在 Coolprop 图表中放置标签

Question

遵循心房结的思路（link）：

from CoolProp.Plots import PropertyPlot

plot = PropertyPlot("Water", 'Ph')
plot.calc_isolines()
ax = plot.axis
ax.text(2000, 100, ' 1', fontsize=10, rotation=45, color='r')
plot.show()

我尝试重现它，在这几行代码中在 Coolprop 图表中引入标签，但没有结果。

知道如何实现这个目标吗？ 可以改进代码。欢迎改进和更改。

这些是代码行：

#pyimport("sys").executable
from numpy import shape as size 
from matplotlib import pyplot as plt
from CoolProp import CoolProp as CP
from CoolProp.Plots import PropertyPlot as CPP #StateContainer
from CoolProp.Plots import SimpleCompressionCycle as CPPSCC

TT =( [[55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55],
[33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]])

n=size(TT)[1]

for i in range(size(TT)[1]):
 pp = CPP("R32", "PH", unit_system="KSI")
 #pp.title("R32 log p-h Diagramm_"+str(i))
 pp.set_axis_limits([-40, 700, 0, 15000])
 pp.xlabel("h [kJ/kg]")
 pp.ylabel("P [kPa]")
 pp.calc_isolines(CP.iQ, num=11)
 cycle = CPPSCC("R32", "PH", unit_system="KSI")
 T0 = TT[1][i]+273.15
 pp.state.update(CP.QT_INPUTS,0.0,T0-0.02) 
 p0 = pp.state.keyed_output(CP.iP)
 T2 = TT[0][i]+273.15
 pp.state.update(CP.QT_INPUTS,1.0,T2+0.02)
 p2 = pp.state.keyed_output(CP.iP)
 pp.calc_isolines(CP.iT, [T0 ,T2 ], num=2)
 pp.props[CP.iT]['color'] = 'green'
 pp.props[CP.iT]['lw'] = '0.5'
 txt ="T0 {:.2f}K /P0 {:.2f}MPa \n T2 {:.2f}K /P2 {:.2f}MPa".format(T0,p0/1e6,T2,p2/1e6)        
 pp.title("R32 log p-h Diagramm \n "+txt)
 
 pa=0.996424*100000
 h=CP.PropsSI("H","P",pa,"T",T0,"R32")
 
 cycle.simple_solve(T0, p0, T2, p2, 0.7, SI=True)
 cycle.steps =50
 sc = cycle.get_state_changes()
 #label 1
 pp.draw_process(sc,line_opts={'color':'blue', 'lw':1.5})
 pp.grid()
 ax = pp.axis
 lb1="{:.2f}K".format(T0)
 ax.text(h, pa, lb1, fontsize=10, rotation=45, color='r')

 plt.close(cycle.figure)
 pp.show()

Answer 1

在我的示例中，如上所示，标签无法显示，因为计算单位与图表的单位不匹配。 为了能够可视化单位和值，请使用属性：_cycle_states。

from numpy import shape as size 
from matplotlib import pyplot as plt
from CoolProp import CoolProp as CP
from CoolProp.Plots import PropertyPlot as CPP #StateContainer
from CoolProp.Plots import SimpleCompressionCycle as CPPSCC

import matplotlib.transforms as mtransforms


TT =( [[55, 55, 55, 55, 55],
    [33, 34, 35, 36, 37]])

n=size(TT)[1]

for i in range(size(TT)[1]):
 pp = CPP("R32", "PH", unit_system="KSI")
 #pp.title("R32 log p-h Diagramm_"+str(i))
 pp.set_axis_limits([-40, 700, 0, 15000])
 pp.xlabel("h [kJ/kg]")
 pp.ylabel("P [kPa]")
 pp.calc_isolines(CP.iQ, num=11)
 cycle = CPPSCC("R32", "PH", unit_system="KSI")
 T0 = TT[1][i]+273.15
 pp.state.update(CP.QT_INPUTS,0.0,T0-0.02) 
 p0 = pp.state.keyed_output(CP.iP)
 T2 = TT[0][i]+273.15
 pp.state.update(CP.QT_INPUTS,1.0,T2+0.02)
 p2 = pp.state.keyed_output(CP.iP)
 pp.calc_isolines(CP.iT, [T0 ,T2 ], num=2)
 pp.props[CP.iT]['color'] = 'green'
 pp.props[CP.iT]['lw'] = '0.5'   
 pp.title("R32 log p-h Diagramm ")
 
 cycle.simple_solve(T0, p0, T2, p2, 0.7, SI=True)
 cycle.steps =50
 sc = cycle.get_state_changes()
 pp.draw_process(sc,line_opts={'color':'blue', 'lw':1.5})
 pp.grid()
 #View the values and units used in the calculation 
 print(cycle._cycle_states)
 #LABELS
 fig = pp.figure
 ax = pp.axis
 trans_offset = mtransforms.offset_copy(ax.transData, fig=fig,
                                       x=-0.12, y=0.10, units='inches')
 
 #label 1
 T0=cycle._cycle_states[0,"T"]
 pa=0.996424#Pressure value selected to place the labels
 h=CP.PropsSI("H","P",pa,"T",T0,"R32")/1000
 lb1="{:.2f}K".format(T0)
 ax.text(h, pa, lb1, fontsize=10, rotation=90, color='r',transform=trans_offset,horizontalalignment='left',verticalalignment='baseline')
 #label 2
 T2=cycle._cycle_states[2,"T"]
 pa=0.996424##Pressure value selected to place the labels
 h=CP.PropsSI("H","P",pa,"T",T2,"R32")/1000
 lb2="{:.2f}K".format(T2)
 ax.text(h, pa, lb2, fontsize=10, rotation=90, color='r',transform=trans_offset,horizontalalignment='left',verticalalignment='baseline')

 #Pressures
 trans_offset = mtransforms.offset_copy(ax.transData, fig=fig,
                                       x=0, y=0.02, units='inches')
 #label p1
 p0=cycle._cycle_states[0,"P"]/1000
 h03=(sum(cycle._cycle_states.H[[0,3]])/2)/1000
 lbp0="{:.2f}KPa".format(p0)
 ax.text(h03, p0, lbp0, fontsize=10, rotation=0, color='b',horizontalalignment='center',transform=trans_offset)
 #label p2
 p1=cycle._cycle_states[1,"P"]/1000
 h12=(sum(cycle._cycle_states.H[[1,2]])/2)/1000
 lbp1="{:.2f}KPa".format(p1)
 ax.text(h12, p1, lbp1, fontsize=10, rotation=0, color='b',horizontalalignment='center',transform=trans_offset)
 
 plt.close(cycle.figure)
 pp.show()

结果显示在图表中。