def draw_ts():
'''
simplified isolines for mixtures in which the calc_isolines() function does not work
Returns
-------
None.
'''
states_sat = StateContainer()
N = 100
sat_l = CP.AbstractState(library, fluid)
sat_v = CP.AbstractState(library, fluid)
Tsat = np.linspace(limits[2],T_crit-0.00001,N)
s_l = np.zeros(N)
s_v = np.zeros(N)
if '&' in fluid:
sat_l.set_mole_fractions([x_molar, 1 - x_molar])
sat_v.set_mole_fractions([x_molar, 1 - x_molar])
for i,T in enumerate(Tsat):
sat_l.update(CP.QT_INPUTS,0,T)
s_l[i] = sat_l.keyed_output(CP.iSmass)
sat_v.update(CP.QT_INPUTS,1,T)
s_v[i] = sat_v.keyed_output(CP.iSmass)
for i in range(N):
states_sat.append({'T':Tsat[i],'S':s_l[i]})
for i in range(N):
states_sat.append({'T':Tsat[N-1-i],'S':s_v[N-1-i]})
with NoStdStreams():
pp.draw_process(states_sat,line_opts={'color':'black','linewidth':0.3})
for x in range(1,10):
states_x = StateContainer()
for i in range(3,N):
s = x/10 * s_l[i] + (1-x/10) * s_v[i]
states_x.append({'T':Tsat[i],'S':s})
with NoStdStreams():
pp.draw_process(states_x,line_opts={'color':'black','linewidth':0.1})
def create_ts_plot(states: list, fluid: str):
cycle_states = StateContainer()
# plot only displays a dot for the state if it occurs twice
merged_states = []
for state in states:
merged_states.append(state['data'])
if state['marker']:
merged_states.append(state['data'])
states = merged_states
i = 0
for state in states:
cycle_states[i, 'P'] = state['P']
cycle_states[i]['T'] = state['T']
cycle_states[i]['S'] = state['S']
cycle_states[i]['H'] = state['H']
i += 1
plot = PropertyPlot(fluid, 'TS', tp_limits='ORC')
plot.calc_isolines(CP.iQ, num=2)
plot.calc_isolines(CP.iP)
style = {}
'''
style = {
'marker': 'o',
'markerfacecolor': 'blue',
'markeredgecolor': 'blue',
'color': matplotlib.colors.to_rgba('#ff0000'),
}
'''
plot.draw_process(cycle_states, line_opts=style)
return plot
def draw_process(self, statecontainer, points=None, line_opts={'color' : 'r', 'lw' : 1.5}):
""" Draw process or cycle from x and y values in axis units
Parameters
----------
statecontainer : CoolProp.Plots.SimpleCycles.StateContainer()
A state container object that contains all the information required to draw the process.
Note that points that appear several times get added to a special of highlighted points.
line_opts : dict
Line options (please see :func:`matplotlib.pyplot.plot`), optional
Use this parameter to pass a label for the legend.
Examples
--------
>>> import CoolProp
>>> from CoolProp.Plots import PropertyPlot
>>> pp = PropertyPlot('HEOS::Water', 'TS', unit_system='EUR')
>>> pp.calc_isolines(CoolProp.iP )
>>> pp.calc_isolines(CoolProp.iHmass )
>>> pp.calc_isolines(CoolProp.iQ, num=11)
>>> cycle = SimpleRankineCycle('HEOS::Water', 'TS', unit_system='EUR')
>>> T0 = 300
>>> pp.state.update(CoolProp.QT_INPUTS,0.0,T0+15)
>>> p0 = pp.state.keyed_output(CoolProp.iP)
>>> T2 = 700
>>> pp.state.update(CoolProp.QT_INPUTS,1.0,T2-150)
>>> p2 = pp.state.keyed_output(CoolProp.iP)
>>> cycle.simple_solve(T0, p0, T2, p2, 0.7, 0.8, SI=True)
>>> cycle.steps = 50
>>> sc = cycle.get_state_changes()
>>> pp.draw_process(sc)
>>> # The same calculation can be carried out in another unit system:
>>> cycle.simple_solve(T0-273.15-10, p0/1e5, T2-273.15+50, p2/1e5-5, 0.7, 0.8, SI=False)
>>> sc2 = cycle.get_state_changes()
>>> pp.draw_process(sc2, line_opts={'color':'blue', 'lw':1.5})
>>> pp.show()
"""
warnings.warn("You called the function \"draw_process\", which is not tested.",UserWarning)
dimx = self.system[self.x_index]
dimy = self.system[self.y_index]
marker = line_opts.pop('marker','o')
style = line_opts.pop('linestyle','solid')
style = line_opts.pop('ls',style)
if points is None: points = StateContainer()
xdata = []
ydata = []
old = statecontainer[len(statecontainer)-1]
for i in statecontainer:
point = statecontainer[i]
if point == old:
points.append(point)
old = point
continue
xdata.append(point[self.x_index])
ydata.append(point[self.y_index])
old = point
xdata = dimx.from_SI(numpy.asarray(xdata))
ydata = dimy.from_SI(numpy.asarray(ydata))
self.axis.plot(xdata,ydata,marker='None',linestyle=style,**line_opts)
xdata = numpy.empty(len(points))
ydata = numpy.empty(len(points))
for i in points:
point = points[i]
xdata[i] = point[self.x_index]
ydata[i] = point[self.y_index]
xdata = dimx.from_SI(numpy.asarray(xdata))
ydata = dimy.from_SI(numpy.asarray(ydata))
line_opts['label'] = ''
self.axis.plot(xdata,ydata,marker=marker,linestyle='None',**line_opts)
def draw_process(self, statecontainer, points=None, line_opts=None):
""" Draw process or cycle from x and y values in axis units
Parameters
----------
statecontainer : CoolProp.Plots.SimpleCycles.StateContainer()
A state container object that contains all the information required to draw the process.
Note that points that appear several times get added to a special of highlighted points.
line_opts : dict
Line options (please see :func:`matplotlib.pyplot.plot`), optional
Use this parameter to pass a label for the legend.
Examples
--------
>>> import CoolProp
>>> from CoolProp.Plots import PropertyPlot
>>> pp = PropertyPlot('HEOS::Water', 'TS', unit_system='EUR')
>>> pp.calc_isolines(CoolProp.iP )
>>> pp.calc_isolines(CoolProp.iHmass )
>>> pp.calc_isolines(CoolProp.iQ, num=11)
>>> cycle = SimpleRankineCycle('HEOS::Water', 'TS', unit_system='EUR')
>>> T0 = 300
>>> pp.state.update(CoolProp.QT_INPUTS,0.0,T0+15)
>>> p0 = pp.state.keyed_output(CoolProp.iP)
>>> T2 = 700
>>> pp.state.update(CoolProp.QT_INPUTS,1.0,T2-150)
>>> p2 = pp.state.keyed_output(CoolProp.iP)
>>> cycle.simple_solve(T0, p0, T2, p2, 0.7, 0.8, SI=True)
>>> cycle.steps = 50
>>> sc = cycle.get_state_changes()
>>> pp.draw_process(sc)
>>> # The same calculation can be carried out in another unit system:
>>> cycle.simple_solve(T0-273.15-10, p0/1e5, T2-273.15+50, p2/1e5-5, 0.7, 0.8, SI=False)
>>> sc2 = cycle.get_state_changes()
>>> pp.draw_process(sc2, line_opts={'color':'blue', 'lw':1.5})
>>> pp.show()
"""
warnings.warn(
"You called the function \"draw_process\", which is not tested.",
UserWarning)
# Default values
line_opts = line_opts or {'color': 'r', 'lw': 1.5}
dimx = self.system[self.x_index]
dimy = self.system[self.y_index]
marker = line_opts.pop('marker', 'o')
style = line_opts.pop('linestyle', 'solid')
style = line_opts.pop('ls', style)
if points is None: points = StateContainer()
xdata = []
ydata = []
old = statecontainer[len(statecontainer) - 1]
for i in statecontainer:
point = statecontainer[i]
if point == old:
points.append(point)
old = point
continue
xdata.append(point[self.x_index])
ydata.append(point[self.y_index])
old = point
xdata = dimx.from_SI(np.asarray(xdata))
ydata = dimy.from_SI(np.asarray(ydata))
self.axis.plot(xdata,
ydata,
marker='None',
linestyle=style,
**line_opts)
xdata = np.empty(len(points))
ydata = np.empty(len(points))
for i in points:
point = points[i]
xdata[i] = point[self.x_index]
ydata[i] = point[self.y_index]
xdata = dimx.from_SI(np.asarray(xdata))
ydata = dimy.from_SI(np.asarray(ydata))
line_opts['label'] = ''
self.axis.plot(xdata,
ydata,
marker=marker,
linestyle='None',
**line_opts)
s_ev,T_ev,T_cf,pinch_ev = hx(fluid,10,M_dot,h[6],h[1],p_low,p_low,T_w_su_ev,M_dot_cw*cp_w)
#%%
from CoolProp.Plots import PropertyPlot
from CoolProp.Plots.SimpleCycles import StateContainer
import pickle
import os
cache_plot = False
if cache_plot:
filename = fluid + '.p'
if os.path.isfile(filename): # Load previously saved plot
pp = pickle.load(open( filename, "rb" ) )
else:
states = StateContainer()
states_hf = StateContainer()
states_cf = StateContainer()
pp = PropertyPlot('HEOS::'+fluid, 'TS')
with NoStdStreams():
pp.calc_isolines()
with open(filename, 'wb') as f:
pickle.dump(pp, f)
else:
states = StateContainer()
states_hf = StateContainer()
states_cf = StateContainer()
pp = PropertyPlot('HEOS::'+fluid, 'TS')
with NoStdStreams():
pp.calc_isolines()
#fluid = 'Pentane[0.697615]&Hexane[0.302385]'
#fluid = 'Butane[0.5]&Hexane[0.5]'
fluid = 'Butane'
library = 'HEOS'
library = 'REFPROP'
limits = [0, 1.75, 250, 550] # limits for plotting
cache_plot = False
if cache_plot:
filename = fluid + '.p'
if os.path.isfile(filename): # Load previously saved plot
pp = pickle.load(open(filename, "rb"))
else:
states = StateContainer()
states_hf = StateContainer()
states_cf = StateContainer()
pp = PropertyPlot(library + '::' + fluid, 'TS')
with NoStdStreams():
pp.calc_isolines()
with open(filename, 'wb') as f:
pickle.dump(pp, f)
else:
states = StateContainer()
states_hf = StateContainer()
states_cf = StateContainer()
pp = PropertyPlot(library + '::' + fluid, 'TS')
# pp.set_axis_limits(limits)
with NoStdStreams():
pp.calc_isolines()