def get_result(A_helio_total, A_rcv, fb, R1, ab_particle, t_storage, pinch):
os.system(
'st_simulate --stop 1y --maxStep 300s --step 3600s --np=0 PhysicalParticleCO21D_2ndApproach.mo n_row_oelt=9 n_col_oelt=25 A_helio_total=%f A_rcv=%f fb=%f R1=%f ab_particle=%f t_storage=%f pinch=%f'
% (A_helio_total, A_rcv, fb, R1, ab_particle, t_storage, pinch))
resmat = "PhysicalParticleCO21D_2ndApproach_res_0.mat"
data = DyMat.DyMatFile(resmat)
UA_HX = data.data("powerBlock.exchanger.UA_HX")[-1] / 1000
C_heliostat = data.data("C_field")[-1]
C_rcv = data.data("C_receiver")[-1]
C_HX = data.data("powerBlock.C_exchanger")[-1]
C_cycle = data.data("C_block")[-1] - C_HX
C_storage = data.data("C_storage")[-1]
C_equipment = data.data("C_cap_total")[-1]
C_total = data.data("C_cap")[-1]
EPY = data.data("E_elec")[-1] / 1000 #in kJ
resultclass = postproc.SimResultElec
res_object = resultclass(
resmat
) #passing the resmatfile into resultclass (postproc.SimResultElec)
result = res_object.calc_perf()
LCOE = float('%.2f' % (result[1])) / 1000
return [
fb, R1, UA_HX, C_heliostat, C_rcv, C_HX, C_cycle, C_storage,
C_equipment, C_total, EPY, LCOE
]
def loadMatFile(filename, prefix=None):
tic = time.time()
d = DyMat.DyMatFile(filename)
toc = time.time()
print("Opening %s in %.3f ms" % (filename, (toc - tic) * 1000))
extractVars(d, var_set, prefix=prefix)
def setUp(self):
fn = '../examples/Reference_2.mo'
res_fn = './Reference_2_res_0.mat'
xml_fn = './Reference_2_init_0.xml'
#xml_fn2='./Reference_2_init.xml'
self.sm = 2.8
self.t_storage = 9
os.system('st_simulate %s SM=%s t_storage=%s' %
(fn, self.sm, self.t_storage))
self.mat = DyMat.DyMatFile(res_fn)
self.pxml = ProcesXML(xml_fn)
def setUp(self): fn = '../examples/Reference_2.mo' res_fn='./Reference_2_res.mat' xml_fn='./Reference_2_init.xml' self.sm=2.8 self.t_storage=9 sim = simulation.Simulator(fn) sim.compile_model() self.pxml=ProcesXML(xml_fn) self.pxml.write_par(par_n=['SM', 't_storage'], par_v=[self.sm, self.t_storage],one=False) sim.compile_sim(args=['-s']) sim.simulate(start=0, stop=10, step=0.1) self.mat=DyMat.DyMatFile(res_fn)
def extractVars(filename, tic=time.time()):
# use just a subset or use all
# vrs_names = ['Systemic1.posterior_tibial_T4_R236.u_C', 'Systemic1.aortic_arch_C2.port_a.pressure']
# vrs_names = d.names(block = 2)
d = DyMat.DyMatFile(filename)
vrs_names = d.names()
timevar = d.abscissa(2)[0]
var_set = {}
var_set['time'] = timevar
for vn in vrs_names:
var_set[vn] = d.data(vn)
print("Opening result ", filename, " in ", time.time() - tic, " s")
return var_set
def test_modelica():
"""
Run the modelica test of STMotab.
"""
fn = './TestSTMotab.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop='1y', step='5m', solver='dassl', nls='homotopy')
res = DyMat.DyMatFile('TestSTMotab_res.mat')
assert res.data("t1")[0] == 31500000.
assert res.data("dnival")[0] == 976.
assert res.data("dnicol")[0] == 2.
cleantest.clean('TestSTMotab')
def get_state_values(self):
"""
Extracts the values of model outputs at the end of modeling time interval from simulation result
:return: Values of model outputs as tuple in order specified in `model_outputs` attribute
"""
self.data = DyMat.DyMatFile('temp_dir/dsres.mat')
for name in self.debug_data:
self.debug_data[name] += self.data[name].tolist()
for name in self.add_names + self.model_input_names + self.rbc_action_names:
if not name in self.debug_data:
self.debug_data.update({name: []})
self.debug_data[name] += self.data[name].tolist()
return
def loadResult(self):
res__ = DyMat.DyMatFile(self.resultName)
res_ = {}
# get result for dymola mat file
for i, req in enumerate(self.requestName):
res_[i] = res__.data(req)
# make time for interpolation
time = numpy.zeros(int(self.simTime / self.deltaTime))
for i in range(1, int(self.simTime / self.deltaTime)):
time[i] = time[i - 1] + self.deltaTime
# interpolation for equibalant time step
res = numpy.zeros((len(time), len(res_)))
for i in range(1, len(res_)):
res[:, i] = numpy.interp(time, res_[0], res_[i])
return res
def setUp(self):
fn = '../examples/Reference_2.mo'
res_fn = './Reference_2_res_0.mat'
xml_fn = './Reference_2_init_0.xml'
#xml_fn2='./Reference_2_init.xml'
self.sm = 2.8
self.t_storage = 9
cmd = ST() + [
'simulate', fn,
'SM=%s' % (self.sm, ),
't_storage=%s' % (self.t_storage, )
]
print("CMD =", cmd)
shell = False
if platform.system() == "Windows":
shell = True
subprocess.run(cmd, shell=shell, check=True)
self.mat = DyMat.DyMatFile(res_fn)
self.pxml = ProcessXML(xml_fn)
modelicavarname = [
'P_net',
'T_in_ref_blk',
'p_high',
'PR',
'pinch_PHX',
'dTemp_HTF_PHX',
'load',
'T_HTF_in',
'T_amb_input',
'eta_gross',
'eta_Q'
]
data = DyMat.DyMatFile('%s_res_0.mat'%(mofile))
#check convergence of the simulation
eta_array = data.data('eta_gross')
written = ''
if len(eta_array)>0:
for name in modelicavarname:
val = data.data(name)[-1]
written+='%s,'%(val)
else:
for name in modelicavarname:
written+='%s,'%(0)
written+='\n'
print(
'################################################### ITERATION %s #########################################################'
% (i + 1))
print(cmd)
with open('cmd.txt', 'w') as a:
a.write(cmd)
a.close()
a = open('cmd.txt', 'a')
a.write('\n%s P_net=%s' % (i + 1, P_net))
a.close()
#Run solartherm
os.system(cmd)
matfile = '%s_res_0.mat' % (mofile)
data = DyMat.DyMatFile(matfile)
#Get the data
eta_gross_array = data.data('eta_gross')
eta_Q_array = data.data('eta_Q')
T_CO2_in = data.data('powerBlock.exchanger.T_CO2_des[1]')[0]
T_HTF_out = data.data('powerBlock.exchanger.T_HTF_des[1]')[0]
delta_Temp = T_HTF_out - T_CO2_in
#If data exists:
if len(eta_gross_array) > 0:
if delta_Temp > 0:
print(
"MODEL CONVERGE, NO TEMPERATURE CROSSING IN PHX, ALL GOOD! CROSSING: %s"
% (delta_Temp))
par_fr = 0.1
eta_rec_assumption = 0.88
T_amb_design = 283.15
P_gross_design = P_net / (1 - par_fr)
T_out_design = 800 + 273.15
T_in_design = 550 + 273.15
os.chdir(
"/home/philgun/solartherm-particle/SolarTherm/Models/CSP/CRS/Receivers")
os.system(
"st_simulate ParticleReceiver1DCalculator.mo SolarMultiple=%s dni_des=%s eta_rec_assumption=%s T_amb_design=%s P_gross_design=%s T_out_design=%s T_in_design=%s"
% (sm, dni_des, eta_rec_assumption, T_amb_design, P_gross_design,
T_out_design, T_in_design))
os.system("rm -rf *.c *.o *.h *.json *.xml *.makefile *.cmake *.bakmo")
resmat = "ParticleReceiver1DCalculator_res_0.mat"
data = DyMat.DyMatFile(resmat)
H_drop = data.data("particleReceiver1D.H_drop")[-1]
print(H_drop)
os.system("rm -rf *.mat")
os.chdir("/home/philgun/solartherm-particle/examples/")
#Generating the efficiency data
n_row = 15 #25 points of Q_in
n_col = 15 #25 points of T_amb
qsolar_val = np.linspace(100e6, 750e6, num=n_row, endpoint=True)
tamb_val = np.linspace(263.15, 323.15, num=n_col, endpoint=True)
meta = []
heading1 = "#1"
heading2 = "#METADATA Efficiency of the receiver Q_in_rcv [W] vs T_amb [K]"
def dy_mat_func(file):
#for n in f.names():
# print(n)
f = dm.DyMatFile(file + ".mat")
time = f.abscissa('HC_B9.T', valuesOnly=True)
B9_T = f.data('HC_B9.T')-273.15
A7_T = f.data('HC_A7.T')-273.15
A2_T = f.data('HC_A2.T')-273.15
A11_T = f.data('HC_A11.T')-273.15
B3_T = f.data('HC_B3.T')-273.15
#speed
v = f.data('Speed.y[1]')
#Perscribed heat flow (conversion from W to kW)
Q = f.data('timeTable.y[1]')/1000
#Inlet and outlet temperature of HE or Radiator
fi = f.data('fluid_inlet.y')
fo = f.data('fluid_outlet.y')
#Conversion of arrays to lists
list1 = time.tolist()
list2 = B9_T.tolist()
list3 = A7_T.tolist()
list4 = A2_T.tolist()
list5 = A11_T.tolist()
list6 = B3_T.tolist()
list7 = fi.tolist()
list8 = fo.tolist()
list9 = v.tolist()
list10 = Q.tolist()
#Plots
f, axarr = plt.subplots(2, 2, figsize=(14, 10))
axarr[0, 0].plot(list1, list2, label='T$_{B9}$')
axarr[0, 0].plot(list1, list3, label='T$_{A7}$')
axarr[0, 0].plot(list1, list4, label='T$_{A2}$')
axarr[0, 0].plot(list1, list5, label='T$_{A11}$')
axarr[0, 0].plot(list1, list6, label='T$_{B3}$')
axarr[0, 0].set_xlabel("Time [s]", fontsize=10)
axarr[0, 0].set_ylabel("Temperature $[^{\circ}C]$", fontsize=10)
axarr[0, 0].autoscale(tight=True)
axarr[0, 0].grid(True)
axarr[0, 0].legend()
#axarr[0, 0].set_title(file)
axarr[0, 1].plot(list1, list7, label='T$_{fluid\; inlet}$')
axarr[0, 1].plot(list1, list8, label='T$_{fluid\; outlet}$')
axarr[0, 1].set_xlabel("Time [s]", fontsize=10)
axarr[0, 1].set_ylabel("Temperature $[^{\circ}C]$", fontsize=10)
axarr[0, 1].autoscale(tight=True)
axarr[0, 1].grid(True)
axarr[0, 1].legend()
#axarr[0, 1].set_title(file)
axarr[1, 0].plot(list1, list9)
axarr[1, 0].set_xlabel("Time [s]", fontsize=10)
axarr[1, 0].set_ylabel("Velocity [km/h]", fontsize=10)
axarr[1, 0].autoscale(tight=True)
axarr[1, 0].grid(True)
#axarr[1, 0].set_title(file)
axarr[1, 1].plot(list1, list10)
axarr[1, 1].set_xlabel("Time [s]", fontsize=10)
axarr[1, 1].set_ylabel("Q [kW]", fontsize=10)
axarr[1, 1].autoscale(tight=True)
axarr[1, 1].grid(True)
# axarr[1, 1].set_title(file)
plt.subplots_adjust(wspace=0.25, hspace=0.25)
plt.suptitle(file)
plt.savefig(file + "_COMPLETE.pdf", format='pdf')
plt.show()
def dy_mat_func_inverter(file):
#for n in f.names():
# print(n)
f = dm.DyMatFile(file + ".mat")
#Stores values from .mat file to numpy array
time = f.abscissa('Chip1.T', valuesOnly=True)
T1 = f.data('Chip1.T') - 273.15
T2 = f.data('DC.T') - 273.15
T3 = f.data('Housing_1.T') - 273.15
T4 = f.data('Housing_pins.T') - 273.15
T5 = f.data('Vapor_chamber.T') - 273.15
T6 = f.data('Insulation.T') - 273.15
#Rejected heat flow [W]
Q = f.data('volume.q.Q_flow')
#Conversion of arrays to lists
list1 = time.tolist()
list2 = T1.tolist()
list3 = T2.tolist()
list4 = T3.tolist()
list5 = T4.tolist()
list6 = T5.tolist()
list7 = T6.tolist()
list8 = Q.tolist()
#Dataframes for plotting
data1 = pd.DataFrame({
'time': list1,
'T$_{chip}$': list2,
'T$_{AC/DC\; copper}$': list3,
'T$_{housing}$': list4,
'T$_{pins}$': list5,
'T$_{vapor\; chamber}$': list6,
'T$_{insulation}$': list7
})
data2 = pd.DataFrame({'time': list1, 'Q [W]': list8})
xmin = 0
xmax = max(list1)
ymin1 = min(list2)
ymax1 = max(list2)
ymin2 = min(list8)
ymax2 = max(list8)
print("Max temperature for case " + file + ": " + str(round(ymax1, 2)) +
" degC.")
with open("Results.txt", "a") as f:
f.write("Max temperature for case " + file + ": " +
str(round(ymax1, 2)) + " degC.\n")
# data1.plot(x='time')
# plt.xlabel("Time [s]")
# plt.ylabel("Temperature $[^{\circ}C]$")
# plt.xlim(xmin, xmax)
# plt.ylim(ymin1, ymax1+5)
## plt.autoscale(tight=True)
# plt.grid(True)
# plt.title(file)
# plt.savefig(file + "_Inverter_T.png")
# plt.show()
#
# data2.plot(x='time')
# plt.xlabel("Time [s]")
# plt.ylabel("Q [W]")
# plt.xlim(xmin, xmax)
# plt.ylim(ymin2, ymax2+5)
## plt.autoscale(tight=True)
# plt.grid(True)
# plt.title(file)
# plt.legend().remove()
# plt.savefig(file + "_Q.png")
# plt.show()
# #All plots
f, axarr = plt.subplots(2, sharex=True, figsize=(15, 10))
axarr[0].plot(list1, list2, label='T$_{chip}$')
axarr[0].plot(list1, list3, label='T$_{AC/DC\; copper}$')
axarr[0].plot(list1, list4, label='T$_{housing}$')
axarr[0].plot(list1, list5, label='T$_{pins}$')
axarr[0].plot(list1, list6, label='T$_{vapor\; chamber}$')
axarr[0].plot(list1, list7, label='T$_{insulation}$')
axarr[0].set_xlabel("Time [s]", fontsize=10)
axarr[0].set_ylabel("Temperature $[^{\circ}C]$", fontsize=10)
axarr[0].set_xlim(xmin, xmax)
axarr[0].set_ylim(ymin1, ymax1 + 5)
# axarr[0].autoscale(tight=True)
axarr[0].grid(True)
axarr[0].legend()
# plt.xlim((0,694))
# axarr[0].set_title(file)
axarr[1].plot(list1, list8)
axarr[1].set_xlabel("Time [s]", fontsize=10)
axarr[1].set_ylabel("Q [W]", fontsize=10)
axarr[1].set_xlim(xmin, xmax)
axarr[1].set_ylim(ymin2, ymax2 + 5)
# axarr[1].autoscale(tight=True)
axarr[1].grid(True)
# axarr[1, 0].set_title(file)
plt.subplots_adjust(wspace=0.25, hspace=0.25)
plt.suptitle(file)
plt.savefig(file + "_complete.png", format='png')
plt.show()
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
# ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import DyMat, DyMat.Export, random
files = ('DoublePendulum_Dymola-7.4.mat',
'DoublePendulum_OpenModelica-1.8.mat',
'DoublePendulum_Dymola-2012.mat',
'DoublePendulum_Dymola-2012-SaveAs.mat',
'DoublePendulum_Dymola-2012-SaveAsPlotted.mat' )
formats = DyMat.Export.formats.keys()
for fi in files:
# open file
df = DyMat.DyMatFile(fi)
# pick a maximum of 30 random variable names
n = df.names()
x = min(len(n), 30)
va = random.sample(df.names(), x)
# do export
for fo in formats:
print('Exporting %s to %s' % (fi, fo))
DyMat.Export.export(fo, df, va)
def dy_mat_func(file):
#for n in f.names():
# print(n)
f = dm.DyMatFile(file + ".mat")
#Stores values from .mat file to numpy array
time = f.abscissa('MotorLeft.T', valuesOnly=True)
MotorL = f.data('MotorLeft.T') - 273.15
MotorR = f.data('MotorRight.T') - 273.15
#speed
v = f.data('Speed.y[1]')
#Perscribed heat flow (conversion from W to kW)
Q_L = f.data('timeTable1.y[1]') / 1000
Q_R = f.data('timeTable2.y[1]') / 1000
#Inlet and outlet temperature of HE or Radiator
fi = f.data('HE_inlet1.y')
fo = f.data('HE_outlet1.y')
#Conversion of arrays to lists
list1 = time.tolist()
list2 = MotorL.tolist()
list3 = MotorR.tolist()
list4 = fi.tolist()
list5 = fo.tolist()
list6 = v.tolist()
list7 = Q_L.tolist()
list8 = Q_R.tolist()
#Average heat flow
list9 = averageQ(list7)
list10 = averageQ(list8)
#Dataframes for plotting
data1 = pd.DataFrame({
'time': list1,
'T$_{left\; motor}$': list2,
'T$_{right\; motor}$': list3
})
data2 = pd.DataFrame({
'time': list1,
'T$_{fluid\; inlet}$': list4,
'T$_{fluid\; outlet}$': list5
})
data3 = pd.DataFrame({'time': list1, 'Velocity [km/h]': list6})
data4 = pd.DataFrame({
'time': list1,
'Q$_{left\; motor}$ [kW]': list7,
'Q$_{right\; motor}$ [kW]': list8,
'Q$_{average\; left}$ [kW]': list9,
'Q$_{average\; right}$ [kW]': list10
})
#fig, ax = plt.subplots()
data1.plot(x='time')
plt.xlabel("Time [s]")
plt.ylabel("Temperature $[^{\circ}C]$")
#plt.xlim((0,694))
#plt.ylim((25,120))
plt.autoscale(tight=True)
plt.grid(True)
plt.title(file)
plt.savefig(file + "_Motor_T.png")
plt.show()
data2.plot(x='time')
plt.xlabel("Time [s]")
plt.ylabel("Temperature $[^{\circ}C]$")
plt.autoscale(tight=True)
#plt.xlim((0,694))
#plt.ylim((20,100))
plt.grid(True)
plt.title(file)
plt.savefig(file + "_HE_T.png")
plt.show()
data3.plot(x='time')
plt.xlabel("Time [s]")
plt.ylabel("Velocity [km/h]")
plt.autoscale(tight=True)
#plt.xlim((0,694))
#plt.ylim((0,100))
plt.grid(True)
plt.title(file)
plt.legend().remove()
plt.savefig(file + "_velocity.png")
plt.show()
data4.plot(x='time')
plt.xlabel("Time [s]")
plt.ylabel("Q [kW]")
#plt.xlim((0,694))
#plt.ylim((0,25))
plt.autoscale(tight=True)
plt.grid(True)
plt.title(file)
#plt.legend().remove()
plt.savefig(file + "_Q.png")
plt.show()
#All plots
f, axarr = plt.subplots(2, 2, figsize=(14, 10))
axarr[0, 0].plot(list1, list2, label='T$_{left\; motor}$')
axarr[0, 0].plot(list1, list3, label='T$_{right\; motor}$')
axarr[0, 0].set_xlabel("Time [s]", fontsize=10)
axarr[0, 0].set_ylabel("Temperature $[^{\circ}C]$", fontsize=10)
axarr[0, 0].autoscale(tight=True)
axarr[0, 0].grid(True)
axarr[0, 0].legend()
#axarr[0, 0].set_title(file)
axarr[0, 1].plot(list1, list4, label='T$_{fluid\; inlet}$')
axarr[0, 1].plot(list1, list5, label='T$_{fluid\; outlet}$')
axarr[0, 1].set_xlabel("Time [s]", fontsize=10)
axarr[0, 1].set_ylabel("Temperature $[^{\circ}C]$", fontsize=10)
axarr[0, 1].autoscale(tight=True)
axarr[0, 1].grid(True)
axarr[0, 1].legend()
#axarr[0, 1].set_title(file)
axarr[1, 0].plot(list1, list6)
axarr[1, 0].set_xlabel("Time [s]", fontsize=10)
axarr[1, 0].set_ylabel("Velocity [km/h]", fontsize=10)
axarr[1, 0].autoscale(tight=True)
axarr[1, 0].grid(True)
#axarr[1, 0].set_title(file)
axarr[1, 1].plot(list1, list7, label='Q$_{left\; motor}$ [kW]')
axarr[1, 1].plot(list1, list8, label='Q$_{right\; motor}$ [kW]')
axarr[1, 1].plot(list1, list9, label='Q$_{average\; left}$ [kW]')
axarr[1, 1].plot(list1, list10, label='Q$_{average\; right}$ [kW]')
axarr[1, 1].set_xlabel("Time [s]", fontsize=10)
axarr[1, 1].set_ylabel("Q [kW]", fontsize=10)
axarr[1, 1].autoscale(tight=True)
axarr[1, 1].grid(True)
axarr[1, 1].legend()
#axarr[1, 1].set_title(file)
plt.subplots_adjust(wspace=0.25, hspace=0.25)
plt.suptitle(file)
plt.savefig(file + "_COMPLETE.png", format='png')
plt.show()
# Build modelica Object Tree
mc_tree = mc.ModelicaClass.BuildObjectTree(lines, root=base_model)
if resetVPV:
mc_tree.buildChildTree([['settings.V_PV_init', 'param']])
vpvn = mc_tree.findNode('settings.V_PV_init')
vpvn.start_val = 0
if mat_file_path is None:
mat_file_path = relative_folder + base_model + '.mat'
mat_date = str(datetime.datetime.fromtimestamp(
os.path.getmtime(mat_file_path)))
# open file with values
d = DyMat.DyMatFile(mat_file_path)
time = d.abscissa(2)[0]
nmsList = d.names(block=2)
#nmsStr = "\r".join(nmsList)
steadyStateInd = TerminalDS.findLowestIndex(steadyStateAt,
time,
returnLast=True)
# pick value
for name in nmsList:
# look for its existence in the states set
n = mc_tree.findNode(name)
if n is None:
continue
# if 'radial_vein_T3_R120' in name:
# -*- coding: utf-8 -*-
#xmodmap -e "keycode 72 = dead_greek dead_greek dead_greek dead_greek"
import DyMat
import numpy as np
from tabulate import tabulate
from solartherm import postproc
fn_1 = '925'
resmat_1 = '/home/philgun/solartherm-particle/examples/%s.mat' %(fn_1)
data_1 = DyMat.DyMatFile(resmat_1)
print(data_1.data('C_hx')[-1])
fn_2 = '2125'
if fn_2 is None :
data_2 = data_1
else:
resmat_2 = '/home/philgun/solartherm-particle/examples/%s.mat' %(fn_2)
data_2 = DyMat.DyMatFile(resmat_2)
if fn_2 is None:
data_set = 1
else:
data_set = 2
num_var = 20
num_parameter = 11
#item_1 = "Turbine / PB Design Efficiency " #powerBlock.turbine.eta_design or eff_blk
item_1 = "Total heliostat area" #SM
def __init__(self, CSV_path, **kwargs):
# Default:
# It WILL NOT interpolate the data according to another "step"
# It WILL replace the . with _ in the variables names
try: # if the kwarg exist, create a variable called x_func
kwargs['interp']
x_func = kwargs['interp']
self.time = kwargs['interp']
except KeyError: # if it doesn't exist:
kwargs['interp'] = 0
try:
kwargs['replaceDot']
except KeyError:
kwargs['replaceDot'] = True
if ".csv" in CSV_path: # User enters with an CSV file
df = pd.read_csv(
CSV_path
) # Read the .OUT file and storage it in a pandas data frame
header = df.columns # Header that will be modified to create object variables
header_orig = df.columns # Original header, just like it is in modelica
n_var = len(df.columns) # Number of variables
aa = "" # Add "nothing" to the variables' names and
header = [aa + s for s in header] # Now it is a list of strings
count = [0] * n_var # Storage the number of . in a variable's name
for ii in range(0, n_var):
if kwargs['replaceDot'] == True: # replaces . with _
for jj in header[ii]:
if jj == ".":
header[ii] = header[ii].replace(".", "_")
elif jj == ")":
header[ii] = header[ii].replace(")", "_")
elif jj == "(":
header[ii] = header[ii].replace("(", "_")
else:
for jj in header[ii]:
if jj == ".":
count[ii] = count[ii] + 1
elif jj == ")":
header[ii] = header[ii].replace(")", "_")
elif jj == "(":
header[ii] = header[ii].replace("(", "_")
for kk in range(0, count[ii]):
header[ii] = re.sub(
r'^.*?\.', "", header[ii]
) # Takes everything before the . and replace with nothing
h_str = "self." # Add "nothing" to the variables names and
header = [h_str + s for s in header] # now it is a list of strings
############################################################################
# Interpolate OMEDit Variables with the PSCAD Time variable, if its the case
# and then storage it in a variable with its name
############################################################################
if type(kwargs['interp']
) is not int: # Means the kwarg is a vector
df1 = pd.DataFrame(
) # A X sized DataFrame can't receive a Y sized df, so a new one is created
for ii in range(0, n_var):
if ii == 0:
df1[header_orig[ii]] = x_func
else:
f_lin = interp1d(df[header_orig[0]],
df[header_orig[ii]]
) # x = OMEdit time, y = the variable
df1[header_orig[ii]] = f_lin(x_func)
exec('%s = np.array(%s)' %
(header[ii], 'df1[header_orig[ii]]'))
else:
for ii in range(0, n_var):
exec('%s = np.array(%s)' %
(header[ii], 'df[header_orig[ii]]'))
else: # If user enters with a .MAT file
d = DyMat.DyMatFile(CSV_path)
n_var = len(d.names())
header = [0] * n_var
vec = []
header_lst = list(d.names())
for a in range(0, n_var):
header[a] = "self." + header_lst[a].replace(".", "_")
header[a] = header[a].replace("(", "_")
header[a] = header[a].replace(")", "_")
if type(kwargs['interp']
) is not int: # Means it is an interpolation vector
f_lin = interp1d(
d.abscissa(header_lst[a])[0], d.data(header_lst[a]))
vec = f_lin(self.time)
exec('%s = np.array(%s)' % (header[a], 'vec'))
else:
exec('%s = np.array(%s)' %
(header[a], 'd.data(header_lst[a])'))
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.express as px
import pandas as pd
import DyMat
import postproc
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
# TODO: use argparse or somethng else to get filename
modelica_result_path = "kiss_1_res.mat"
modelica_result = DyMat.DyMatFile(modelica_result_path)
# parameters for visualisation
tmax = 1000
every = 5
# -----------------------------------------
# Cell temperatures vs. time, as facet plot
# -----------------------------------------
k = 0 # plot fwd cells only
df_tcell = postproc.read_tcell(modelica_result,
every=every).query(f'k=={k} & t<{tmax}')
df_tcell["Tcell"] -= 273.15
fig_tcell = px.line(df_tcell,
x="t",
y="Tcell",
def test1(self):
global VERBOSE, RUNSIM, PLOTME
file_name = 'PhysicalParticleCO21D'
#file_name = 'PhysicalParticleSystem1D'
fn = ('%s.mo' % (file_name, ))
print "Modelica File Name = " + fn
sim = simulation.Simulator(fn)
resfn = sim.model + '_res.mat'
print "Modelica File Result Name = " + resfn
if VERBOSE: print "RUNNING SETUP"
if RUNSIM == 1:
if VERBOSE: print "COMPILING MODEL"
sim.compile_model(args=['-d=bltdump'])
if VERBOSE: print "COMPILING SIM"
sim.compile_sim(args=['-s'])
if VERBOSE: print "SOLVING MODEL"
reporting_interval = 1800
step_string = '%fs' % (reporting_interval)
stop_time = 365 * 24 * 3600
stop_string = '%fs' % (stop_time)
sim.simulate(start=0,
stop=stop_string,
step=step_string,
maxStep='300s',
solver='dassl',
nls=None
#,lv='LOG_DEBUG,LOG_NLS,LOG_SOLVER'#,LOG_NLS_V'
)
self.res = postproc.SimResult(resfn)
resmatfile = '/home/philgun/solartherm/examples/%s' % (
resfn) #getting the res_mat file
data = DyMat.DyMatFile(
resmatfile) #getting the value inside the resmat file
data2 = DyMat.DyMatFile('/home/philgun/solartherm/examples/%s' %
('PhysicalParticleCO21D_res.mat'))
if file_name == 'PhysicalParticleSystem0D':
rcv = 'receiver.'
elif file_name == 'PhysicalParticleCO21D_v11':
rcv = 'particleReceiver1D_v11.'
else:
rcv = 'particleReceiver1D.'
pb = 'powerBlock.'
if file_name == 'PhysicalParticleSystem1D' or file_name == 'PhysicalParticleCO21D':
N = data.data(rcv +
'N')[1] #getval(rcv + 'N') # getval('%s.N' %(rcv,))
print 'Particle Receiver Discretization = %f cells' % (N)
if VERBOSE:
print("SYSTEM'S RESULTS %s" % (file_name))
print ""
name_var = 'A_field'
var = data.data(name_var)
print 'Heliostat Field Area (m.sq) = %f' % (var[1])
name_var = 'E_elec'
var = data.data(
name_var) #getval (name_var) #('%s.%s' %(sys,name_var))
print 'Energy Per Year (MWh/year) = %f' % (var[-1] * 2.778e-10)
name_var = 'E_total_loses_optical'
var = data.data('heliostatsField.E_total_loses_optical')[
-1] #getval (name_var) #('%s.%s' %(sys,name_var))
print 'Energy losses due to optical (MWh/year) = %f' % (var *
2.778e-10)
name_var = 'H_tower'
var = data.data(name_var)
print 'Tower height (m) = %f' % (var[1])
print ""
print "Receiver's Geometry"
name_var = 'A_rcv'
var = data.data(name_var)
print 'Total receiver area (m.sq) = %f' % (var[1])
name_var = 'H_rcv'
var = data.data(name_var)
print 'Receiver height (m) = %f' % (var[1])
name_var = 'A_rcv'
var = data.data(name_var)
print 'Receiver aperture area (m.sq) = %f' % (var[1])
print ""
print "PLANT'S ANALYTICS" #two type curtailments 1 shutdown the heliostat 2 defocusing
print ""
print "Energy Analytics"
name_var = 'E_resource'
var = data.data(name_var)
print "Annual Sun's Energy coming to the heliostat field before cosine loses and curtailment (MWh/year) = %f" % (
var[-1] * 2.778e-10)
name_var = 'E_helio_incident'
var = data.data(name_var)[-1]
print "Annual energy incident of the heliostat field after curtailment due to low DNI / high windspeed (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_helio_raw'
var = data.data(name_var)[-1]
print "Annual energy delivered by the heliostat field before defocusing curtailment (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_helio_net'
var = data.data(name_var)[-1]
print "Annual energy delivered by the heliostat to the receiver after every curtailments (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_recv_incident'
var = data.data(name_var)[-1]
print "Annual energy delivered to the receiver by heliostat (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_recv_net'
var = data.data(name_var)[-1]
print "Annual energy absorbed by the working fluid in the receiver (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_pb_input'
var = data.data(name_var)[-1]
print "Annual energy delivered to the power block (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_pb_gross'
var = data.data(name_var)[-1]
print "Annual energy produced by the turbine's shaft (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_pb_net'
var = data.data(name_var)[-1]
print "Annual net energy produced by the system (MWh/year) = %f" % (
var * 2.778e-10)
print '#################################################################################################################'
print ""
print "Efficiency Analytics"
name_var = 'eta_curtail_off'
var = data.data(name_var)[-1]
print "Annual Efficiency of the heliostat due to low DNI/high windspeed curtailment = %f" % (
var)
name_var = 'eta_optical'
var = data.data(name_var)[-1]
print "Annual Efficiency of the heliostat due to field efficiency = %f" % (
var)
name_var = 'he_av_design'
var = data.data(name_var)[1]
print "Annual Efficiency of the heliostat due availability = %f" % (
var)
name_var = 'eta_curtail_defocus'
var = data.data(name_var)[-1]
print "Annual Efficiency of the heliostat due to defocus curtailment = %f" % (
var)
if resfn == 'PhysicalParticleCO21D_res.mat' or resfn == 'PhysicalParticleSystem1D._res.mat':
print "Annual Efficiency of the receiver due to absorption = %s" % (
'N/A')
else:
name_var = 'eta_recv_abs'
var = data.data(name_var)[-1]
print "Annual Efficiency of the receiver due to absorption = %s" % (
'N/A')
name_var = 'eta_recv_thermal'
var = data.data(name_var)[-1]
print "Annual Efficiency of the receiver due to heat losses and physics phenomena in the receiver = %f" % (
var)
name_var = 'eta_storage'
var = data.data(name_var)[-1]
print "Annual Efficiency of the storage due to losses in the storage system = %f" % (
var)
name_var = 'eta_pb_gross'
var = data.data(name_var)[-1]
print "Annual Efficiency of the power block (ratio between power gross power block / heat input to the heat exchanger) = %f" % (
var)
name_var = 'eta_pb_net'
var = data.data(name_var)[-1]
print "Annual Efficiency of the power block (ratio between net power produced by power block sub system / power produced by turbine shaft) = %f" % (
var)
name_var = 'eta_solartoelec'
var = data.data(name_var)[-1]
print "Annual Efficiency of system (solar energy / generated electrical energy) = %f" % (
var)
print '#################################################################################################################'
print "TOTAL PLANT'S COST (million AUD) = %f " % (
data.data('C_cap')[1] / 1e6)
print "TOTAL EQUIPMENTS COST (million AUD) = %f " % (
data.data('C_cap_total')[1] / 1e6)
print "Contingency, indirect and construction cost constants = %f" % (
(data.data('r_contg')[1] + 1) *
(data.data('r_indirect')[1] + 1) *
(data.data('r_cons')[1] + 1))
print ""
print "Annual OnM (million AUD) = %f " % (data.data('C_year')[1] /
1e6)
print '#################################################################################################################'
print ""
print "Site's, land and heliostat field's cost (million AUD) = %f" % (
(data.data('C_field')[1] + data.data('C_site')[1] +
data.data('C_land')[1]) / 1e6)
name_var = 'C_field'
var = data.data(name_var)[1]
print 'Capital cost of the solar field (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_site'
var = data.data(name_var)[1]
print 'Capital cost of site improvement work (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_land'
var = data.data(name_var)[1]
print 'Capital cost of land (million AUD) = %f' % ((var) / 1e6)
print '#################################################################################################################'
print ""
print "Falling particle receiver sub-system cost (million AUD)= %f" % (
(data.data('C_receiver')[1]) / 1e6)
name_var = 'C_tower'
var = data.data(name_var)[1]
print 'Capital cost of the tower (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_fpr'
var = data.data(name_var)[1]
print 'Capital cost of the falling particle receiver (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_lift_rec'
var = data.data(name_var)[1]
print 'Capital cost of the receiver lift (million AUD) = %f' % (
(var) / 1e6)
print '#################################################################################################################'
print ""
print 'Storage Tank / Bin costs (million AUD)= %f' % (
(data.data('C_storage')[1]) / 1e6)
name_var = 'C_bins'
var = data.data(name_var)[1]
print 'Total capital cost hot and cold storage bins (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_particles'
var = data.data(name_var)[1]
print 'Total capital cost of the particles (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_lift_hx'
var = data.data(name_var)[1]
print 'Capital cost of the heat exchanger lift (power block) (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_lift_cold'
var = data.data(name_var)[1]
print 'Capital cost of the cold storage lift (million AUD) = %f' % (
(var) / 1e6)
print '#################################################################################################################'
if fn == 'PhysicalParticleSystem1D.mo' or fn == 'PhysicalParticleSystem0D.mo':
print 'Power Block sub-system cost (million AUD)= %f' % (
(data.data('C_pb')[1]) / 1e6)
else:
print 'Power Block sub-system cost (million AUD)= %f' % (
(data.data('C_block')[1]) / 1e6)
name_var = 'C_LTR'
var = data.data(pb + name_var)[1]
print 'Capital cost of the low temperature recuperator (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_HTR'
var = data.data(pb + name_var)[1]
print 'Capital cost of the high temperature recuperator (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_cooler'
var = data.data(pb + name_var)[1]
print 'Capital cost of the air-cooler CO2 (million AUD) = %f' % (
var / 1e6)
name_var = 'C_exchanger'
var = data.data(pb + name_var)[1]
print 'Capital cost of the main heat exchager (between CO2 and Particle) (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_generator'
var = data.data(pb + name_var)[1]
print 'Capital cost of the generator (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_mainCompressor'
var = data.data(pb + name_var)[1]
print 'Capital cost of the main compressor (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_reCompressor'
var = data.data(pb + name_var)[1]
print 'Capital cost of the recompressor (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_turbine'
var = data.data(pb + name_var)[1]
print 'Capital cost of the turbine (million AUD) = %f' % (
(var) / 1e6)
print '#################################################################################################################'
print ""
resultclass = postproc.SimResultElec #calling the class of SimResultElec in postproc.py
res = resultclass(
resfn
) #passing the resmatfile into resultclass (postproc.SimResultElec)
result = res.calc_perf(
) #calculating result by calling calc_perf function inside the resultclass class
print '#################################################################################################################'
print "Energy Per Year(MWh/year) = %f, LCOE(USD/MWh) = %f, Capacity Factor(%%)= %f, Spot Market Revenue(million USD/year) = %f" % (
result[0], result[1], result[2], result[3] / 1e6
) #printing the postproc result
#vl = ['N','T_s[1]','T_s[%d]'%(N+1,), 'mdot', 'q_solar','A_ap'
# ,'eta_rec','eps_c[%d]'%(N,)
# ,'H_drop','W_rcv','t_c_in']
#for v in vl:
# print '%s = %f' %(v,getval('revOneDPGv2LookUpTable.%s'%(v,)))
#for v in ['Qdot_rec','Qdot_inc']:
# print '%s = %f MW' %(v,getval('revOneDPGv2LookUpTable.%s'%(v,))/1e6)
#for T in ['T_in','T_out']:
# #print '%s = %f°C'%(T,getval('revOneDPGv2LookUpTable.%s'%(T,))-273.15)
#print 'T_in = %f°C'%(getval('revOneDPGv2LookUpTable.T_s[1]')-273.15)
#print 'T_out= %f°C'%(getval('revOneDPGv2LookUpTable.T_s[%d]'%(N+1,))-273.15)
if PLOTME:
import matplotlib
matplotlib.use('GTKCairo')
import matplotlib.pyplot as pl
#nr = 1; nc = 1; sp=0 #nr = number of row , nc = nuber of column, sp = space between plot
time = data.abscissa(rcv + 'eta_rec', valuesOnly=True)
eta_rec_v11 = data.data(rcv + 'eta_rec')
eta_rec_v9 = data2.data('particleReceiver1D.' + 'eta_rec')
Qdot_rec_v11 = data.data(rcv + 'Qdot_rec') * 100
Qdot_rec_v9 = data2.data('particleReceiver1D.' + 'Qdot_rec') * 100
#print type(y)
#print np.shape(y)
#print type(time)
#print np.shape(time)
#print '**********************************'
#print ''
fig = pl.figure()
#sp+=1; ax1 = pl.subplot(nr,nc,sp)
pl.xlim(170 * 24 * 3600, 173 * 24 * 3600)
pl.plot(time, eta_rec_v11, label='v_11')
pl.plot(time, eta_rec_v9, label='v_09')
pl.legend(fontsize=20)
pl.ylabel('Efficiency of the receiver', fontsize=40)
pl.xlabel('Time', fontsize=40)
pl.title('Receiver efficiency at day 170 to 172', fontsize=40)
pl.show()
pl.xlim(170 * 24 * 3600, 173 * 24 * 3600)
pl.plot(time, Qdot_rec_v11, label='v_11')
pl.plot(time, Qdot_rec_v9, label='v_09')
pl.legend(fontsize=20)
pl.ylabel('Energy (MW)', fontsize=40)
pl.xlabel('Time', fontsize=40)
pl.title('Energy absorbed by particle at day 170 to 172',
fontsize=40)
pl.show()
def load_res(self): self.mat = DyMat.DyMatFile(self.fn) self.load_units()
def dy_mat_func_motor(file):
#for n in f.names():
# print(n)
f = dm.DyMatFile(file + ".mat")
#Stores values from .mat file to numpy array
time = f.abscissa('Shaft.T', valuesOnly=True)
T1 = f.data('Shaft.T') - 273.15
T2 = f.data('Magnet.T') - 273.15
T3 = f.data('Tooth_outerInner.T') - 273.15
T4 = f.data('StatorYoke.T') - 273.15
T5 = f.data('Winding.T') - 273.15
T6 = f.data('Housing_pin.T') - 273.15
T7 = f.data('Housing_casing.T') - 273.15
T8 = f.data('Gearbox.T') - 273.15
#Rejected heat flow [W]
Q = f.data('volume.q.Q_flow')
#Conversion of arrays to lists
list1 = time.tolist()
list2 = T1.tolist()
list3 = T2.tolist()
list4 = T3.tolist()
list5 = T4.tolist()
list6 = T5.tolist()
list7 = T6.tolist()
list8 = T7.tolist()
list9 = T8.tolist()
list10 = Q.tolist()
#Dataframes for plotting
data1 = pd.DataFrame({
'time': list1,
'T$_{shaft}$': list2,
'T$_{magnet}$': list3,
'T$_{stator\; tooth}$': list4,
'T$_{stator\; yoke}$': list5,
'T$_{winding}$': list6,
'T$_{pins}$': list7,
'T$_{casing}$': list8,
'T$_{gearbox}$': list9
})
data2 = pd.DataFrame({'time': list1, 'Q [W]': list10})
xmin = 0
xmax = max(list1)
ymin1 = min(list6)
ymax1 = max(list6)
ymin2 = min(list10)
ymax2 = max(list10)
print("Max temperature for case " + file + ": " + str(round(ymax1, 2)) +
" degC.")
with open("Results.txt", "a") as f:
f.write("Max temperature for case " + file + ": " +
str(round(ymax1, 2)) + " degC.\n")
# data1.plot(x='time')
# plt.xlabel("Time [s]")
# plt.ylabel("Temperature $[^{\circ}C]$")
# plt.xlim(xmin, xmax)
# plt.ylim(ymin1, ymax1+5)
## plt.autoscale(tight=True)
# plt.grid(True)
# plt.title(file)
# plt.savefig(file + "_Inverter_T.png")
# plt.show()
#
# data2.plot(x='time')
# plt.xlabel("Time [s]")
# plt.ylabel("Q [W]")
# plt.xlim(xmin, xmax)
# plt.ylim(ymin2, ymax2+5)
## plt.autoscale(tight=True)
# plt.grid(True)
# plt.title(file)
# plt.legend().remove()
# plt.savefig(file + "_Q.png")
# plt.show()
# #All plots
f, axarr = plt.subplots(2, sharex=True, figsize=(15, 10))
axarr[0].plot(list1, list2, label='T$_{shaft}$')
axarr[0].plot(list1, list3, label='T$_{magnet}$')
axarr[0].plot(list1, list4, label='T$_{stator\; tooth}$')
axarr[0].plot(list1, list5, label='T$_{stator\; yoke}$')
axarr[0].plot(list1, list6, label='T$_{winding}$')
axarr[0].plot(list1, list7, label='T$_{pins}$')
axarr[0].plot(list1, list8, label='T$_{casing}$')
axarr[0].plot(list1, list9, label='T$_{gearbox}$')
axarr[0].set_xlabel("Time [s]", fontsize=10)
axarr[0].set_ylabel("Temperature $[^{\circ}C]$", fontsize=10)
axarr[0].set_xlim(xmin, xmax)
axarr[0].set_ylim(ymin1, ymax1 + 15)
# axarr[0].autoscale(tight=True)
axarr[0].grid(True)
axarr[0].legend()
# plt.xlim((0,694))
# axarr[0].set_title(file)
axarr[1].plot(list1, list10)
axarr[1].set_xlabel("Time [s]", fontsize=10)
axarr[1].set_ylabel("Q [W]", fontsize=10)
axarr[1].set_xlim(xmin, xmax)
axarr[1].set_ylim(ymin2, ymax2 + 5)
# axarr[1].autoscale(tight=True)
axarr[1].grid(True)
# axarr[1, 0].set_title(file)
plt.subplots_adjust(wspace=0.25, hspace=0.25)
plt.suptitle(file)
plt.savefig(file + "_complete.png", format='png')
plt.show()
arg.add_argument('-o',
'--outfile',
nargs=1,
help='write exported data to this file')
arg.add_argument('-f', '--format', nargs=1, help='export data in this format')
arg.add_argument('-p',
'--options',
nargs=1,
help='export options specific to export format')
arg.add_argument('matfile', nargs=1, help='MAT-file')
pargs = arg.parse_args()
dm = DyMat.DyMatFile(pargs.matfile[0])
if pargs.info:
blocks = dm.blocks()
blocks.sort()
for b in blocks:
print('Block %02d:' % b)
s = dm.mat['data_%d' % (b)].shape
v = len(dm.names(b))
print(' %d variables point to %d columns with %d timesteps' %
(v, s[0] - 1, s[1]))
elif pargs.list:
for n in dm.names():
print(n)
BPM='maxBP',
Qlymph='Qlymph [L/day]',
Vint_r='Relative change to interstitial volume',
Vint_excess='Excess interstitial volume [L]',
ESP='ESP',
EDP='EDP',
comp='compensated'))
for i in exp_range:
filename = filePattern % (experiment_type, i)
# filename = R"c:\home\UMICH\Valsalva\Results2\CardiovascularSystem.mat"
try:
print("Loading file %s..." % filename, end='')
tic = timer.time()
datafile = DyMat.DyMatFile(filename)
print("Ok [%ds]. Processing..." % (timer.time() - tic), end='')
except FileNotFoundError:
print(" File %0d not found !" % i)
continue
except:
print(" File %0d failed, show must go on" % i)
# os.system("c:\\Program Files\\Dymola 2021\\bin\\dsres2dsf %s %s" % (filename, filename.replace('.mat', '.sdf'))
continue
time = datafile.abscissa(2)[0]
i_dt = int(
6 / (time[100] / 100)
) # index of mean interval of 6s , measured over range of 100 samples
## Reads parameters of venous terminals for reparametrization
import scipy.io as skipy
import DyMat
from matplotlib import pyplot as plt
import re
import TerminalDS
# filename = 'CardiovascularSystem_ADANExport'
steadyStateAt = 30
filename = '../CardiovascularSystem'
# mat = skipy.loadmat(filename)
d = DyMat.DyMatFile(filename)
time = d.abscissa(2)[0]
nmsList = d.names(block=2)
nmsStr = "\r".join(nmsList)
steadyStateInd = TerminalDS.findLowestIndex(steadyStateAt, time)
# lines = open('terminators_venousRed.txt', 'r').read().splitlines()
lines = open('terminators_venousRedPlus.txt', 'r').read().splitlines()
terminators_venous = TerminalDS.createTerminatorsDS(lines)
name_patt = ["Systemic1.", '']
for t in terminators_venous:
t.C = d.data("".join([name_patt[0], t.name, '.', 'C']))[-1]
t.RA = d.data("".join([name_patt[0], t.name, '.', 'Ra']))[-1]
t.RV = 3.0 * d.data("".join([name_patt[0], t.name, '.', 'Rv']))[-1]
t.I = d.data("".join([name_patt[0], t.name, '.', 'I']))[-1]
def dy_mat_func(file):
#for n in f.names():
# print(n)
f = dm.DyMatFile(file + ".mat")
#Stores values from .mat file to numpy array
time = f.abscissa('HC_B9.T', valuesOnly=True)
B9_T = f.data('HC_B9.T') - 273.15
A7_T = f.data('HC_A7.T') - 273.15
A2_T = f.data('HC_A2.T') - 273.15
A11_T = f.data('HC_A11.T') - 273.15
B3_T = f.data('HC_B3.T') - 273.15
#speed
v = f.data('Speed.y[1]')
#Perscribed heat flow (conversion from W to kW)
Q = f.data('timeTable.y[1]') / 1000
#Inlet and outlet temperature of HE or Radiator
fi = f.data('fluid_inlet.y')
fo = f.data('fluid_outlet.y')
#Conversion of arrays to lists
list1 = time.tolist()
list2 = B9_T.tolist()
list3 = A7_T.tolist()
list4 = A2_T.tolist()
list5 = A11_T.tolist()
list6 = B3_T.tolist()
list7 = fi.tolist()
list8 = fo.tolist()
list9 = v.tolist()
list10 = Q.tolist()
#Dataframes for plotting
data1 = pd.DataFrame({
'time': list1,
'T$_{B9}$': list2,
'T$_{A7}$': list3,
'T$_{A2}$': list4,
'T$_{A11}$': list5,
'T$_{B3}$': list6
})
data2 = pd.DataFrame({
'time': list1,
'T$_{fluid\; inlet}$': list7,
'T$_{fluid\; outlet}$': list8
})
data3 = pd.DataFrame({'time': list1, 'Velocity [km/h]': list9})
data4 = pd.DataFrame({'time': list1, 'Q [kW]': list10})
#fig, ax = plt.subplots()
data1.plot(x='time')
plt.xlabel("Time [s]")
plt.ylabel("Temperature $[^{\circ}C]$")
#plt.xlim((0,694))
#plt.ylim((25,120))
plt.autoscale(tight=True)
plt.grid(True)
plt.title(file)
plt.savefig(file + "_Module_T.png")
plt.show()
data2.plot(x='time')
plt.xlabel("Time [s]")
plt.ylabel("Temperature $[^{\circ}C]$")
plt.autoscale(tight=True)
#plt.xlim((0,694))
#plt.ylim((20,100))
plt.grid(True)
plt.title(file)
plt.savefig(file + "_HE_T.png")
plt.show()
data3.plot(x='time')
plt.xlabel("Time [s]")
plt.ylabel("Velocity [km/h]")
plt.autoscale(tight=True)
#plt.xlim((0,694))
#plt.ylim((0,100))
plt.grid(True)
plt.title(file)
plt.legend().remove()
plt.savefig(file + "_velocity.png")
plt.show()
data4.plot(x='time')
plt.xlabel("Time [s]")
plt.ylabel("Q [kW]")
#plt.xlim((0,694))
#plt.ylim((0,25))
plt.autoscale(tight=True)
plt.grid(True)
plt.title(file)
plt.legend().remove()
plt.savefig(file + "_Q.png")
plt.show()
#All plots
f, axarr = plt.subplots(2, 2, figsize=(14, 10))
axarr[0, 0].plot(list1, list2, label='T$_{B9}$')
axarr[0, 0].plot(list1, list3, label='T$_{A7}$')
axarr[0, 0].plot(list1, list4, label='T$_{A2}$')
axarr[0, 0].plot(list1, list5, label='T$_{A11}$')
axarr[0, 0].plot(list1, list6, label='T$_{B3}$')
axarr[0, 0].set_xlabel("Time [s]", fontsize=10)
axarr[0, 0].set_ylabel("Temperature $[^{\circ}C]$", fontsize=10)
axarr[0, 0].autoscale(tight=True)
axarr[0, 0].grid(True)
axarr[0, 0].legend()
#axarr[0, 0].set_title(file)
axarr[0, 1].plot(list1, list7, label='T$_{fluid\; inlet}$')
axarr[0, 1].plot(list1, list8, label='T$_{fluid\; outlet}$')
axarr[0, 1].set_xlabel("Time [s]", fontsize=10)
axarr[0, 1].set_ylabel("Temperature $[^{\circ}C]$", fontsize=10)
axarr[0, 1].autoscale(tight=True)
axarr[0, 1].grid(True)
axarr[0, 1].legend()
#axarr[0, 1].set_title(file)
axarr[1, 0].plot(list1, list9)
axarr[1, 0].set_xlabel("Time [s]", fontsize=10)
axarr[1, 0].set_ylabel("Velocity [km/h]", fontsize=10)
axarr[1, 0].autoscale(tight=True)
axarr[1, 0].grid(True)
#axarr[1, 0].set_title(file)
axarr[1, 1].plot(list1, list10)
axarr[1, 1].set_xlabel("Time [s]", fontsize=10)
axarr[1, 1].set_ylabel("Q [kW]", fontsize=10)
axarr[1, 1].autoscale(tight=True)
axarr[1, 1].grid(True)
#axarr[1, 1].set_title(file)
plt.subplots_adjust(wspace=0.25, hspace=0.25)
plt.suptitle(file)
plt.savefig(file + "_COMPLETE.pdf", format='pdf')
plt.show()