan 2024 14:40:48 +0100
Subject: [PATCH] Unifying numpy, scipy, pylab imports
---
src/common/algorithm_drivers.py | 18 +-
src/common/core.py | 52 +--
src/common/io.py | 83 +++--
src/common/plotting/plot_gui.py | 2 +-
src/pyfmi/__init__.py | 6 +-
src/pyfmi/debug.py | 128 +++----
.../examples/fmi20_bouncing_ball_native.py | 26 +-
src/pyfmi/examples/fmi_bouncing_ball.py | 30 +-
src/pyfmi/examples/fmi_bouncing_ball_cs.py | 30 +-
.../examples/fmi_bouncing_ball_native.py | 26 +-
src/pyfmi/examples/fmu_with_input.py | 28 +-
src/pyfmi/examples/fmu_with_input_function.py | 24 +-
src/pyfmi/fmi.pxd | 20 +-
src/pyfmi/fmi.pyx | 346 +++++++++---------
src/pyfmi/fmi_algorithm_drivers.py | 26 +-
src/pyfmi/fmi_coupled.pyx | 13 +-
src/pyfmi/fmi_extended.pyx | 24 +-
src/pyfmi/master.pyx | 43 ++-
src/pyfmi/simulation/assimulo_interface.pxd | 12 +-
src/pyfmi/simulation/assimulo_interface.pyx | 93 +++--
tests/test_fmi_master.py | 8 +-
21 files changed, 520 insertions(+), 518 deletions(-)
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 8bd8baaf..0cfb3f52 100644
--- a/src/common/core.py
+++ b/src/common/core.py
@@ -25,7 +25,7 @@
import sys
import shutil
-import numpy as N
+import numpy as np
# location for temporary JModelica files
def get_temp_location():
@@ -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 c0e391da..2f3b4c8a 100644
--- a/src/common/io.py
+++ b/src/common/io.py
@@ -24,7 +24,6 @@
import os
from functools import reduce
-import numpy as N
import numpy as np
import scipy
scipy_minmaj = tuple(map(int, scipy.__version__.split('.')[:2]))
@@ -200,7 +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:
@@ -326,7 +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):
"""
@@ -604,9 +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))))
@@ -712,7 +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])
@@ -806,7 +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])
@@ -928,7 +927,7 @@ def __init__(self,fname):
nLines = int(nLines[0])
nCols = int(nCols[0])
- self.dataInfo = N.array([list(map(int,fid.readline().split()[0:nCols])) for i in range(nLines)])
+ 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(self._name) == 1: #Only time
@@ -963,7 +962,7 @@ def __init__(self,fname):
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.')
@@ -1109,7 +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):
@@ -1122,9 +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
@@ -1449,7 +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)
@@ -1488,12 +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
@@ -1520,7 +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:
@@ -1670,7 +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):
"""
@@ -1685,16 +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)
@@ -1822,18 +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):
"""
@@ -1859,7 +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:
@@ -2259,10 +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=[]):
"""
@@ -2287,14 +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]))
@@ -2397,11 +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
@@ -2609,7 +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/plotting/plot_gui.py b/src/common/plotting/plot_gui.py
index 380f929f..7c3cf89e 100644
--- a/src/common/plotting/plot_gui.py
+++ b/src/common/plotting/plot_gui.py
@@ -25,7 +25,7 @@
from matplotlib import rcParams
import fnmatch
import re
-import oss
+import os
#GUI modules
try:
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 a66e6e41..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 pylab as P
+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]
@@ -63,69 +63,69 @@ def _load_data(self):
def plot_time_distribution(self, normalized=False):
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):
- 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):
- 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):
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):
- 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
@@ -157,11 +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]
@@ -174,44 +174,44 @@ def _load_data(self):
def plot_order(self):
- 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):
- 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 9911313f..22fc59fc 100644
--- a/src/pyfmi/examples/fmi20_bouncing_ball_native.py
+++ b/src/pyfmi/examples/fmi20_bouncing_ball_native.py
@@ -16,8 +16,8 @@
# 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
@@ -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 f15b080c..d7b4b658 100644
--- a/src/pyfmi/examples/fmi_bouncing_ball.py
+++ b/src/pyfmi/examples/fmi_bouncing_ball.py
@@ -16,8 +16,8 @@
# 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
@@ -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
- 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 c3e8785c..5008adbc 100644
--- a/src/pyfmi/examples/fmi_bouncing_ball_cs.py
+++ b/src/pyfmi/examples/fmi_bouncing_ball_cs.py
@@ -16,8 +16,8 @@
# 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
@@ -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
- 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 bf747260..b1dd78ef 100644
--- a/src/pyfmi/examples/fmi_bouncing_ball_native.py
+++ b/src/pyfmi/examples/fmi_bouncing_ball_native.py
@@ -16,8 +16,8 @@
# 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
@@ -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 177b60d0..985233f5 100644
--- a/src/pyfmi/examples/fmu_with_input.py
+++ b/src/pyfmi/examples/fmu_with_input.py
@@ -16,8 +16,8 @@
# along with this program. If not, see .
import os
-import numpy as N
-import pylab as p
+import numpy as np
+import pylab as pl
from pyfmi import load_fmu
@@ -35,9 +35,9 @@ def run_demo(with_plots=True):
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:
- 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 e0abaaa9..2e4c42f5 100644
--- a/src/pyfmi/examples/fmu_with_input_function.py
+++ b/src/pyfmi/examples/fmu_with_input_function.py
@@ -16,8 +16,8 @@
# along with this program. If not, see .
import os
-import numpy as N
-import pylab as p
+import numpy as np
+import pylab as pl
from pyfmi import load_fmu
@@ -35,7 +35,7 @@ def run_demo(with_plots=True):
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:
- 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 ad27c383..b110a24c 100644
--- a/src/pyfmi/fmi.pxd
+++ b/src/pyfmi/fmi.pxd
@@ -17,8 +17,8 @@
"""
Module containing the FMI interface Python wrappers.
"""
-import numpy as N
-cimport numpy as N
+import numpy as np
+cimport numpy as np
cimport pyfmi.fmil_import as FMIL
@@ -219,9 +219,9 @@ 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)
+ 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)
@@ -233,8 +233,8 @@ 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):
@@ -253,11 +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)
diff --git a/src/pyfmi/fmi.pyx b/src/pyfmi/fmi.pyx
index bc29d43e..13263331 100644
--- a/src/pyfmi/fmi.pyx
+++ b/src/pyfmi/fmi.pyx
@@ -34,9 +34,9 @@ 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
@@ -46,8 +46,8 @@ from pyfmi.common.core import create_temp_dir
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"""
@@ -141,8 +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."""
@@ -1156,7 +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
@@ -1188,7 +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)
@@ -1542,9 +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
@@ -1575,11 +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.')
@@ -1609,9 +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
@@ -1642,11 +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.')
@@ -1677,11 +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)
@@ -1697,7 +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):
"""
@@ -1718,19 +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.')
@@ -1762,8 +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 []
@@ -1801,21 +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)
@@ -2886,9 +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)
@@ -2899,20 +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)
@@ -2974,30 +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:
@@ -3402,7 +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:
@@ -3410,11 +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 '\
@@ -3444,7 +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:
@@ -3494,7 +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)
@@ -3522,7 +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)
@@ -3679,7 +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)
@@ -4166,7 +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).
@@ -4187,9 +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
@@ -4221,13 +4221,13 @@ 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.')
@@ -4265,9 +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
@@ -4298,11 +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)
@@ -4344,11 +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)
@@ -4364,7 +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):
"""
@@ -4386,12 +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
@@ -4429,8 +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 []
@@ -4469,21 +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)
@@ -6096,7 +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)
@@ -6104,7 +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)
@@ -6136,7 +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)
@@ -6485,8 +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:
@@ -6495,7 +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
@@ -6526,16 +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
@@ -6794,11 +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')
@@ -6823,20 +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)
@@ -7147,11 +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?
@@ -7162,10 +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
@@ -7179,16 +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
@@ -7214,9 +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)
@@ -7225,20 +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)
@@ -7249,15 +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
@@ -7766,7 +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:
@@ -7788,7 +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)
@@ -7962,7 +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:
@@ -7976,7 +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.
@@ -7986,9 +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 '\
@@ -8017,7 +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:
@@ -8071,7 +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)
@@ -8236,9 +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
@@ -8283,11 +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):
@@ -8302,7 +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)
@@ -8395,23 +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]
@@ -8735,22 +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
@@ -8776,8 +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 70618d33..1f0f4869 100644
--- a/src/pyfmi/fmi_algorithm_drivers.py
+++ b/src/pyfmi/fmi_algorithm_drivers.py
@@ -21,7 +21,8 @@
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
@@ -35,8 +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
@@ -583,10 +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"]
@@ -639,7 +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:
@@ -665,7 +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.
@@ -712,7 +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:
@@ -1094,7 +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
@@ -1276,7 +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()
@@ -1301,7 +1302,6 @@ def solve(self):
"""
Runs the estimation.
"""
- import scipy.optimize as sciopt
from pyfmi.fmi_util import parameter_estimation_f
#Define callback
@@ -1321,13 +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 7885c9e6..c821917b 100644
--- a/src/pyfmi/fmi_coupled.pyx
+++ b/src/pyfmi/fmi_coupled.pyx
@@ -17,6 +17,10 @@
# 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
@@ -24,10 +28,7 @@ cimport fmil_import as FMIL
from pyfmi.fmi_util import enable_caching, Graph
from collections import OrderedDict
-import time
-import numpy as np
-cimport numpy as np
-import scipy.optimize as sopt
+import scipy.optimize as spopt
def init_f_block(u, coupled, block):
@@ -1978,7 +1979,7 @@ cdef class CoupledFMUModelME2(CoupledFMUModelBase):
u = np.array(u).ravel()
success = False
- res = sopt.root(init_f_block, u, args=(self,block))
+ res = spopt.root(init_f_block, u, args=(self,block))
success = res["success"]
if not success:
@@ -1988,7 +1989,7 @@ cdef class CoupledFMUModelME2(CoupledFMUModelBase):
for model in block["outputs"].keys():
self.get_specific_connection_outputs(model, block["outputs_mask"][model], y)
- res = sopt.root(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 07d37ce9..894e5693 100644
--- a/src/pyfmi/fmi_extended.pyx
+++ b/src/pyfmi/fmi_extended.pyx
@@ -22,8 +22,8 @@ Module containing the FMI interface Python wrappers.
"""
import logging
-import numpy as N
-cimport numpy as N
+import numpy as np
+cimport numpy as np
cimport fmil_import as FMIL
from pyfmi.fmi cimport FMUModelME1
@@ -38,7 +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
@@ -52,7 +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:
@@ -97,7 +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):
@@ -126,7 +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)
@@ -281,12 +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.")
@@ -298,10 +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/master.pyx b/src/pyfmi/master.pyx
index a9942b25..b7fe956a 100644
--- a/src/pyfmi/master.pyx
+++ b/src/pyfmi/master.pyx
@@ -32,9 +32,8 @@ import time
import numpy as np
import warnings
cimport numpy as np
-import scipy.sparse as sp
-import scipy.sparse.linalg as splin
-import scipy.optimize as sopt
+import scipy.sparse as sps
+import scipy.optimize as spopt
from pyfmi.fmi cimport FMUModelCS2
from cpython cimport bool
@@ -460,7 +459,7 @@ 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":[]}
@@ -559,8 +558,8 @@ 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 = []
@@ -601,7 +600,7 @@ 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)
@@ -622,7 +621,7 @@ 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 = []
@@ -638,7 +637,7 @@ 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 = []
@@ -654,7 +653,7 @@ 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:
@@ -845,7 +844,7 @@ 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:
@@ -890,7 +889,7 @@ 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:
@@ -957,7 +956,7 @@ 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
@@ -972,7 +971,7 @@ 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
@@ -984,7 +983,7 @@ cdef class Master:
JM_FMUS = False
break
if JM_FMUS:
- res = sopt.root(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.")
@@ -1005,8 +1004,8 @@ cdef class Master:
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))
+ #y = sps.linalg.lsqr((sps.eye(*DL.shape)-DL),z)[0].reshape((-1,1))
elif self.algebraic_loops and self.support_directional_derivatives:
pass
@@ -1113,7 +1112,7 @@ cdef class Master:
for model in block["outputs"].keys():
self.get_specific_connection_outputs(model, block["outputs_mask"][model], y)
- res = sopt.root(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.")
@@ -1135,9 +1134,9 @@ cdef class Master:
if self.algebraic_loops: #If there is an algebraic loop, solve the resulting system
if self.support_directional_derivatives:
- res = sopt.root(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:
- res = sopt.root(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.")
@@ -1314,7 +1313,7 @@ cdef class Master:
D = self.compute_global_D()
DL = D.dot(self.L)
import numpy.linalg
- import scipy.linalg as slin
+ from scipy.linalg import expm
print("At time: %E , rho(DL)=%s"%(tcur + step_size, str(numpy.linalg.eig(DL.todense())[0])))
C = self.compute_global_C()
if C is not None:
@@ -1326,7 +1325,7 @@ cdef class Master:
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)
+ eAH = 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))
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 288c41c3..db7debea 100644
--- a/src/pyfmi/simulation/assimulo_interface.pyx
+++ b/src/pyfmi/simulation/assimulo_interface.pyx
@@ -24,10 +24,9 @@ required by Assimulo.
import logging as logging_module
from operator import index
-import numpy as N
-
-cimport numpy as N
-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
@@ -73,17 +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)
@@ -145,7 +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 == '':
@@ -195,7 +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):
@@ -220,7 +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
@@ -294,7 +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()
@@ -385,8 +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()
@@ -520,8 +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
@@ -564,7 +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)
@@ -614,7 +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 == '':
@@ -644,12 +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"):
@@ -673,8 +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:
@@ -699,8 +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:
@@ -717,7 +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)
@@ -734,7 +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:
@@ -754,7 +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.
"""
@@ -784,14 +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.
"""
@@ -816,7 +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:
@@ -829,16 +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")
@@ -851,7 +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.
"""
@@ -874,7 +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.
"""
@@ -975,7 +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
@@ -1150,7 +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
@@ -1330,8 +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:
diff --git a/tests/test_fmi_master.py b/tests/test_fmi_master.py
index 13e58749..42af2971 100644
--- a/tests/test_fmi_master.py
+++ b/tests/test_fmi_master.py
@@ -424,10 +424,10 @@ def test_unstable_simulation_extrapolation(self):
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()
+ #import pylab as pl
+ #pl.plot(res[model_sub1]["time"], res[model_sub1]["x1"])
+ #pl.plot(res_full["time"], res_full["p1.x1"])
+ #pl.show()
@testattr(stddist = True)
def test_initialize(self):