Welcome to Sur’s documentation!

Sur is python library to calculate and plot envelopes and flashes for multicompound mixtures using equation of states.

It have been designed to be easy to use interactively, for example using Jupyter, although it could be used as a “backend” to develop your own programs.

Contents

Install

Sur is still under development (considered in alpha stage), but it’s ready to experiment with.

Attention

By the moment, Sur only works with Python 2.7.x. It may change in future versions.

For Windows users

Under Windows, Sur is easily installable via a recent version of [pip](https://pip.pypa.io/en/stable/). It’s bundle in recents version of Python.

  • Open a command line (Start » Run » cmd.exe) and first, upgrade the version of pip (just in case):

    pip install -U pip

  • Then, in a 32bits OS:

    pip install https://ci.appveyor.com/api/buildjobs/satlj7c3vteww2wi/artifacts/dist/sur-1.0.postf6ee05dfcf5c-cp27-cp27m-win32.whl

  • Or for 64 bits:

    pip install https://ci.appveyor.com/api/buildjobs/0yyuyr7mb4skhk1l/artifacts/dist/sur-1.0.postf6ee05dfcf5c-cp27-cp27m-win_amd64.whl

Note

Those links are for the last stable (but still in develop) versions. You can try newer ones going to https://ci.appveyor.com/project/mgaitan/envelope-sur » Enviroment (x86 or x64) » Artifacts, and copy the the link to the .whl file)

For Linux users

(to do)

Sur crash course

This is a tutorial to dive in the key concepts of Sur and its usage under an interactive session.

Getting up

Sur has an object-oriented design. This means that the library provides classes to interact with. The very first step is to import the classes and some helper functions we will need.

In [1]:

from sur import Mixture, Compound, EosSetup, EosEnvelope, EosFlash, ExperimentalEnvelope, setup_database

We also need to create the database and load the built-in dataset of pure components constants. By default, Sur uses a database in memory, which is not persistence.

In [2]:

setup_database()

We are ready to start.

Define a mixture

As you know, a mixture is two or more compound which have been combined such that each substance retains its own chemical identity. A Mixture in sur is the same: a combination of compounds, each one with its fraction (i.e, the sum of the fractions of all the compounds in the mixture must be 1)

In [3]:

mixture = Mixture()

There are several ways to add compounds to a Mixture instance. For instance, you can use as if it would be a dictionary.

In [4]:

mixture["co2"] = 0.5
mixture["n-decane"] = 0.25
mixture["methane"] = 0.25

In order to facilitate the definition of interaction matrixes, we could sort each fraction by its molecular weight, no matter the order we added them.

In [5]:

mixture.sort()

In [6]:

mixture

Out[6]:

[(<Compound: METHANE>, Decimal('0.25')), (<Compound: CARBON DIOXIDE>, Decimal('0.5')), (<Compound: n-DECANE>, Decimal('0.25'))]

Setup the EoS

To simulate the envelope, we need to choice and configurate an Equation of State. This is done via an EosSetup instance. For example, to use an RK-PR EoS with parameters \(k_{ij}\) and \(l_{ij}\) as constants, we create a setup object like this:

In [7]:

setup = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.CONSTANTS, lij_mode=EosSetup.CONSTANTS)

By default, the interaction parameter between two compounds is 0.0 (however, Sur may provide a better choice when appropiated). To customize the calculation with our own parameters, we can override the default values.

In [8]:

setup.set_interaction('kij', 'methane', 'co2', 0.1)
setup.set_interaction('kij', 'co2', 'n-decane',  0.091)

Out[8]:

<KijInteractionParameter: RKPR [<Compound: CARBON DIOXIDE>, <Compound: n-DECANE>]: 0.091>

A setup object is independent of a mixture. It just define the equation to be used and the bag of parameters to tune it when we simulate an envelope for a particular mixture, but to have interaction between compounds that don’t belong to a mixture is perfectly valid.

After set the interaction parameter, we probably want to see how the interaction matrix looks like for our particular compounds

In [9]:

setup.kij(mixture)

Out[9]:

array([[ 0.   ,  0.1  ,  0.   ],
       [ 0.1  ,  0.   ,  0.091],
       [ 0.   ,  0.091,  0.   ]])

By the way, it’d be also possible to define the whole matrix for a particular mixture at once, using the method setup.set_interaction_matrix()

Simulate the envelope

Having the mixture and the setup, we are able to obtain a the simulated envelope.

In [10]:

envelope = mixture.get_envelope(setup)

In this case, envelope is an instance of EosEnvelope, i.e. an envelope that have been created via an equation of state.

Any kind of envelope has many attributes ready to be inspected. For instance, we have the array of pressure and temperature

In [11]:

envelope.p

Out[11]:

array([  1.44200000e-02,   1.64600000e-02,   2.01600000e-02,
         2.45700000e-02,   2.97800000e-02,   3.59200000e-02,
         4.31100000e-02,   5.14700000e-02,   6.11500000e-02,
         7.22700000e-02,   8.49900000e-02,   9.94400000e-02,
         1.15800000e-01,   1.34100000e-01,   1.54500000e-01,
         1.77100000e-01,   2.02000000e-01,   2.29200000e-01,
         2.58800000e-01,   2.90700000e-01,   3.24900000e-01,
         4.05600000e-01,   5.23400000e-01,   6.71100000e-01,
         8.54900000e-01,   1.08200000e+00,   1.36100000e+00,
         1.70100000e+00,   2.11100000e+00,   2.60400000e+00,
         3.19200000e+00,   3.88700000e+00,   4.70400000e+00,
         5.65700000e+00,   6.75900000e+00,   8.02800000e+00,
         9.47500000e+00,   1.11200000e+01,   1.29700000e+01,
         1.50400000e+01,   1.73400000e+01,   1.98900000e+01,
         2.26900000e+01,   2.57500000e+01,   2.90700000e+01,
         3.26600000e+01,   3.65200000e+01,   4.06600000e+01,
         4.50600000e+01,   4.97300000e+01,   5.46600000e+01,
         5.98400000e+01,   6.52700000e+01,   7.09400000e+01,
         7.71600000e+01,   8.40100000e+01,   9.15900000e+01,
         1.00000000e+02,   1.09400000e+02,   1.18800000e+02,
         1.27600000e+02,   1.35800000e+02,   1.43600000e+02,
         1.50900000e+02,   1.54400000e+02,   1.64100000e+02,
         1.70000000e+02,   1.75400000e+02,   1.80400000e+02,
         1.84800000e+02,   1.88700000e+02,   1.92100000e+02,
         1.95000000e+02,   1.97400000e+02,   1.99300000e+02,
         2.00700000e+02,   2.01200000e+02,   2.01600000e+02,
         2.01800000e+02,   2.02000000e+02,   2.02000000e+02,
         2.01600000e+02,   2.01200000e+02,   2.00700000e+02,
         2.00000000e+02,   1.99200000e+02,   1.98200000e+02,
         1.97100000e+02,   1.95900000e+02,   1.94600000e+02,
         1.93300000e+02,   1.90200000e+02,   1.88200000e+02,
         1.86100000e+02,   1.83900000e+02,   1.81700000e+02,
         1.79400000e+02,   1.74600000e+02,   1.72000000e+02,
         1.66500000e+02,   1.60900000e+02,   1.55200000e+02,
         1.49500000e+02,   1.43900000e+02,   1.38400000e+02,
         1.33100000e+02,   1.28000000e+02,   1.23000000e+02,
         1.18400000e+02,   1.13900000e+02,   1.09600000e+02,
         1.05500000e+02,   1.01700000e+02,   9.79600000e+01,
         9.44300000e+01,   9.10500000e+01,   8.78100000e+01,
         8.47000000e+01,   8.17100000e+01,   7.88300000e+01,
         7.60400000e+01,   7.33500000e+01,   7.07400000e+01,
         6.82100000e+01,   6.57500000e+01,   6.33700000e+01,
         6.10400000e+01,   5.87900000e+01,   5.65900000e+01,
         5.44400000e+01,   5.23600000e+01,   5.03300000e+01,
         4.83500000e+01,   4.64300000e+01,   4.45600000e+01,
         4.27400000e+01,   4.09700000e+01,   3.92500000e+01,
         3.75900000e+01,   3.59700000e+01,   3.44000000e+01,
         3.28800000e+01,   3.14100000e+01,   2.99800000e+01,
         2.86000000e+01,   2.72700000e+01,   2.59800000e+01,
         2.47400000e+01,   2.35400000e+01,   2.23900000e+01,
         2.12800000e+01,   2.02100000e+01,   1.91800000e+01,
         1.81900000e+01,   1.72400000e+01,   1.63300000e+01,
         1.54500000e+01,   1.46200000e+01,   1.38100000e+01,
         1.30500000e+01,   1.23100000e+01,   1.16100000e+01,
         1.09400000e+01,   1.03000000e+01,   9.69100000e+00,
         9.11100000e+00,   8.55800000e+00,   8.03200000e+00,
         7.53200000e+00,   7.05800000e+00,   6.60800000e+00,
         6.18100000e+00,   5.77700000e+00,   5.39400000e+00,
         5.03200000e+00])

In [12]:

envelope.t

Out[12]:

array([ 310.    ,  312.0833,  315.3334,  318.5817,  321.8256,  325.0618,
        328.287 ,  331.4979,  334.6908,  337.8618,  341.0071,  344.1223,
        347.2033,  350.2456,  353.2444,  356.1952,  359.0929,  361.9326,
        364.7092,  367.4176,  370.0526,  375.4492,  381.889 ,  388.4249,
        395.0497,  401.7551,  408.5312,  415.3667,  422.2482,  429.1612,
        436.0893,  443.0145,  449.9174,  456.7773,  463.5724,  470.2797,
        476.8758,  483.3365,  489.6373,  495.7541,  501.6625,  507.3389,
        512.7602,  517.904 ,  522.749 ,  527.2748,  531.462 ,  535.2922,
        538.7482,  541.8137,  544.4731,  546.7121,  548.5169,  549.8788,
        550.8162,  551.236 ,  551.015 ,  549.9858,  547.9151,  544.911 ,
        541.2341,  536.9976,  532.2864,  527.1669,  524.4715,  515.914 ,
        509.8688,  503.5958,  497.1301,  490.5047,  483.751 ,  476.8995,
        469.9794,  463.0191,  456.0457,  449.0857,  445.4863,  441.9006,
        438.332 ,  434.7837,  431.2588,  424.291 ,  420.3194,  416.3945,
        412.5202,  408.7   ,  404.9371,  401.2346,  397.5952,  394.0213,
        390.5151,  383.7132,  379.7462,  375.8867,  372.1359,  368.4946,
        364.9629,  358.2265,  354.6604,  347.9187,  341.4057,  335.2389,
        329.4222,  323.9512,  318.8144,  313.9956,  309.4744,  305.2285,
        301.2344,  297.4685,  293.9078,  290.5301,  287.3146,  284.2421,
        281.2947,  278.4564,  275.7124,  273.0497,  270.4565,  267.9224,
        265.4384,  262.9962,  260.589 ,  258.2107,  255.8562,  253.5209,
        251.2014,  248.8943,  246.5974,  244.3085,  242.0261,  239.7491,
        237.4765,  235.2078,  232.9426,  230.681 ,  228.423 ,  226.1689,
        223.9189,  221.6736,  219.4335,  217.1993,  214.9716,  212.7511,
        210.5385,  208.3345,  206.1399,  203.9553,  201.7815,  199.6192,
        197.4689,  195.3314,  193.2072,  191.097 ,  189.0011,  186.9202,
        184.8547,  182.8049,  180.7714,  178.7545,  176.7545,  174.7718,
        172.8065,  170.8589,  168.9294,  167.0179,  165.1248,  163.2502,
        161.3942,  159.5569,  157.7385,  155.9389,  154.1583,  152.3968,
        150.6543])

There is also equivalent arrays for critical points, if any. In our example there is just one point.

In [13]:

envelope.t_cri, envelope.p_cri

Out[13]:

(array([ 520.3626]), array([ 159.1]))

Plotting

In addition, an envelope object is able to generate a predefined Matplotlib figure. Before run it, if you are using Sur through Jupyter, may be handy to use the magic command to embed matplotlib figures directly in the document (instead of raise a popup window)

In [14]:

%matplotlib inline

In [15]:

fig = envelope.plot()
_images/tutorial_33_0.png

As we saved the figure object (fig), we can use the matplotlib API to manipulate it (changing aspect, size, span, colors..., in fact, anything we want), export, etc.

In [16]:

from matplotlib import pyplot as plt

ax = fig.get_axes()[0]
ax.set_yticks([0] + ax.get_yticks()[1:])
ax.set_ylim((-50/3, 220))
ax.set_title('Sur rocks!')
plt.setp(ax.lines, linewidth=3)
plt.setp(ax.lines[1:], linestyle='--')
fig.set_size_inches(fig.get_size_inches() * 2)
fig

Out[16]:
_images/tutorial_35_0.png

However, if that is too much power to your goal, you can pass some format directives (as in pyplot’s `plot() <http://matplotlib.org/users/pyplot_tutorial.html>`__) directly to the method’s parameters. For example:

In [17]:

envelope.plot(format='k');
_images/tutorial_37_0.png 
In [18]:

envelope.plot(critical_point='^', format='--y');
_images/tutorial_38_0.png

Compare with experimental data

Constrant the simulation against a known experimental dataset for an evelope is possible. Here we’ll mock this experimental data modifing the simulated one, but you should get it from a reliable source

In [19]:

import numpy as np
n = envelope.p.size

p_experimental = envelope.p[np.arange(0, n, 7)]  * 1.1
t_experimental = envelope.t[np.arange(0, n, 7)]
exp_envelope = mixture.experimental_envelope(t_experimental, p_experimental)

In this case, the exp_envelope object is an instance of ExperimentalEnvelope. In many way it works identically than an EosEnvelope (strictly, both are subclasses of the same base class), and they share attribute and methods. Of course, the key difference for an experimental envelope is that we don’t need to calculate, we just set the arrays manually.

Another difference is that the default plot style is slightly different.

In [20]:

exp_fig = exp_envelope.plot()
_images/tutorial_42_0.png

By the way, many envelope’s figures can be chained, passing a base one to the method plot() as the first parameter. For example, here we plot both the simulated and the experimental envelopes in the same figure

In [21]:

envelope.plot(exp_fig)

Out[21]:
_images/tutorial_44_0.png

Calculate a flash

A flash represents a separation of the mixture in two with the same compounds but different fractions. In Sur, we can get a flash instance through the method get_flash()

In [22]:

flash = mixture.get_flash(setup, t=400, p=100)

In [23]:

flash.vapour_mixture

Out[23]:

[(<Compound: METHANE>, Decimal('0.360497')), (<Compound: CARBON DIOXIDE>, Decimal('0.625358')), (<Compound: n-DECANE>, Decimal('0.014145'))]

In [24]:

flash.liquid_mixture.z

Out[24]:

array([ 0.116292,  0.348308,  0.5354  ])

Which is the same than

In [25]:

flash.x

Out[25]:

array([ 0.116292,  0.348308,  0.5354  ])

The liquid_mixture and vapour_mixture attributes are Mixture objects, meaning we can get its own evelopes and the plot all together

In [26]:

le = flash.liquid_mixture.get_envelope(setup)
ve = flash.vapour_mixture.get_envelope(setup)

final_fig = envelope.plot(ve.plot(le.plot()))
_images/tutorial_52_0.png

Advanced examples

Attention

These notebook examples are very raw, created as an internal practice, with no deep explanation of each step done. However, they may be useful to discover further possibilities of Sur.

Modeling Golzapour’s synthetic oil

In [1]:

c = """METHANE
PROPANE
n-PENTANE
n-DECANE
n-HEXADECANE"""

In [2]:

f = """0.8232
0.0871
0.0505
0.0198
0.0194
"""

In [3]:

from sur import Mixture, EosSetup, setup_database
setup_database()

In [4]:

m = Mixture()

In [5]:

m.add_many(c, f)

In [6]:

m.sort()
m

Out[6]:

[(<Compound: METHANE>, Decimal('0.8232')), (<Compound: PROPANE>, Decimal('0.0871')), (<Compound: n-PENTANE>, Decimal('0.0505')), (<Compound: n-DECANE>, Decimal('0.0198')), (<Compound: n-HEXADECANE>, Decimal('0.0194'))]

In [7]:

from itertools import combinations

In [8]:

setup = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.T_DEP, lij_mode=EosSetup.CONSTANTS)

In [9]:

for c1, c2 in combinations(m.compounds, 2):
    t = c1.tc if c1.weight < c2.weight else c2.tc
    setup.set_interaction('tstar', c1, c2, t)

In [10]:

setup.tstar(m)

Out[10]:

array([[   0.   ,  190.564,  190.564,  190.564,  190.564],
       [ 190.564,    0.   ,  369.83 ,  369.83 ,  369.83 ],
       [ 190.564,  369.83 ,    0.   ,  469.7  ,  469.7  ],
       [ 190.564,  369.83 ,  469.7  ,    0.   ,  617.7  ],
       [ 190.564,  369.83 ,  469.7  ,  617.7  ,    0.   ]])

In [11]:

setup.set_interaction('k0', 'methane', 'propane', 0.0572)
setup.set_interaction('k0', 'methane', 'n-pentane', 0.05616)
setup.set_interaction('k0', 'methane', 'n-decane', 0.06891)
setup.set_interaction('k0', 'methane', 'n-hexadecane', 0.14031);

In [12]:

setup.k0(m)

Out[12]:

array([[ 0.     ,  0.0572 ,  0.05616,  0.06891,  0.14031],
       [ 0.0572 ,  0.     ,  0.     ,  0.     ,  0.     ],
       [ 0.05616,  0.     ,  0.     ,  0.     ,  0.     ],
       [ 0.06891,  0.     ,  0.     ,  0.     ,  0.     ],
       [ 0.14031,  0.     ,  0.     ,  0.     ,  0.     ]])

In [13]:

setup.set_interaction('lij', 'methane', 'propane', -0.00272)
setup.set_interaction('lij', 'methane', 'n-pentane', -0.06603)
setup.set_interaction('lij', 'methane', 'n-decane', -0.09227)
setup.set_interaction('lij', 'methane', 'n-hexadecane', -0.12441);

In [14]:

setup.lij(m)

Out[14]:

array([[ 0.      , -0.00272 , -0.06603 , -0.09227 , -0.12441 ],
       [-0.00272 ,  0.      , -0.010835, -0.032481, -0.023269],
       [-0.06603 , -0.010835,  0.      , -0.02353 , -0.012501],
       [-0.09227 , -0.032481, -0.02353 ,  0.      ,  0.049878],
       [-0.12441 , -0.023269, -0.012501,  0.049878,  0.      ]])

In [15]:

envelope = m.get_envelope(setup)

In [17]:

%matplotlib inline

In [19]:

envelope.plot();
_images/examples_Gozalpour_rkpr_17_0.png
Debug attributes

There is possible to see the raw input and output data that sur interchange with the EnvelopeSur.exe fortran program.

In [21]:

print(envelope.input_txt)

5               NC
0.8232  0.0871  0.0505  0.0198  0.0194                  z1,z2...zNC
3                               NMODEL (1:SRK / 2:PR / 3:RKPR)
0  1                    ncomb, nTdep
METHANE(1)
190.564  45.99 0.0115478  0.116530154855 1.16          tc, pc, ohm, vc, zrat
2.30376807604   0.0304337956072   0.5   1.54083758839           ac, b, delta1, k
PROPANE(2)
369.83  42.48 0.152291  0.233012170918 1.16          tc, pc, ohm, vc, zrat
9.80216972295   0.0598748909487   1.663687   1.9574557212               ac, b, delta1, k
0.0572          k0
190.564       tstar
-0.00272                lij
n-PENTANE(3)
469.7  33.7 0.251506  0.366506659349 1.16          tc, pc, ohm, vc, zrat
20.2236971345   0.0936309815449   1.957315   2.28798764446              ac, b, delta1, k
0.05616   0.0          k0
190.564   369.83       tstar
-0.06603   -0.010835            lij
n-DECANE(4)
617.7  21.1 0.492328  0.756468369911 1.16          tc, pc, ohm, vc, zrat
56.6610724692   0.192140038284   2.239538   3.11337933794               ac, b, delta1, k
0.06891   0.0   0.0          k0
190.564   369.83   469.7       tstar
-0.09227   -0.032481   -0.02353                 lij
n-HEXADECANE(5)
723.0  14.0 0.717404  1.34252502769 1.16          tc, pc, ohm, vc, zrat
116.426356444   0.341676477137   2.14291   3.90352446586                ac, b, delta1, k
0.14031   0.0   0.0   0.0          k0
190.564   369.83   469.7   617.7       tstar
-0.12441   -0.023269   -0.012501   0.049878             lij



In [22]:

print(envelope.output_txt)

METHANE(1)
Tc= 190.5640   Pc =  45.9900   Vc =  0.1005   OM = 0.0115
Zc=   0.2916 Zcrat=   1.1600 Zceos=  0.3382 Vceos= 0.1165
ac=   2.3038    b =   0.0304  del1=  0.5000    k = 1.5408
PROPANE(2)
Tc= 369.8300   Pc =  42.4800   Vc =  0.2009   OM = 0.1523
Zc=   0.2775 Zcrat=   1.1600 Zceos=  0.3219 Vceos= 0.2330
ac=   9.8022    b =   0.0599  del1=  1.6637    k = 1.9575
n-PENTANE(3)
Tc= 469.7000   Pc =  33.7000   Vc =  0.3160   OM = 0.2515
Zc=   0.2726 Zcrat=   1.1600 Zceos=  0.3163 Vceos= 0.3665
ac=  20.2237    b =   0.0936  del1=  1.9573    k = 2.2880
n-DECANE(4)
Tc= 617.7000   Pc =  21.1000   Vc =  0.6521   OM = 0.4923
Zc=   0.2679 Zcrat=   1.1600 Zceos=  0.3108 Vceos= 0.7565
ac=  56.6611    b =   0.1921  del1=  2.2395    k = 3.1134
n-HEXADECANE(5)
Tc= 723.0000   Pc =  14.0000   Vc =  1.1573   OM = 0.7174
Zc=   0.2695 Zcrat=   1.1600 Zceos=  0.3127 Vceos= 1.3425
ac= 116.4264    b =   0.3417  del1=  2.1429    k = 3.9035

 Tc, Pc and Vc are given in K, bar and L/mol respectively

   K0ij MATRIX
METHANE(1)
PROPANE(2)           0.05720
n-PENTANE(3)         0.05616   0.00000
n-DECANE(4)          0.06891   0.00000   0.00000
n-HEXADECANE(5)      0.14031   0.00000   0.00000   0.00000

   T* MATRIX
METHANE(1)
PROPANE(2)         190.56400
n-PENTANE(3)       190.56400 369.83000
n-DECANE(4)        190.56400 369.83000 469.70000
n-HEXADECANE(5)    190.56400 369.83000 469.70000 617.70000

   LIJ MATRIX
METHANE(1)
PROPANE(2)          -0.00272
n-PENTANE(3)        -0.06603  -0.01083
n-DECANE(4)         -0.09227  -0.03248  -0.02353
n-HEXADECANE(5)     -0.12441  -0.02327  -0.01250   0.04988

  Combining rules:
  0: Classical or van der Waals

Molar fractions:  0.823 0.087 0.051 0.020 0.019
  x    0.8232E+00  0.8710E-01  0.5050E-01  0.1980E-01  0.1940E-01
  y    0.8083E+00  0.9037E-01  0.5408E-01  0.2300E-01  0.2427E-01
  x    0.8232E+00  0.8710E-01  0.5050E-01  0.1980E-01  0.1940E-01
  y    0.8106E+00  0.8992E-01  0.5354E-01  0.2249E-01  0.2347E-01
  x    0.8232E+00  0.8710E-01  0.5050E-01  0.1980E-01  0.1940E-01
  y    0.8129E+00  0.8946E-01  0.5300E-01  0.2198E-01  0.2270E-01
  x    0.8232E+00  0.8710E-01  0.5050E-01  0.1980E-01  0.1940E-01
  y    0.8132E+00  0.8939E-01  0.5290E-01  0.2190E-01  0.2258E-01
  x    0.8232E+00  0.8710E-01  0.5050E-01  0.1980E-01  0.1940E-01
  y    0.8132E+00  0.8939E-01  0.5290E-01  0.2189E-01  0.2257E-01

    T(K)        P(bar)        D(mol/L)
    310.0000    0.2472E-03    0.9591E-05
    312.0835    0.3052E-03    0.1176E-04
    314.9521    0.4056E-03    0.1549E-04
    317.8332    0.5364E-03    0.2030E-04
    320.7258    0.7057E-03    0.2647E-04
    323.6288    0.9239E-03    0.3434E-04
    326.5410    0.1203E-02    0.4433E-04
    329.4613    0.1560E-02    0.5694E-04
    332.3882    0.2011E-02    0.7278E-04
    335.3203    0.2580E-02    0.9255E-04
    338.2562    0.3294E-02    0.1171E-03
    341.1944    0.4183E-02    0.1475E-03
    344.1330    0.5286E-02    0.1848E-03
    347.0704    0.6646E-02    0.2303E-03
    350.0046    0.8314E-02    0.2857E-03
    352.9337    0.1035E-01    0.3527E-03
    355.8556    0.1282E-01    0.4332E-03
    358.7683    0.1579E-01    0.5294E-03
    361.6694    0.1936E-01    0.6438E-03
    364.5565    0.2361E-01    0.7790E-03
    367.4272    0.2865E-01    0.9380E-03
    370.2788    0.3459E-01    0.1124E-02
    373.1088    0.4156E-01    0.1340E-02
    375.9142    0.4967E-01    0.1590E-02
    378.6923    0.5907E-01    0.1876E-02
    381.4399    0.6989E-01    0.2204E-02
    384.1540    0.8227E-01    0.2576E-02
    386.8314    0.9636E-01    0.2997E-02
    389.4689    0.1123E+00    0.3469E-02
    392.0630    0.1302E+00    0.3995E-02
    394.6103    0.1502E+00    0.4578E-02
    397.1074    0.1723E+00    0.5221E-02
    399.5507    0.1968E+00    0.5926E-02
    401.9367    0.2235E+00    0.6692E-02
    404.2616    0.2526E+00    0.7520E-02
    406.5220    0.2841E+00    0.8409E-02
    408.7141    0.3178E+00    0.9357E-02
    410.8344    0.3537E+00    0.1036E-01
    412.8793    0.3917E+00    0.1142E-01
    414.9101    0.4329E+00    0.1256E-01
    416.9662    0.4784E+00    0.1381E-01
    419.0479    0.5287E+00    0.1519E-01
    421.1556    0.5843E+00    0.1670E-01
    423.2897    0.6457E+00    0.1837E-01
    425.4506    0.7137E+00    0.2020E-01
    427.6385    0.7887E+00    0.2221E-01
    429.8540    0.8717E+00    0.2442E-01
    435.2429    0.1106E+01    0.3061E-01
    440.6600    0.1396E+01    0.3816E-01
    446.0967    0.1751E+01    0.4732E-01
    451.5439    0.2185E+01    0.5835E-01
    456.9909    0.2711E+01    0.7157E-01
    462.4262    0.3345E+01    0.8732E-01
    467.8367    0.4105E+01    0.1060E+00
    473.2085    0.5011E+01    0.1280E+00
    478.5263    0.6083E+01    0.1537E+00
    483.7736    0.7347E+01    0.1838E+00
    488.9328    0.8827E+01    0.2186E+00
    493.9850    0.1055E+02    0.2589E+00
    498.9102    0.1255E+02    0.3052E+00
    503.6871    0.1486E+02    0.3581E+00
    508.2933    0.1750E+02    0.4185E+00
    512.7048    0.2053E+02    0.4871E+00
    516.8961    0.2397E+02    0.5647E+00
    520.8398    0.2787E+02    0.6524E+00
    524.5063    0.3228E+02    0.7510E+00
    527.8631    0.3724E+02    0.8617E+00
    531.8966    0.4504E+02    0.1036E+01
    535.3488    0.5475E+02    0.1252E+01
    537.9048    0.6687E+02    0.1523E+01
    539.1107    0.8209E+02    0.1866E+01
    538.2987    0.1013E+03    0.2305E+01
    534.4547    0.1255E+03    0.2874E+01
    525.9621    0.1564E+03    0.3625E+01
    522.0429    0.1675E+03    0.3905E+01
    517.8064    0.1783E+03    0.4182E+01
    513.2952    0.1887E+03    0.4458E+01
    508.5464    0.1989E+03    0.4732E+01
    503.5934    0.2087E+03    0.5004E+01
    498.4657    0.2181E+03    0.5272E+01
    493.1902    0.2272E+03    0.5538E+01
    487.7914    0.2358E+03    0.5801E+01
    482.2913    0.2441E+03    0.6061E+01
    476.7103    0.2521E+03    0.6317E+01
    471.0667    0.2596E+03    0.6569E+01
    465.3775    0.2667E+03    0.6818E+01
    459.6579    0.2734E+03    0.7063E+01
    453.9218    0.2797E+03    0.7303E+01
    448.1818    0.2856E+03    0.7540E+01
    442.4494    0.2911E+03    0.7772E+01
    436.7347    0.2962E+03    0.7999E+01
    431.0469    0.3010E+03    0.8223E+01
    425.3940    0.3053E+03    0.8442E+01
    419.7833    0.3093E+03    0.8656E+01
    414.2209    0.3129E+03    0.8866E+01
    408.7122    0.3161E+03    0.9072E+01
    403.2617    0.3191E+03    0.9273E+01
    397.8733    0.3216E+03    0.9470E+01
    392.5500    0.3239E+03    0.9663E+01
    387.2942    0.3258E+03    0.9852E+01
    382.0379    0.3274E+03    0.1004E+02
    376.7143    0.3288E+03    0.1023E+02
    371.3183    0.3299E+03    0.1042E+02
    365.8427    0.3307E+03    0.1061E+02
    360.2784    0.3311E+03    0.1080E+02
    354.6136    0.3313E+03    0.1099E+02
    348.8328    0.3311E+03    0.1119E+02
    342.9153    0.3306E+03    0.1139E+02
    336.8332    0.3296E+03    0.1159E+02
    330.5478    0.3282E+03    0.1180E+02
    324.0036    0.3263E+03    0.1202E+02
    317.1145    0.3238E+03    0.1224E+02
    309.7443    0.3206E+03    0.1249E+02
    301.6363    0.3164E+03    0.1275E+02
    292.2243    0.3108E+03    0.1306E+02
    284.4179    0.3054E+03    0.1331E+02
    272.0585    0.2961E+03    0.1371E+02
    265.9509    0.2911E+03    0.1391E+02
    265.6858    0.2909E+03    0.1392E+02

  Number of critical points found:            0
    T(K)        P(bar)        D(mol/L)

Isochores

In [1]:

%config InlineBackend.close_figures=False
%matplotlib inline
from matplotlib import interactive
interactive(False)

In [2]:

from sur import *
setup_database()

In [3]:

m = Mixture()
m.add_many('methane propane n-pentane n-decane n-hexadecane',
           '0.822  0.088  0.050  0.020  0.020')

s = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.T_DEP, lij_mode='constants')


env = m.get_envelope(setup=s)

In [4]:

fig = env.plot()
fig

Out[4]:
_images/examples_isochore_4_0.png 
In [15]:

help(m.get_isochore)

Help on method get_isochore in module sur.models:

get_isochore(self, setup, v, ts, ps, t_sup, t_step=5.0, t_inf=270.0) method of sur.models.Mixture instance
    Get the isochore (isoV) for this mixture, calculated using
    the setup EOS with its selected interaction parameters
    mode.


In [5]:

isochore = m.get_isochore(setup=s, v=10., ts=467.01, ps=3.86, t_sup=465.0, t_step=5.0, t_inf=270.0)

You can get the raw input and output

In [6]:

print(isochore.input_txt)

5               NC
5       nplus
isoV            Spec    v(k), ts and ps
0.822  0.088  0.05  0.02  0.02                  z1,z2...zNC
10.0   467.01    3.86         v(L/mol)+Ts+Ps
465.0  5.0  270.0         T(K)+dT+Tinf
3                               NMODEL (1:SRK / 2:PR / 3:RKPR)
0  1                    ncomb, nTdep
METHANE(1)
190.564  45.99 0.0115478  0.116530154855 1.16          tc, pc, ohm, vc, zrat
2.30376807604   0.0304337956072   0.5   1.54083758839           ac, b, delta1, k
PROPANE(2)
369.83  42.48 0.152291  0.233012170918 1.16          tc, pc, ohm, vc, zrat
9.80216972295   0.0598748909487   1.663687   1.9574557212               ac, b, delta1, k
0.013831          k0
190.564       tstar
-0.047134               lij
n-PENTANE(3)
469.7  33.7 0.251506  0.366506659349 1.16          tc, pc, ohm, vc, zrat
20.2236971345   0.0936309815449   1.957315   2.28798764446              ac, b, delta1, k
0.030221   0.0          k0
190.564   369.83       tstar
-0.084739   -0.010835           lij
n-DECANE(4)
617.7  21.1 0.492328  0.756468369911 1.16          tc, pc, ohm, vc, zrat
56.6610724692   0.192140038284   2.239538   3.11337933794               ac, b, delta1, k
0.068534   0.0   0.0          k0
190.564   369.83   469.7       tstar
-0.145519   -0.032481   -0.02353                lij
n-HEXADECANE(5)
723.0  14.0 0.717404  1.34252502769 1.16          tc, pc, ohm, vc, zrat
116.426356444   0.341676477137   2.14291   3.90352446586                ac, b, delta1, k
0.095928   0.0   0.0   0.0          k0
190.564   369.83   469.7   617.7       tstar
-0.121142   -0.023269   -0.012501   0.049878            lij



In [7]:

print(isochore.output_txt)

  The plus fraction from component            5  is   2.000000000000000E-002
    T(K)   rho(mol/L)   P(bar)    v(L/mol)     beta       betav    xplus   yplus
    iter
  467.01  0.1000E+00  0.3860E+01  0.1000E+02  0.1000E+01  0.1000E+01
  465.00  0.1000E+00  0.3845E+01  0.1000E+02  0.9984E+00  0.9999E+00  0.898332  0.018611   6
  460.00  0.1000E+00  0.3792E+01  0.1000E+02  0.9950E+00  0.9998E+00  0.890882  0.015582   7
  455.00  0.1000E+00  0.3740E+01  0.1000E+02  0.9919E+00  0.9997E+00  0.882580  0.012958   7
  450.00  0.1000E+00  0.3689E+01  0.1000E+02  0.9892E+00  0.9996E+00  0.873347  0.010699   7
  445.00  0.1000E+00  0.3640E+01  0.1000E+02  0.9869E+00  0.9995E+00  0.863099  0.008769   7
  440.00  0.1000E+00  0.3591E+01  0.1000E+02  0.9848E+00  0.9994E+00  0.851757  0.007130   7
  435.00  0.1000E+00  0.3544E+01  0.1000E+02  0.9829E+00  0.9994E+00  0.839247  0.005750   8
  430.00  0.1000E+00  0.3498E+01  0.1000E+02  0.9812E+00  0.9993E+00  0.825509  0.004596   8
  425.00  0.1000E+00  0.3451E+01  0.1000E+02  0.9797E+00  0.9993E+00  0.810500  0.003639   8
  420.00  0.1000E+00  0.3406E+01  0.1000E+02  0.9783E+00  0.9992E+00  0.794204  0.002854   8
  415.00  0.1000E+00  0.3361E+01  0.1000E+02  0.9770E+00  0.9992E+00  0.776641  0.002215   9
  410.00  0.1000E+00  0.3316E+01  0.1000E+02  0.9758E+00  0.9992E+00  0.757877  0.001701   9
  405.00  0.1000E+00  0.3271E+01  0.1000E+02  0.9746E+00  0.9991E+00  0.738030  0.001291   9
  400.00  0.1000E+00  0.3227E+01  0.1000E+02  0.9734E+00  0.9991E+00  0.717280  0.000969   9
  395.00  0.1000E+00  0.3182E+01  0.1000E+02  0.9723E+00  0.9991E+00  0.695871  0.000719   9
  390.00  0.1000E+00  0.3138E+01  0.1000E+02  0.9711E+00  0.9991E+00  0.674107  0.000527   9
  385.00  0.1000E+00  0.3094E+01  0.1000E+02  0.9699E+00  0.9990E+00  0.652340  0.000382   9
  380.00  0.1000E+00  0.3050E+01  0.1000E+02  0.9687E+00  0.9990E+00  0.630950  0.000273   8
  375.00  0.1000E+00  0.3006E+01  0.1000E+02  0.9675E+00  0.9990E+00  0.610313  0.000193   8
  370.00  0.1000E+00  0.2962E+01  0.1000E+02  0.9664E+00  0.9990E+00  0.590768  0.000136   8
  365.00  0.1000E+00  0.2918E+01  0.1000E+02  0.9652E+00  0.9990E+00  0.572588  0.000094   7
  360.00  0.1000E+00  0.2874E+01  0.1000E+02  0.9641E+00  0.9989E+00  0.555955  0.000065   7
  355.00  0.1000E+00  0.2831E+01  0.1000E+02  0.9631E+00  0.9989E+00  0.540952  0.000044   7
  350.00  0.1000E+00  0.2788E+01  0.1000E+02  0.9621E+00  0.9989E+00  0.527568  0.000030   6
  345.00  0.1000E+00  0.2745E+01  0.1000E+02  0.9613E+00  0.9989E+00  0.515708  0.000020   6
  340.00  0.1000E+00  0.2703E+01  0.1000E+02  0.9604E+00  0.9989E+00  0.505214  0.000013   6
  335.00  0.1000E+00  0.2660E+01  0.1000E+02  0.9597E+00  0.9989E+00  0.495883  0.000008   6
  330.00  0.1000E+00  0.2618E+01  0.1000E+02  0.9590E+00  0.9989E+00  0.487479  0.000005   6
  325.00  0.1000E+00  0.2576E+01  0.1000E+02  0.9583E+00  0.9988E+00  0.479748  0.000003   6
  320.00  0.1000E+00  0.2534E+01  0.1000E+02  0.9577E+00  0.9988E+00  0.472422  0.000002   6
  315.00  0.1000E+00  0.2493E+01  0.1000E+02  0.9570E+00  0.9988E+00  0.465218  0.000001   7
  310.00  0.1000E+00  0.2451E+01  0.1000E+02  0.9563E+00  0.9988E+00  0.457840  0.000001   7
  305.00  0.1000E+00  0.2409E+01  0.1000E+02  0.9556E+00  0.9988E+00  0.449965  0.000000   7
  300.00  0.1000E+00  0.2366E+01  0.1000E+02  0.9547E+00  0.9988E+00  0.441244  0.000000   7
  295.00  0.1000E+00  0.2324E+01  0.1000E+02  0.9536E+00  0.9988E+00  0.431283  0.000000   8
  290.00  0.1000E+00  0.2281E+01  0.1000E+02  0.9523E+00  0.9988E+00  0.419647  0.000000   8
  285.00  0.1000E+00  0.2237E+01  0.1000E+02  0.9507E+00  0.9988E+00  0.405877  0.000000   8
  280.00  0.1000E+00  0.2193E+01  0.1000E+02  0.9487E+00  0.9987E+00  0.389552  0.000000   8
  275.00  0.1000E+00  0.2147E+01  0.1000E+02  0.9460E+00  0.9987E+00  0.370439  0.000000   9
  270.00  0.1000E+00  0.2100E+01  0.1000E+02  0.9427E+00  0.9987E+00  0.348747  0.000000   9
  Monophasic Region:
    T(K)   rho(mol/L)   P(bar)    v(L/mol)
  467.01  0.1000E+00  0.3860E+01  0.1000E+02
  472.01  0.1000E+00  0.3910E+01  0.1000E+02
  477.01  0.1000E+00  0.3952E+01  0.1000E+02
  482.01  0.1000E+00  0.3994E+01  0.1000E+02
  487.01  0.1000E+00  0.4036E+01  0.1000E+02
  492.01  0.1000E+00  0.4078E+01  0.1000E+02
  497.01  0.1000E+00  0.4120E+01  0.1000E+02
  502.01  0.1000E+00  0.4162E+01  0.1000E+02
  507.01  0.1000E+00  0.4204E+01  0.1000E+02
  512.01  0.1000E+00  0.4246E+01  0.1000E+02
  517.01  0.1000E+00  0.4288E+01  0.1000E+02
  522.01  0.1000E+00  0.4330E+01  0.1000E+02
  527.01  0.1000E+00  0.4372E+01  0.1000E+02
  532.01  0.1000E+00  0.4414E+01  0.1000E+02
  537.01  0.1000E+00  0.4456E+01  0.1000E+02
  542.01  0.1000E+00  0.4498E+01  0.1000E+02
  547.01  0.1000E+00  0.4540E+01  0.1000E+02
  552.01  0.1000E+00  0.4582E+01  0.1000E+02
  557.01  0.1000E+00  0.4624E+01  0.1000E+02
  562.01  0.1000E+00  0.4666E+01  0.1000E+02
  567.01  0.1000E+00  0.4708E+01  0.1000E+02
  572.01  0.1000E+00  0.4750E+01  0.1000E+02
  577.01  0.1000E+00  0.4792E+01  0.1000E+02
  582.01  0.1000E+00  0.4834E+01  0.1000E+02
  587.01  0.1000E+00  0.4876E+01  0.1000E+02
  592.01  0.1000E+00  0.4918E+01  0.1000E+02
  597.01  0.1000E+00  0.4960E+01  0.1000E+02
  602.01  0.1000E+00  0.5002E+01  0.1000E+02
  607.01  0.1000E+00  0.5044E+01  0.1000E+02
  612.01  0.1000E+00  0.5086E+01  0.1000E+02
  617.01  0.1000E+00  0.5128E+01  0.1000E+02
  622.01  0.1000E+00  0.5170E+01  0.1000E+02
  627.01  0.1000E+00  0.5212E+01  0.1000E+02
  632.01  0.1000E+00  0.5254E+01  0.1000E+02
  637.01  0.1000E+00  0.5296E+01  0.1000E+02
  642.01  0.1000E+00  0.5338E+01  0.1000E+02
  647.01  0.1000E+00  0.5380E+01  0.1000E+02
  652.01  0.1000E+00  0.5422E+01  0.1000E+02
  657.01  0.1000E+00  0.5464E+01  0.1000E+02
  662.01  0.1000E+00  0.5506E+01  0.1000E+02
  667.01  0.1000E+00  0.5548E+01  0.1000E+02
  672.01  0.1000E+00  0.5590E+01  0.1000E+02
  677.01  0.1000E+00  0.5632E+01  0.1000E+02
  682.01  0.1000E+00  0.5674E+01  0.1000E+02
  687.01  0.1000E+00  0.5716E+01  0.1000E+02
  692.01  0.1000E+00  0.5758E+01  0.1000E+02
  697.01  0.1000E+00  0.5800E+01  0.1000E+02
  702.01  0.1000E+00  0.5842E+01  0.1000E+02
  707.01  0.1000E+00  0.5884E+01  0.1000E+02
  712.01  0.1000E+00  0.5926E+01  0.1000E+02
  717.01  0.1000E+00  0.5967E+01  0.1000E+02
  722.01  0.1000E+00  0.6009E+01  0.1000E+02
  727.01  0.1000E+00  0.6051E+01  0.1000E+02
  732.01  0.1000E+00  0.6093E+01  0.1000E+02
  737.01  0.1000E+00  0.6135E+01  0.1000E+02
  742.01  0.1000E+00  0.6177E+01  0.1000E+02
  747.01  0.1000E+00  0.6219E+01  0.1000E+02
  752.01  0.1000E+00  0.6261E+01  0.1000E+02
  757.01  0.1000E+00  0.6303E+01  0.1000E+02
  762.01  0.1000E+00  0.6345E+01  0.1000E+02
  767.01  0.1000E+00  0.6387E+01  0.1000E+02
  772.01  0.1000E+00  0.6429E+01  0.1000E+02
  777.01  0.1000E+00  0.6471E+01  0.1000E+02
  782.01  0.1000E+00  0.6513E+01  0.1000E+02
  787.01  0.1000E+00  0.6554E+01  0.1000E+02
  792.01  0.1000E+00  0.6596E+01  0.1000E+02
  797.01  0.1000E+00  0.6638E+01  0.1000E+02
  802.01  0.1000E+00  0.6680E+01  0.1000E+02
  807.01  0.1000E+00  0.6722E+01  0.1000E+02
  812.01  0.1000E+00  0.6764E+01  0.1000E+02
  817.01  0.1000E+00  0.6806E+01  0.1000E+02
  822.01  0.1000E+00  0.6848E+01  0.1000E+02
  827.01  0.1000E+00  0.6890E+01  0.1000E+02
  832.01  0.1000E+00  0.6932E+01  0.1000E+02
  837.01  0.1000E+00  0.6974E+01  0.1000E+02
  842.01  0.1000E+00  0.7015E+01  0.1000E+02
  847.01  0.1000E+00  0.7057E+01  0.1000E+02
  852.01  0.1000E+00  0.7099E+01  0.1000E+02
  857.01  0.1000E+00  0.7141E+01  0.1000E+02
  862.01  0.1000E+00  0.7183E+01  0.1000E+02
  867.01  0.1000E+00  0.7225E+01  0.1000E+02
  872.01  0.1000E+00  0.7267E+01  0.1000E+02
  877.01  0.1000E+00  0.7309E+01  0.1000E+02
  882.01  0.1000E+00  0.7351E+01  0.1000E+02
  887.01  0.1000E+00  0.7392E+01  0.1000E+02
  892.01  0.1000E+00  0.7434E+01  0.1000E+02
  897.01  0.1000E+00  0.7476E+01  0.1000E+02
  902.01  0.1000E+00  0.7518E+01  0.1000E+02
  907.01  0.1000E+00  0.7560E+01  0.1000E+02
  912.01  0.1000E+00  0.7602E+01  0.1000E+02
  917.01  0.1000E+00  0.7644E+01  0.1000E+02
  922.01  0.1000E+00  0.7686E+01  0.1000E+02
  927.01  0.1000E+00  0.7728E+01  0.1000E+02
  932.01  0.1000E+00  0.7769E+01  0.1000E+02
  937.01  0.1000E+00  0.7811E+01  0.1000E+02
  942.01  0.1000E+00  0.7853E+01  0.1000E+02
  947.01  0.1000E+00  0.7895E+01  0.1000E+02
  952.01  0.1000E+00  0.7937E+01  0.1000E+02
  957.01  0.1000E+00  0.7979E+01  0.1000E+02
  962.01  0.1000E+00  0.8021E+01  0.1000E+02
  967.01  0.1000E+00  0.8063E+01  0.1000E+02
  972.01  0.1000E+00  0.8104E+01  0.1000E+02
  977.01  0.1000E+00  0.8146E+01  0.1000E+02
  982.01  0.1000E+00  0.8188E+01  0.1000E+02
  987.01  0.1000E+00  0.8230E+01  0.1000E+02
  992.01  0.1000E+00  0.8272E+01  0.1000E+02
  997.01  0.1000E+00  0.8314E+01  0.1000E+02
 1002.01  0.1000E+00  0.8356E+01  0.1000E+02

los vectores t y p son recortados en dos partes, como se generan

In [8]:

isochore.t

Out[8]:

array([ 467.01,  465.  ,  460.  ,  455.  ,  450.  ,  445.  ,  440.  ,
        435.  ,  430.  ,  425.  ,  420.  ,  415.  ,  410.  ,  405.  ,
        400.  ,  395.  ,  390.  ,  385.  ,  380.  ,  375.  ,  370.  ,
        365.  ,  360.  ,  355.  ,  350.  ,  345.  ,  340.  ,  335.  ,
        330.  ,  325.  ,  320.  ,  315.  ,  310.  ,  305.  ,  300.  ,
        295.  ,  290.  ,  285.  ,  280.  ,  275.  ,  270.  ])

In [9]:

isochore.p

Out[9]:

array([ 3.86 ,  3.845,  3.792,  3.74 ,  3.689,  3.64 ,  3.591,  3.544,
        3.498,  3.451,  3.406,  3.361,  3.316,  3.271,  3.227,  3.182,
        3.138,  3.094,  3.05 ,  3.006,  2.962,  2.918,  2.874,  2.831,
        2.788,  2.745,  2.703,  2.66 ,  2.618,  2.576,  2.534,  2.493,
        2.451,  2.409,  2.366,  2.324,  2.281,  2.237,  2.193,  2.147,  2.1  ])

In [10]:

isochore.t_monophasic

Out[10]:

array([  467.01,   472.01,   477.01,   482.01,   487.01,   492.01,
         497.01,   502.01,   507.01,   512.01,   517.01,   522.01,
         527.01,   532.01,   537.01,   542.01,   547.01,   552.01,
         557.01,   562.01,   567.01,   572.01,   577.01,   582.01,
         587.01,   592.01,   597.01,   602.01,   607.01,   612.01,
         617.01,   622.01,   627.01,   632.01,   637.01,   642.01,
         647.01,   652.01,   657.01,   662.01,   667.01,   672.01,
         677.01,   682.01,   687.01,   692.01,   697.01,   702.01,
         707.01,   712.01,   717.01,   722.01,   727.01,   732.01,
         737.01,   742.01,   747.01,   752.01,   757.01,   762.01,
         767.01,   772.01,   777.01,   782.01,   787.01,   792.01,
         797.01,   802.01,   807.01,   812.01,   817.01,   822.01,
         827.01,   832.01,   837.01,   842.01,   847.01,   852.01,
         857.01,   862.01,   867.01,   872.01,   877.01,   882.01,
         887.01,   892.01,   897.01,   902.01,   907.01,   912.01,
         917.01,   922.01,   927.01,   932.01,   937.01,   942.01,
         947.01,   952.01,   957.01,   962.01,   967.01,   972.01,
         977.01,   982.01,   987.01,   992.01,   997.01,  1002.01])

In [11]:

isochore.p_monophasic

Out[11]:

array([ 3.86 ,  3.91 ,  3.952,  3.994,  4.036,  4.078,  4.12 ,  4.162,
        4.204,  4.246,  4.288,  4.33 ,  4.372,  4.414,  4.456,  4.498,
        4.54 ,  4.582,  4.624,  4.666,  4.708,  4.75 ,  4.792,  4.834,
        4.876,  4.918,  4.96 ,  5.002,  5.044,  5.086,  5.128,  5.17 ,
        5.212,  5.254,  5.296,  5.338,  5.38 ,  5.422,  5.464,  5.506,
        5.548,  5.59 ,  5.632,  5.674,  5.716,  5.758,  5.8  ,  5.842,
        5.884,  5.926,  5.967,  6.009,  6.051,  6.093,  6.135,  6.177,
        6.219,  6.261,  6.303,  6.345,  6.387,  6.429,  6.471,  6.513,
        6.554,  6.596,  6.638,  6.68 ,  6.722,  6.764,  6.806,  6.848,
        6.89 ,  6.932,  6.974,  7.015,  7.057,  7.099,  7.141,  7.183,
        7.225,  7.267,  7.309,  7.351,  7.392,  7.434,  7.476,  7.518,
        7.56 ,  7.602,  7.644,  7.686,  7.728,  7.769,  7.811,  7.853,
        7.895,  7.937,  7.979,  8.021,  8.063,  8.104,  8.146,  8.188,
        8.23 ,  8.272,  8.314,  8.356])

In [12]:

isochore.rho, isochore.rho_monophasic,

Out[12]:

(array([ 0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1]),
 array([ 0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,
         0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1,  0.1]))

In [13]:

isochore.plot()

Out[13]:
_images/examples_isochore_16_0.png

También se le puede pasar una figura ya generada, para que superponga el nuevo plot

In [14]:

isochore.plot(fig)

Out[14]:
_images/examples_isochore_18_0.png

Advanced plots

In [1]:

%config InlineBackend.close_figures=False
%matplotlib inline
from matplotlib import interactive
interactive(False)

from sur import *
setup_database()

m = Mixture()
m.add_many("methane co2 n-decane", "0.25 0.50 0.25")


In [2]:

s1 = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.CONSTANTS, lij_mode=EosSetup.CONSTANTS)
s1.set_interaction('kij', 'methane', 'co2', .1)
s1.set_interaction('kij', 'co2', 'n-decane',  0.091)
s1.set_interaction('lij', 'co2', 'n-decane',  -0.90)
env1 = m.get_envelope(s1, label="Envelope 1")

In [3]:

s2 = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.CONSTANTS, lij_mode=EosSetup.CONSTANTS)
s2.set_interaction('kij', 'methane', 'co2', .11)
s2.set_interaction('kij', 'co2', 'n-decane',  0.081)
s2.set_interaction('lij', 'co2', 'n-decane',  -0.93)
env2 = m.get_envelope(s2, label="Envelope 2")

In [4]:

from sur.plots import multiplot

In [6]:

fig = multiplot([env1, env2], legends='best')

In [7]:

fig

Out[7]:
_images/examples_legends_6_0.png

You can use the bbox_to_anchor keyword argument to place the legend partially outside the axes and/or decrease the font size.

In [8]:

ax = fig.get_axes()[0]
ax.legend(bbox_to_anchor=(1.1, 1.1))
fig

Out[8]:
_images/examples_legends_8_0.png 
In [9]:

ax.legend(bbox_to_anchor=(1.4, 1))
fig

Out[9]:
_images/examples_legends_9_0.png

Similarly, you can make the legend more horizontal and/or put it at the top of the figure (I’m also turning on rounded corners and a simple drop shadow):

In [10]:

ax.legend(loc='upper center', bbox_to_anchor=(0.5, 1.05),
          ncol=3, fancybox=True, shadow=True)

fig

Out[10]:
_images/examples_legends_11_0.png

Alternatively, you can shrink the current plot’s width, and put the legend entirely outside the axis of the figure

In [11]:

# Shink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])

# Put a legend to the right of the current axis
ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
fig

Out[11]:
_images/examples_legends_13_0.png

And in a similar manner, you can shrink the plot vertically, and put the a horizontal legend at the bottom

In [12]:

# Shink current axis's height by 10% on the bottom
box = ax.get_position()
ax.set_position([box.x0, box.y0 + box.height * 0.1,
                 box.width, box.height * 0.9])

# Put a legend below current axis
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.2),
          fancybox=True, shadow=True, ncol=5)
fig

Out[12]:
_images/examples_legends_15_0.png
Configure fonts
In [13]:

# reset figure
fig = multiplot([env1, env2], legends='upper right')
ax = fig.get_axes()[0]

from matplotlib.font_manager import FontProperties

fontP = FontProperties()
fontP.set_size('small')
fontP.set_family('serif')
fontP.set_weight('bold')

ax.legend(loc='best', prop=fontP)
fig

Out[13]:
_images/examples_legends_17_0.png

Setup a development enviroment

This document is a guide to install an enviroment to contribute to the development of Sur library. It’s fully based on modern Ubuntu Linux distributions (particularly Ubuntu 15.10) but should be straight forward follow this on any other linux distribution.

Install system packages

  1. Install system packages:

    $ sudo apt-get install git python-dev python-pip wine gfortran \
                      g++ libfreetype6-dev libpng12-dev xclip
$ sudo pip install virtualenvwrapper

Note

To code, of course you’ll also need an editor. Could be anyone you prefer! Some people prefers simple ones like gedit (installed by default) or geany. Some other prefers something more geeky like vim or even more complete tools like pydev or ninja-ide.

Make a virtual enviroment

We use virtualenv (using virtualenvwrapper) to isolate our enviroment for other projects and system-wide python packages

  1. Setup virtualenvwrapper

    2.1 Create a directory to hold your virtualenvs:

    mkdir ~/.virtualenvs
mkdir ~/projects
mkdir ~/.pip_download_cache

    2.2 Edit you ~/.bashrc adding these lines:

    export WORKON_HOME=$HOME/.virtualenvs
source /usr/local/bin/virtualenvwrapper.sh
export PROJECT_HOME=$HOME/projects      #folder for new projects. Could be what you want

2.3 And reload that:

$ source ~/.bashrc

  1. Now create the project sur:

    $ mkproject sur
This will create a new virtualenv in the WORKON_HOME binded to a project directory in PROJECT_HOME

Note

Next times, when you want to active the sur’s virtualenv you’ll run:

$ workon sur

When you want to deactive the virtualenv, on any path

(sur)~/projects/sur$ deactivate

Checkout the code

sur’s git repo isn’t public, so you need to have credentials to read and/or write it. Please if you don’t have a Bitbucket account, create one:

  1. Go to https://bitbucket.org/account/signup/ and sign up

  2. Let me know (gaitan@gmail.com) your username and ask for dev permissions on Sur. If you don’t have an user on bitbucket also let me know first. I’ll send and invitation

  3. Setup a ssh-key

    $ ssh-keygen
$ xclip -sel clip < ~/.ssh/id_rsa.pub

and paste this on
https://bitbucket.org/account/user/<your_userr>/ssh-keys/

  4. Then we go:

    (sur)~/projects/sur$ git clone git@bitbucket.org:phasety/envelope-sur.git .
(sur)~/projects/sur$ git checkout develop

  5. Remember to configure your identity (so, your future great code will be recognized):

    (sur)$ git config --global user.name "Juan Perez"
(sur)$ git config --global user.email perez@phasety.com

Install in dev mode

(sur)~/projects/sur$ pip install -U numpy pip jupyter nose (sur)~/projects/sur$ pip install -e .

Tip

The flag -e on the last command means this package will be editable. Every change on the code of Sur will impact automatically. It’s the same than python setup.py develop

Then check if it was installed:

(sur) $ ipython

In [1]: import sur    # may take few seconds to load

Run tests:

(sur) $ nosetests

And open an example notebook for lib usage:

(sur) $ jupyter notebook examples/basic_envelope.ipynb

¡Happy coding!

API reference

sur.apps module

class sur.apps.SurConfig(app_name, app_module)

Bases: django.apps.config.AppConfig

name = 'sur'
verbose_name = 'Sur'

sur.envelope module

sur.envelope_sp module

this is a hack due we couldn’t compile the fortran code using gfortran.

sur.envelope_sp.envelope(env)
sur.envelope_sp.exec_fortran(bin, path, as_out_txt=None, timeout=10)

Execute a fortran program if as_out_txt is read that file and return its content

sur.envelope_sp.flash(fi)
sur.envelope_sp.isochore(ii)
sur.envelope_sp.multiflash(mixture, setup, t, p, v)
sur.envelope_sp.write_input(mixture, eos, t=None, p=[], v=[], ii=None, as_data=False, interactions=None, **kwargs)

if t and p are given, return the path of the folder with a written flashIN.txt

sur.eos module

class sur.eos.SRK

Bases: sur.eos.CubicModel

Soave modification of Redlich–Kwong EOS

MODEL_ID = 1
MODEL_NAME = 'SRK'
class sur.eos.PR

Bases: sur.eos.CubicModel

Peng–Robinson equation of state

MODEL_ID = 2
MODEL_NAME = 'PR'
class sur.eos.RKPR

Bases: sur.eos.CubicModel

RKPR equation of state

MODEL_ID = 3
MODEL_NAME = 'RKPR'
classmethod from_constants(tc, pc, acentric_factor, vc=None, del1=None, rhoLsat_t=(), pvdat=())

Given the constants of a pure compound, returns a tuple of arrays with the same constants adjusted and the arrays of correspond model’s parameters.

Constants requires tc, pc, and acentric_factor as mandatory and vc or del1 or rhoLsat_t=(rhoLsat, T).

If a point pvdat = (P, T) is given, it’s used as a constraint to calculate the vapor pressure

Returns:(constants, model_parameters)

Where:

constants = array([tc, pc, acentric_factor, vc])
models_parameters =  array([ac, b, del1, rk])
classmethod from_parameters(ac, b, del1, rk)

Given the model’s parameters, returns a tuple of arrays with the pure compound constants adjusted and the the ajusted model’s array of parameters.

Returns:(constants, model_parameters)

Where:

constants = array([Tc, Pc, acentric_factor, Vc])
models_parameters =  array([ac, b, del1, rk])
sur.eos.get_eos(model)

sur.manage module

sur.models module

class sur.models.Compound(id, name, formula, formula_extended, tc, tc_unit, pc, pc_unit, vc, vc_unit, acentric_factor, a, b, c, d, delta1, weight)

Bases: django.db.models.base.Model

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception Compound.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

Compound.aliases
Compound.calculate_weight()

An aproximation to determine if a compound is heavier than other

Compound.create_alias(alias)

Create an alias for this compound.

static Compound.from_str(key)
Compound.get_ac(model)

Return the critical value for the attractive parameter for PR, SRK or RKPR

Compound.get_b(model)

Return the temperature dependence of the attractive parameter for PR and the repulsive parameter in SRK and RKPR [l/mol]

Compound.get_delta1()

Return the RK-PR third parameter

Compound.get_k()

Return the parameter for the temperature dependence of the attractive parameter for the RKPR eos

Compound.get_m(model)

Parameter for temperature dependence of the attractive parameter for PR or SRK

Compound.get_pc_unit_display(*moreargs, **morekwargs)
Compound.get_tc_unit_display(*moreargs, **morekwargs)
Compound.get_vc_unit_display(*moreargs, **morekwargs)
Compound.k0interactionparameter_set
Compound.kijinteractionparameter_set
Compound.lijinteractionparameter_set
Compound.mixture_set
Compound.mixturefraction_set
Compound.objects = <sur.models.CompoundManager object>
Compound.tstarinteractionparameter_set
class sur.models.KijInteractionParameter(*args, **kwargs)

Bases: sur.models.AbstractInteractionParameter

Constanst for Kij in mode Kij constant

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception KijInteractionParameter.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

KijInteractionParameter.compounds
KijInteractionParameter.get_eos_display(*moreargs, **morekwargs)
KijInteractionParameter.objects = <sur.models.InteractionManager object>
KijInteractionParameter.setup
KijInteractionParameter.user
class sur.models.LijInteractionParameter(*args, **kwargs)

Bases: sur.models.AbstractInteractionParameter

Lij constanst

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception LijInteractionParameter.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

LijInteractionParameter.compounds
LijInteractionParameter.get_eos_display(*moreargs, **morekwargs)
LijInteractionParameter.objects = <sur.models.InteractionManager object>
LijInteractionParameter.setup
LijInteractionParameter.user
class sur.models.EosFlash(id, mixture_id, t, p, v, rho_l, rho_v, beta_mol, beta_vol, setup_id, vapour_mixture_id, liquid_mixture_id, input_txt, output_txt)

Bases: sur.models.Flash

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception EosFlash.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

EosFlash.as_json()
EosFlash.clean()
EosFlash.get_eos()
EosFlash.get_txt()
EosFlash.interactions
EosFlash.liquid_mixture
EosFlash.mixture
EosFlash.objects = <django.db.models.manager.Manager object>
EosFlash.setup
EosFlash.vapour_mixture
class sur.models.ExperimentalEnvelope(id, mixture_id, p, t, rho, p_cri, t_cri, rho_cri, index_cri, label)

Bases: sur.models.Envelope

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception ExperimentalEnvelope.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

ExperimentalEnvelope.index_cri

A placeholder class that provides a way to set the attribute on the model.

ExperimentalEnvelope.mixture
ExperimentalEnvelope.objects = <django.db.models.manager.Manager object>
ExperimentalEnvelope.p

A placeholder class that provides a way to set the attribute on the model.

ExperimentalEnvelope.p_cri

A placeholder class that provides a way to set the attribute on the model.

ExperimentalEnvelope.plot(fig=None, critical_point=None, marker='s', color='k')

Plot the envelope in a T vs P as a scatter figure

Parameters:
  • figure (Figure instance or None) – If it’ss given, the envelope will be plotted in its last axes. Otherwise a new figure will be created. This is useful to chain multiples plots in the same figure.
  • critical_point (str or None) – Define the marker for the critical point. If it’s None, the point won’t be plotted.
  • marker (str or None) – Define the marker for each experimental point in the envelope. A square by default
  • color (color str) – define the color of the points
Returns:

a Figure instance
ExperimentalEnvelope.rho

A placeholder class that provides a way to set the attribute on the model.

ExperimentalEnvelope.rho_cri

A placeholder class that provides a way to set the attribute on the model.

ExperimentalEnvelope.t

A placeholder class that provides a way to set the attribute on the model.

ExperimentalEnvelope.t_cri

A placeholder class that provides a way to set the attribute on the model.

class sur.models.ExperimentalFlash(id, mixture_id, t, p, v, rho_l, rho_v, beta_mol, beta_vol, vapour_mixture_id, liquid_mixture_id)

Bases: sur.models.Flash

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception ExperimentalFlash.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

ExperimentalFlash.liquid_mixture
ExperimentalFlash.mixture
ExperimentalFlash.objects = <django.db.models.manager.Manager object>
ExperimentalFlash.vapour_mixture
class sur.models.EosEnvelope(id, mixture_id, p, t, rho, p_cri, t_cri, rho_cri, index_cri, label, setup_id, input_txt, output_txt)

Bases: sur.models.Envelope

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception EosEnvelope.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

EosEnvelope.get_txt()
EosEnvelope.index_cri

A placeholder class that provides a way to set the attribute on the model.

EosEnvelope.interactions
EosEnvelope.mixture
EosEnvelope.objects = <django.db.models.manager.Manager object>
EosEnvelope.p

A placeholder class that provides a way to set the attribute on the model.

EosEnvelope.p_cri

A placeholder class that provides a way to set the attribute on the model.

EosEnvelope.rho

A placeholder class that provides a way to set the attribute on the model.

EosEnvelope.rho_cri

A placeholder class that provides a way to set the attribute on the model.

EosEnvelope.save(*args, **kwargs)
EosEnvelope.setup
EosEnvelope.t

A placeholder class that provides a way to set the attribute on the model.

EosEnvelope.t_cri

A placeholder class that provides a way to set the attribute on the model.

class sur.models.EosSetup(id, name, eos, user_id, kij_mode, lij_mode)

Bases: django.db.models.base.Model

CONSTANTS = 'constants'
exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

EosSetup.KIJ_MODE_CHOICES = (('t_dep', 'Kij is temperature dependent'), ('constants', 'kij is a constant for each binary interaction'))
EosSetup.LIJ_MODE_CHOICES = (('zero', 'Lij is zero for each binary interaction'), ('constants', 'Lij is a constant of each binary interaction'))
exception EosSetup.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

EosSetup.T_DEP = 't_dep'
EosSetup.ZERO = 'zero'
EosSetup.eosenvelope_set
EosSetup.eosflash_set
EosSetup.get_eos_display(*moreargs, **morekwargs)
EosSetup.get_interactions(mixture)

returns a sorted dict with the interactions matrix for a given mode and mixture

EosSetup.get_kij_mode_display(*moreargs, **morekwargs)
EosSetup.get_lij_mode_display(*moreargs, **morekwargs)
EosSetup.isochore_set
EosSetup.k0(mixture)
EosSetup.k0interactionparameter_set
EosSetup.kij(mixture)
EosSetup.kijinteractionparameter_set
EosSetup.lij(mixture)
EosSetup.lijinteractionparameter_set
EosSetup.objects = <django.db.models.manager.Manager object>
EosSetup.set_interaction(kind, compound1, compound2, value)

create or update an interaction parameter

EosSetup.set_interaction_matrix(kind, mixture, matrix)

set a matrix as the one returned by setup.kij(mixture) or analogs methods.

kind – ‘lij’, ‘k0’, ‘tstar’, ‘kij’ mixture – the Mixture matrix – could be a string (multiline) or a N x N array

EosSetup.tstar(mixture)
EosSetup.tstarinteractionparameter_set
EosSetup.user
class sur.models.Mixture(id, user_id, name)

Bases: django.db.models.base.Model

Compounds
exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception Mixture.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

Mixture.acentric_factor

return the $omega$ array.

It is the $omega$ of each compound in the mixture as a :class:`numpy.array instance in the same order than self.compounds

Mixture.add(compound, fraction=None)

Add compound fraction to the mixture.

Compound could be a Compound instance or a string passed to Compound.objects.find()

if fraction is None, it is set to the complement to reach self.total_z == Decimal('1.0')

Mixture.add_many(compounds, fractions)

shortcut to add many compounds to the mixture at once.

compounds and fractions could be iterables or strings.

Mixture.as_json()
Mixture.clean()
Mixture.compounds
Mixture.eos_flashes_as_gas
Mixture.eos_flashes_as_liquid
Mixture.eosenvelopes
Mixture.eosflashes
Mixture.experimental_envelope(t, p, rho=None, t_cri=None, p_cri=None, rho_cri=None, label=None)
Create an associated ExperimentalEnvelope
associated to this mixture
Mixture.experimental_flashes_as_gas
Mixture.experimental_flashes_as_liquid
Mixture.experimentalenvelopes
Mixture.experimentalflashes
Mixture.fractions
Mixture.get_ac(model)

Return the critical value for the attractive parameter array for PR, SRK or RKPR

Mixture.get_b(model)

Return the temperature dependence of the attractive parameter array for PR and the repulsive parameter in SRK and RKPR [l/mol]

Mixture.get_delta1()

Return the RK-PR third parameter array

Mixture.get_envelope(setup, label=None)

Get the envelope object for this mixture, calculated using the setup EOS with its selected interaction parameters mode.

Mixture.get_flash(setup, t, p=None, v=None)

Get the flash on (t, p) or (t,v) for this mixture, calculated using the setup EOS with its selected interaction parameters mode.

Mixture.get_flashes(setup, t, p=[], v=[])

Get a serie of flashes on (t, [p1, p2, p3...]) or (t,[v1, v2...]) for this mixture, calculated using the setup EOS with its selected interaction parameters mode. Return a list of flashes

Mixture.get_isochore(setup, v, ts, ps, t_sup, t_step=5.0, t_inf=270.0)

Get the isochore (isoV) for this mixture, calculated using the setup EOS with its selected interaction parameters mode.

Mixture.get_k()

Return the parameter for the temperature dependence of the attractive parameter array for the RKPR eos

Mixture.get_m(model)

Parameter for temperature dependence of the attractive parameter for PR or SRK

Mixture.isochorees
Mixture.objects = <django.db.models.manager.Manager object>
Mixture.pc

return the Pc array.

It is the Pc of each compound in the mixture as a numpy.array instance in the same order than self.compounds

Mixture.reset()

delete all MixtureFraction

Mixture.sort(by_weight=True)

Sort the mixture by compound’s weight or by position

Mixture.tc

return the Tc array.

It is the Tc of each compound in the mixture as a numpy.array instance in the same order than self.compounds

Mixture.total_z

Return the summatory of z fractions. Should sum 1.0 to be a valid mixture

Mixture.user
Mixture.vc

return the Vc array.

It is the Vc of each compound in the mixture as a numpy.array instance in the same order than self.compounds

Mixture.z

the Z as a numpy.array instance in the same order than self.compounds

class sur.models.MixtureFraction(id, mixture_id, compound_id, fraction, position)

Bases: django.db.models.base.Model

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception MixtureFraction.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

MixtureFraction.compound
MixtureFraction.mixture
MixtureFraction.objects = <django.db.models.manager.Manager object>
MixtureFraction.save(*args, **kwargs)
class sur.models.Isochore(id, mixture_id, setup_id, v, ts, ps, t_sup, t_step, t_inf, p, t, rho, beta_mol, beta_vol, p_monophasic, t_monophasic, rho_monophasic, input_txt, output_txt)

Bases: django.db.models.base.Model

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception Isochore.MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

Isochore.beta_mol

A placeholder class that provides a way to set the attribute on the model.

Isochore.beta_vol

A placeholder class that provides a way to set the attribute on the model.

Isochore.get_txt()
Isochore.interactions
Isochore.mixture
Isochore.objects = <django.db.models.manager.Manager object>
Isochore.p

A placeholder class that provides a way to set the attribute on the model.

Isochore.p_monophasic

A placeholder class that provides a way to set the attribute on the model.

Isochore.plot(fig=None, legends=None)
Isochore.rho

A placeholder class that provides a way to set the attribute on the model.

Isochore.rho_monophasic

A placeholder class that provides a way to set the attribute on the model.

Isochore.setup
Isochore.t

A placeholder class that provides a way to set the attribute on the model.

Isochore.t_monophasic

A placeholder class that provides a way to set the attribute on the model.

sur.plots module

Plot shortcuts utilities

sur.plots.multiplot(envelopes=None, experimental_envelopes=None, formats=None, critical_point='o', experimental_colors=None, experimental_markers=None, legends=None)

merge the plot of multiples envelopes

sur.settings module

sur.tools module

sur.tools.dump_json(json_path, indent=2)

A helper function to dump models from the current database state. Useful to update data/initial_data.json

it’s analog to

manage.py dumpdata –indent=2 sur.Compound sur.K0InteractionParameter sur.KijInteractionParameter sur.LijInteractionParameter sur.TstarInteractionParameter > json_path

but taking care of current in memory saved data.

sur.units module

class sur.units.BaseUnit

Bases: object

classmethod convert(array, original_unit, new_unit)
classmethod reverse(display)

return the key unit for a given display value

classmethod sanitize_unit(unit)
class sur.units.DensityVolume

Bases: sur.units.BaseUnit

CHOICES = (('L/mol', 'L/mol'), ('mol/L', 'mol/L'), ('g/cm**3', 'g/cm3'))
DEFAULT = 'g/cm**3'
G_CM3 = 'g/cm**3'
LITER_MOL = 'L/mol'
MOL_LITER = 'mol/L'
class sur.units.Pressure

Bases: sur.units.BaseUnit

ATM = 'atm'
BAR = 'bar'
CHOICES = (('bar', 'bar'), ('mmHg', 'mmHg'), ('atm', 'atm'), ('Pa', 'Pa'), ('Pa', 'psi'))
DEFAULT = 'bar'
MMHG = 'mmHg'
PASCAL = 'Pa'
PSI = 'psi'
VALIDATION_CLASS

alias of UnitQuantity

class sur.units.Temperature

Bases: sur.units.BaseUnit

CELSIUS = 'degC'
CHOICES = (('degC', u'\xb0C'), ('K', 'K'), ('degF', u'\xb0F'))
CLASS

alias of UnitTemperature

DEFAULT = 'K'
FAHRENHEIT = 'degF'
KELVIN = 'K'
classmethod convert(array, u_from, u_to)
sur.units.default_units(header)

given a lists of headers, return the default unit for each one

sur.units.get_units_display(units)
sur.units.unit_belongs_to_header(unit, h)

asserts the unit represents the variable in the header

sur.units.units_map()

Module contents

sur.data(a)
sur.setup_database()

this is a hackish trick.

It setup the django enviroment through setup_environ(settings)

Then populates the database but, instead of fixtures, it dumps db on disk (‘disk’) to a memory one (‘default’), and then syncs the missing tables on the latter.

Indices and tables