Пример #1
0
def forward():
    '''
    Run forward Badlands models.
    '''
    xml_filename = os.path.join(
        DIR,
        '..',
        '..',
        'inputs',
        SCENARIO,
        'input_forward_{}_prerift.xml'.format(SCENARIO),
    )
    model = badlandsModel()
    model.load_xml(xml_filename)
    model.run_to_time(RIFT_TIME * -1.e6)

    xml_filename = os.path.join(
        DIR,
        '..',
        '..',
        'inputs',
        SCENARIO,
        'input_forward_{}_postrift.xml'.format(SCENARIO),
    )
    model = badlandsModel()
    model.load_xml(xml_filename)
    model.run_to_time(END_TIME * -1.e6)
Пример #2
0
    def get_synthetic_initopo(self):

        model = badlandsModel() 
        # Load the XmL input file
        model.load_xml(str(self.run_nb_str), self.xmlinput, muted=True) 
        #Update the initial topography
        #Use the coordinates from the original dem file
        xi=int(np.shape(model.recGrid.rectX)[0]/model.recGrid.nx)
        yi=int(np.shape(model.recGrid.rectY)[0]/model.recGrid.ny)
        #And put the demfile on a grid we can manipulate easily
        elev=np.reshape(model.recGrid.rectZ,(xi,yi))

        return elev
Пример #3
0
def backward():
    '''
    Run backward Badlands model.
    '''
    xml_filename = os.path.join(
        DIR,
        '..',
        '..',
        'inputs',
        SCENARIO,
        'input_back_{}.xml'.format(SCENARIO),
    )
    model = badlandsModel()
    model.load_xml(xml_filename)
    model.run_to_time(END_TIME * -1.e6)
from scipy.spatial import cKDTree
from scipy.ndimage import gaussian_filter

from scripts import badInput as tools

import matplotlib
import matplotlib.pyplot as plt
from matplotlib import cm

import warnings
warnings.filterwarnings("ignore", category=RuntimeWarning)

from badlands.model import Model as badlandsModel

# initialise model
model = badlandsModel()

# Define the XmL input file
model.load_xml('input_paleo2-depo-isoFlex.xml')

keepgoing = True

changeTe_t = np.arange(0, 70 + 1, 1) * -1000000
flex = []

while (keepgoing):

    next_time = model.tNow + model.input.tDisplay

    if next_time > model.input.tEnd:
        model.run_to_time(model.input.tEnd)