In [1]:

    

%matplotlib inline
from espei.plot import dataplot
from espei.datasets import recursive_glob, load_datasets

from pycalphad import variables as v
import matplotlib.pyplot as plt


    

In [18]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/AL-CO-NI/input-data/'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['AL', 'CO', 'NI', 'VA']
phases = ['BCC_B2', 'FCC_A1', 'FCC_L12']
conds = {v.P: 101325, v.T: 1173,v.X('AL'): (0, 1, 0.01), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

In [3]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/AL-CO-MO/'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['AL', 'CO', 'MO', 'VA']
phases = ["BCC_A2", "BCC_B2", "CO3MO", "FCC_A1", "MU_D85"]
conds = {v.P: 101325, v.T: 1073,v.X('AL'): (0, 1, 0.01), v.X('CO'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[3]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x10f5f8c18>






    

In [4]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/AL-CO-NB/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['AL', 'CO', 'NB', 'VA']
phases = ["CO7NB2", "FCC_A1", "LAVES_C36", "BCC_B2", "CO2ALNB", "LAVES_C15", "MU_D85"]
conds = {v.P: 101325, v.T: 1173.0, v.X('AL'): (0, 1, 0.01), v.X('NB'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[4]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x11f31c080>






    

In [3]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/AL-CO-CR/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['AL', 'CO', 'CR', 'VA']
phases = ["BCC_A2", "BCC_B2", "FCC_A1", "SIGMA_D8B"]
conds = {v.P: 101325, v.T: 1273.0, v.X('AL'): (0, 1, 0.01), v.X('CO'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[3]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x11ac920f0>






    

In [26]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/AL-CO-TA/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['AL', 'CO', 'TA', 'VA']
phases = ["BCC_B2",
        "CO2ALTA",
        "CO7TA2",
        "FCC_A1",
        "LAVES_C15",
        "LAVES_C36"]
conds = {v.P: 101325, v.T: 1173.0, v.X('AL'): (0, 1, 0.01), v.X('CO'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[26]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x116197390>






    

In [6]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/AL-CO-W/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['AL', 'CO', 'W', 'VA']
phases = ["BCC_B2",
        "CO3W",
        "FCC_A1",
        "BCC_A2",
        "MU_D85"]
conds = {v.P: 101325, v.T: 1173.0, v.X('AL'): (0, 1, 0.01), v.X('W'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[6]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x11f84b0f0>






    

In [31]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-MN-TI/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE', 'MN', 'TI', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2"]
conds = {v.P: 101325, v.T: 1273.15, v.X('TI'): (0, 1, 0.01), v.X('MN'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[31]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x11753b160>






    

In [27]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-NI-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE', 'NI', 'V', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2", "SIGMA", "FCC_A1"]
conds = {v.P: 101325, v.T: 1100, v.X('FE'): (0, 1, 0.01), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[27]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x11a9b3630>






    

In [19]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-TI-V/input data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['V', 'CR', 'TI', 'VA']
phases = ["BCC_A2", "LAVES_C15", "HCP_A3"]
conds = {v.P: 101325, v.T: 873.15, v.X('TI'): (0, 1, 0.01), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[19]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x113d03cf8>






    

In [20]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-TI-V/input data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['V', 'CR', 'TI', 'VA']
phases = ["BCC_A2", "LAVES_C15", "HCP_A3"]
conds = {v.P: 101325, v.T: 773.15, v.X('TI'): (0, 1, 0.01), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[20]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x113d184a8>






    

In [21]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-TI-V/input data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['V', 'CR', 'TI', 'VA']
phases = ["BCC_A2", "LAVES_C15", "HCP_A3"]
conds = {v.P: 101325, v.T: 1473.15, v.X('TI'): (0, 1, 0.01), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[21]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x1149a7668>






    

In [22]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-TI-V/input data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['V', 'CR', 'TI', 'VA']
phases = ["BCC_A2", "LAVES_C15", "HCP_A3"]
conds = {v.P: 101325, v.T: 923.15, v.X('TI'): (0, 1, 0.01), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[22]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x114561c88>






    

In [23]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-TI-V/input data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['V', 'CR', 'TI', 'VA']
phases = ["BCC_A2", "LAVES_C15", "HCP_A3"]
conds = {v.P: 101325, v.T: 973.15, v.X('TI'): (0, 1, 0.01), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[23]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x1146455f8>






    

In [24]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-TI-V/input data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['V', 'CR', 'TI', 'VA']
phases = ["BCC_A2", "LAVES_C15", "HCP_A3"]
conds = {v.P: 101325, v.T: 1273.15, v.X('TI'): (0, 1, 0.01), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[24]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x1149ad630>






    

In [8]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-FE-TI/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE', 'CR', 'TI', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2"]
conds = {v.P: 101325, v.T: 1373, v.X('TI'): (0, 1, 0.01), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[8]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x113509400>






    

In [9]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-FE-TI/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE', 'CR', 'TI', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2"]
conds = {v.P: 101325, v.T: 1473, v.X('TI'): (0, 1, 0.01), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[9]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x113509048>






    

In [27]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-NI-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE', 'NI', 'V', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2", "SIGMA", "FCC_A1"]
conds = {v.P: 101325, v.T: 1100, v.X('FE'): (0, 1, 0.01), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[27]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x11a9b3630>






    

In [12]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-NI-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE', 'NI', 'V', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2", "SIGMA", "FCC_A1"]
conds = {v.P: 101325, v.T: 1100, v.X('FE'): (0, 1, 0.01), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[12]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x113509588>






    

In [13]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-NI-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE', 'NI', 'V', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2", "SIGMA", "FCC_A1"]
conds = {v.P: 101325, v.T: 1273.15, v.X('FE'): (0, 1, 0.01), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[13]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x113ec5550>






    

In [14]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-NI-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE', 'NI', 'V', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2", "SIGMA", "FCC_A1"]
conds = {v.P: 101325, v.T: 1373.15, v.X('FE'): (0, 1, 0.01), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[14]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x113f05898>






    

In [15]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-NI-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE', 'NI', 'V', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2", "SIGMA", "FCC_A1"]
conds = {v.P: 101325, v.T: 1473.15, v.X('FE'): (0, 1, 0.01), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[15]:





<matplotlib.axes._subplots.TriangularAxesSubplot at 0x1135189e8>






    

In [6]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-TI/input-json'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['FE','TI', 'VA']
phases = ["BCC_B2", "LAVES_C14", "BCC_A2"]
conds = {v.P: 101325, v.T: (500,1273.15,40), v.X('TI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[6]:





<matplotlib.axes._subplots.AxesSubplot at 0x10e4fa390>






    

In [4]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-NI/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['CR','NI', 'VA']
phases = ["LIQUID", "BCC_A2", "FCC_A1"]
conds = {v.P: 101325, v.T: (500,2100,40), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[4]:





<matplotlib.axes._subplots.AxesSubplot at 0x104bf2438>






    

In [5]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/AL-NI/input-json'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['AL','NI', 'VA']
phases = ["LIQUID", "BCC_B2", "FCC_L12", "AL3NI1", "AL3NI2", "AL3NI5"]
conds = {v.P: 101325, v.T: (500,1273.15,40), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[5]:





<matplotlib.axes._subplots.AxesSubplot at 0x11e51e710>






    

In [4]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-FE/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['CR','FE', 'VA']
phases = ["LIQUID", "BCC_B2", "FCC_A1", "SIGMA"]
conds = {v.P: 101325, v.T: (500,1273.15,40), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[4]:





<matplotlib.axes._subplots.AxesSubplot at 0x11b3997f0>






    

In [27]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Box Sync/23.02_Aleksei_espei_all/input-data/'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['CR','FE', 'VA']
phases = ["LIQUID", "BCC_B2", "FCC_A1", "SIGMA"]
conds = {v.P: 101325, v.T: (300,1273.15,40), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[27]:





<matplotlib.axes._subplots.AxesSubplot at 0x1158366d8>






    

In [30]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Box Sync/abdulmonem-input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['NI','FE', 'VA']
phases = ["LIQUID", "BCC_B2", "FCC_A1", "L12"]
conds = {v.P: 101325, v.T: (300,1273.15,40), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[30]:





<matplotlib.axes._subplots.AxesSubplot at 0x114236748>






    

In [5]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CU-TI/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['CU','TI', 'VA']
phases = ["BCC_A2", "HCP_A3"]
conds = {v.P: 101325, v.T: (500,1273.15,40), v.X('CU'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[5]:





<matplotlib.axes._subplots.AxesSubplot at 0x11d6d9358>






    

In [6]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-MN/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['MN','FE', 'VA']
phases = ["LIQUID", "BCC_B2", "FCC_A1"]
conds = {v.P: 101325, v.T: (500,1273.15,40), v.X('MN'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[6]:





<matplotlib.axes._subplots.AxesSubplot at 0x11db64c88>






    

In [10]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['V','FE', 'VA']
phases = ["LIQUID", "BCC_B2", "FCC_A1"]
conds = {v.P: 101325, v.T: (500,1273.15,40), v.X('V'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[10]:





<matplotlib.axes._subplots.AxesSubplot at 0x1186c5e48>






    

In [11]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/FE-NI/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['NI','FE', 'VA']
phases = ["LIQUID", "BCC_B2", "FCC_A1"]
conds = {v.P: 101325, v.T: (500,1273.15,40), v.X('NI'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[11]:





<matplotlib.axes._subplots.AxesSubplot at 0x118c01ac8>






    

In [5]:

    

ds_xt = load_datasets(recursive_glob('/Users/brandon/Projects/espei-datasets/CU-MG/input-data/', '*.json'))
my_phases = ['BCC_A2', 'CUMG2', 'FCC_A1', 'LAVES_C15', 'LIQUID']
my_components = ['CU', 'MG', 'VA']
conditions = {v.P: 101325, v.T: (500, 1400, 10), v.X('MG'): (0, 1, 0.01)}
dataplot(my_components, my_phases, conditions, ds_xt)
plt.savefig('/Users/brandon/testfigure.png')


    

In [9]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/TI-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['TI','V', 'VA']
phases = ["LIQUID", "BCC_B2", "HCP_A3"]
conds = {v.P: 101325, v.T: (400,1273.15,40), v.X('V'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[9]:





<matplotlib.axes._subplots.AxesSubplot at 0x1184822e8>






    

In [29]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/CR-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['CR','V', 'VA']
phases = ["LIQUID", "BCC_A2", "HCP_A3"]
conds = {v.P: 101325, v.T: (2000,2200,40), v.X('V'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[29]:





<matplotlib.axes._subplots.AxesSubplot at 0x11a6fd240>






    

In [22]:

    

plt.figure(figsize=(8,8))

ds_dir = '/Users/brandon/Projects/espei-datasets/NI-V/input-data'
ds = load_datasets(recursive_glob(ds_dir, '*.json'))
# inputs
comps = ['NI','V', 'VA']
phases = ["BCC_A2", "LIQUID", "SIGMA", "NI2V", "NI3V", "NI2V7"]

conds = {v.P: 101325, v.T: (700,2300,40), v.X('V'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[22]:





<matplotlib.axes._subplots.AxesSubplot at 0x11d9c7c50>






    

In [23]:

    

plt.figure(figsize=(8,8))

ds = load_datasets(['/Users/brandon/Downloads/7_Eutectic_SIGMA-BCC1-BCC2_Dubiel1987.json'])
# inputs
comps = ['CR','FE', 'VA']
phases = ["LIQUID", "BCC_B2", "FCC_A1", "SIGMA"]
conds = {v.P: 101325, v.T: (500,1273.15,40), v.X('CR'): (0, 1, 0.01)}

dataplot(comps, phases, conds, ds)


    

    
Out[23]:





<matplotlib.axes._subplots.AxesSubplot at 0x11e6cfd68>






    

In [24]:

    

ds.all()


    

    
Out[24]:





[{'broadcast_conditions': False,
  'comment': 'On the Miscibility Gap in the Fe-Cr System: A Mössbauer Study on the Long Term Annealed Alloys',
  'components': ['FE', 'CR'],
  'conditions': {'P': 101325, 'T': 774},
  'output': 'ZPF',
  'phases': ['SIGMA', 'BCC_A2'],
  'reference': 'Dubiel and Inden (1987)',
  'values': [[['SIGMA', ['CR'], [0.489]],
    ['BCC_A2', ['CR'], [0.156]],
    ['BCC_A2', ['CR'], [0.859]]]]}]

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