In [10]:

    

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt, mpld3
import ThermoPyle as TP
import CoolProp.CoolProp as CP
from cytoolz import get
import itertools as it
%matplotlib notebook
mpld3.enable_notebook()
#print(plt.style.available)
plt.style.use(["seaborn-talk","seaborn-notebook","seaborn-paper"])


    

In [9]:

    

%run ../scripts/der_CSV_gen.py


    

    




Iteration 0
    Generating Initial Fluid Object.
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Iteration 54 of 124:
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Iteration 59 of 124:
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Iteration 60 of 124:
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Iteration 61 of 124:
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Iteration 62 of 124:
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Iteration 63 of 124:
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Iteration 66 of 124:
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Iteration 69 of 124:
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Iteration 70 of 124:
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    Success!
    This Iteration: 0 hours, 0 minutes, 9.154 seconds
    Time Elapsed: 0 hours, 21 minutes, 19.105 seconds

Iteration 122 of 124:
    Calculating Column d(U)/d(G)|T
======================================================
    Success!
    This Iteration: 0 hours, 0 minutes, 9.3 seconds
    Time Elapsed: 0 hours, 21 minutes, 28.405 seconds

Iteration 123 of 124:
    Calculating Column d(S)/d(T)|D
======================================================
    Success!
    This Iteration: 0 hours, 0 minutes, 9.169 seconds
    Time Elapsed: 0 hours, 21 minutes, 37.574 seconds

Iteration 124 of 124:
    Calculating Column d(P)/d(G)|S
======================================================
    Success!
    This Iteration: 0 hours, 0 minutes, 9.175 seconds
    Time Elapsed: 0 hours, 21 minutes, 46.75 seconds







    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
C:\Users\at8183jk\Desktop\Drive\Dropsync\School\Winona\ResearchProject\code\scripts\der_CSV_gen.py in <module>()
     67 
     68 
---> 69 myfluid.data["V"] = pd.Series(myfluid.M / myfluid.data["D"], index=myfluid.data.index)
     70 myfluid.refresh()
     71 myfluid.clean()

NameError: name 'pd' is not defined

In [17]:

    

myfluid.data["V"] = pd.Series(myfluid.M / myfluid.data["D"], index=myfluid.data.index)
myfluid.refresh()
myfluid.clean()


    

In [19]:

    

myfluid.write_data("../finalData/", mode="dual", filename="with_derivatives_and_volume")


    

In [26]:

    

rescaled = myfluid.copy()


    

In [23]:

    

varrange = {col:[min(rescaled.data[col]),max(rescaled.data[col])] for col in rescaled.vars}

invars = ["T", "P", "S", "D", "V"]

for var in invars:
    rescaled.data[var] = rescaled.data[var].apply(TP.rescale(get(var, varrange), [0,216]))

rescaled.data["U"] = rescaled.data["U"].apply(TP.rescale(urange, [15, 152]))


    

In [27]:

    

rescaled.write_data("../finalData/", mode="dual", filename="with_derivatives_and_volume_SCALED")


    

In [40]:

    

for i in range(10):
    dU = 0.1*i + 0.1
    uSel = 10 + 10*i
    rescaled.data.ix[np.abs(rescaled.data["U"] - uSel) <= 1, "U"] = rescaled.data.ix[np.abs(rescaled.data["U"] - uSel) <= 1 , "U"] + dU

rescaled.data.ix[np.abs(rescaled.data["d(U)/d(S)|P"] - 400) <= 50, 'U'] = rescaled.data.ix[np.abs(rescaled.data["d(U)/d(S)|P"] - 400) <= 50, 'U'] + 5


    

In [41]:

    

TP.fluid_plot(rescaled)


    

In [25]:

    

myfluid2 = rescaled.copy()
print(myfluid2.vars)
myfluid2.yvar = "S"
myfluid2.vars[1] = "S"
myfluid2.units[1] = "J/kg*K"
#myfluid2.clean()
myfluid2.make_meta()
print(myfluid2.meta)
TP.fluid_plot(myfluid2)


    

    




['T', 'P', 'U', 'S', 'd(U)/d(S)|P', 'd(U)/d(P)|T', 'd(U)/d(T)|P']
pmap({'fluid': 'Water', 'numPoints': [216, 216], 'date': '2017-03-01 @ 10:28:53', 'units': ['K', 'J/kg/K', 'J/kg', 'J/kg/K', 'UnknownVar', 'UnknownVar', 'UnknownVar'], 'yvar': 'S', 'colorMap': 'viridis', 'xvar': 'T', 'vars': ['T', 'S', 'U', 'S', 'd(U)/d(S)|P', 'd(U)/d(P)|T', 'd(U)/d(T)|P'], 'zvar': 'U'})






    















    

In [42]:

    

rescaled.write_data("../finalData/")


    

In [ ]: