updated functions and made some notebooks

binary_c_python_api.o

output/*

david_results/*

*.nfs*

                    value_dict[key] = val

                value_dicts.append(value_dict)

    if len(value_dicts)==0:

        print('Sorry, didnt find any line matching your header {}'.format(selected_header))

        return None

    keys = value_dicts[0].keys()

    # Construct final dict.

%% Cell type:code id: tags:

``` python

import os, sys, time

import matplotlib.pyplot as plt

from collections import defaultdict

import numpy as np

import pandas as pd

# sys.path.append('../')

import binary_c

from binaryc_python_utils.functions import create_arg_string, parse_output, run_system

result_dir = '../david_results/'

```

%% Cell type:markdown id: tags:

# Run binaryc command

%% Cell type:code id: tags:

``` python

start = time.time()

output = run_system(M_1=10, M_2=20, separation=0, orbital_period=100, max_evolution_time=15000)

result = parse_output(output, 'DAVID_BINARY_ANALYSIS')

stop = time.time()

print("Took {:.2f}s to run single system".format(stop-start))

print("The following keys are present in the results:\n{}".format(result.keys()))

```

%% Output

    Took 1.60s to run single system

    The following keys are present in the results:

    dict_keys(['t', 'mass_1', 'zams_mass_1', 'mass_2', 'zams_mass_2', 'stellar_type_1', 'prev_stellar_type_1', 'stellar_type_2', 'prev_stellar_type_2', 'radius_1', 'radius_2', 'roche_radius_1', 'roche_radius_2', 'core_mass_1', 'core_mass_2', 'luminosity_1', 'luminosity_2', 'omega_1', 'omega_2', 'metallicity', 'probability', 'separation', 'eccentricity', 'period', 'dtm', 'core_radius_1', 'core_radius_2', 'teff_1', 'teff_2', 'drdt_1', 'drdt_2', 'vwind_1', 'vwind_2', 'tm_1', 'tm_2', 'tn_1', 'tn_2', 'tkh_1', 'tk_2', 'angular_momentum_1', 'angular_momentum_2', 'he_core_mass_1', 'he_core_mass_2', 'CO_core_mass_1', 'CO_core_mass_2', 'GB_core_mass_1', 'GB_core_mass_2', 'v_eq_1', 'v_eq_2', 'v_eq_ratio_1', 'v_eq_ratio_2'])

%% Cell type:code id: tags:

``` python

```

%% Output

    18351949

%% Cell type:code id: tags:

``` python

# Cast the data into a dataframe.

df = pd.DataFrame.from_dict(result, dtype=np.float64)

#### Now do whatever you want with it:

# Get last change moment

last_st_1 = df['stellar_type_1'].unique()[-1]

last_stellar_type_change_time_1 = df[df.stellar_type_1==last_st_1]['t'].iloc[0]

last_st_2 = df['stellar_type_2'].unique()[-1]

last_stellar_type_change_time_2 = df[df.stellar_type_2==last_st_2]['t'].iloc[0]

last_change_time = last_stellar_type_change_time_1 if last_stellar_type_change_time_1>last_stellar_type_change_time_2 else last_stellar_type_change_time_2

# slice to get that last time

sliced_df = df[df.t < last_change_time] # Cut off late parts of evolution

```

%% Cell type:code id: tags:

``` python

plt.plot(sliced_df['t'], sliced_df['mass_1'], label='mass_1')

plt.plot(sliced_df['t'], sliced_df['mass_2'], label='mass_2')

plt.xlabel('Time (Myr)')

plt.ylabel('Radius (Rsol)')

# plt.yscale('log')

plt.legend()

plt.savefig(os.path.join(result_dir, 's'))

plt.show()

```

%% Output

%% Cell type:code id: tags:

``` python

plt.plot(sliced_df['t'], sliced_df['period'], label='period')

plt.plot(sliced_df['t'], sliced_df['mass_2'], label='mass_2')

plt.xlabel('Time (Myr)')

plt.ylabel('Radius (Rsol)')

# plt.yscale('log')

plt.legend()

plt.savefig(os.path.join(result_dir, 's'))

plt.show()

```