def rasterDimensions(maxx, maxy, minx=0, miny=0, dy=100, dx=100):
# construct the range
x = pd.Series(range(int(minx), int(maxx) + 1, 1))
y = pd.Series(range(int(miny), int(maxy) + 1, 1))
# filter for values that meet the increment or is the last value
cols = pd.Series(x.index).apply(lambda x1: x[x1] if x1 % dx == 0 or x1 ==
x[0] or x1 == x.index[-1] else None)
rows = pd.Series(y.index).apply(lambda y1: y[y1] if y1 % dy == 0 or y1 ==
y[0] or y1 == y.index[-1] else None)
# construct the indices
row_list = np.array(rows.loc[pd.notnull(rows)])
col_list = np.array(cols.loc[pd.notnull(cols)])
# construct the raster
raster = r.RasterModelGrid((len(row_list), len(col_list)),
spacing=(dy, dx))
raster.add_zeros
return (raster, row_list, col_list)
reload(stream_power)
reload(raster)
class data(object):
'''
This is where all the whole-grid data lives, as arrays over the various elements of the grid.
'''
#Data goes here!!!
def __init__(self, grid):
self.elev = grid.zeros() #some data
iterations = 10
tstep = 1.
#Make grid, set the elevs
mg = raster.RasterModelGrid(50, 50, 1.)
mg.set_inactive_boundaries(True, True, True, True)
vectors = data(mg)
#A surface dipping right, plus random noise:
loading_vector = np.linspace(50,1,num=50)
vectors.elev = np.repeat(loading_vector, 50)
vectors.elev += np.random.random_sample(vectors.elev.shape)/10.
vectors.init_elev = copy(vectors.elev)
print vectors.elev.shape
#print vectors.elev.reshape((5,10))
print vectors.elev.shape
print type(vectors.elev)
#print vectors.elev.reshape((5,10))
reload(flow_accumulation)
reload(raster)
class data(object):
'''
This is where all the whole-grid data lives, as arrays over the various elements of the grid.
'''
#Data goes here!!!
def __init__(self, grid):
self.elev = grid.zeros(centering='node') #some data
#Make grid, set the elevs
mg = raster.RasterModelGrid(5, 5, 1.)
mg.set_inactive_boundaries(True, True, False, True)
vectors = data(mg)
vectors.elev = np.array([
10., 10., 0., 10., 10., 10., 8., 8., 9., 10., 10., 4., 6., 7., 10., 10.,
1., 3., 8., 10., 10., 0., 10., 10., 10.
])
print vectors.elev.reshape((5, 5))
print np.array(range(25)).reshape((5, 5))
#print mg.node_status.reshape((5,5))
#imshow_grid(mg,vectors.elev)
#plot()