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%matplotlib inline

# import statements
import numpy as np
import matplotlib.pyplot as plt #for figures
from mpl_toolkits.basemap import Basemap #to render maps
import math
import json #to write dict with parameters

import GrowYourIC
from GrowYourIC import positions, geodyn, geodyn_trg, geodyn_static, plot_data, data

plt.rcParams['figure.figsize'] = (8.0, 3.0) #size of figures
cm = plt.cm.get_cmap('viridis')
cm2 = plt.cm.get_cmap('winter')


    

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## real data set - WD13
data_set = data.SeismicFromFile("../GrowYourIC/data/WD11.dat")

# random data set -
data_set_random = data.RandomData(3000)


    

In [10]:

    

r, t, p = data_set.extract_rtp("bottom_turning_point")

## map
m, fig = plot_data.setting_map() 
x, y = m(p, t)
sc = m.scatter(x, y, c='black',s=8, zorder=10, cmap=cm, edgecolors='none',alpha=0.5)

plt.savefig("repartition_1.pdf")

r, t, p = data_set_random.extract_rtp("bottom_turning_point")

## map
m, fig = plot_data.setting_map() 
x, y = m(p, t)
sc = m.scatter(x, y, c='black',s=8, zorder=10, cmap=cm, edgecolors='none',alpha=0.5)
plt.savefig("repartition_2.pdf")


    

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