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Resolut=120
amp=1
T0=2
a = np.linspace(0.1, 5, Resolut)
b = np.linspace(0.1, 5, Resolut)
W = np.zeros((Resolut, Resolut))
for i in range (0,Resolut):
for j in range (0,Resolut):
def integrand1(t):
output = a[i]**-0.5 * amp * (t-b[j])/a[i] * exp(-( (t-b[j])/a[i] )**2.0)
return output
W[i][j]=quad(integrand1, 1, 3)[0]
Image_source.data = {'a': [a],'b':[b],'W':[W]}
Image.image(image="W", source=Image_source, palette=cc.palette.CET_R3, x=0, y=0, dw=5, dh=5)
show(Image)
# CET_D1A
}
_colorbar_types = ['image', 'hexbin', 'heatmap', 'quadmesh', 'bivariate',
'contour', 'contourf', 'polygons']
_legend_positions = ("top_right", "top_left", "bottom_left",
"bottom_right", "right", "left", "top",
"bottom")
_default_plot_opts = {
'logx': False, 'logy': False, 'show_legend': True, 'legend_position': 'right',
'show_grid': False, 'responsive': False, 'shared_axes': True}
_default_cmaps = {
'linear': 'kbc_r',
'categorical': cc.palette['glasbey_category10'],
'cyclic': 'colorwheel',
'diverging': 'coolwarm'
}
def __init__(self, data, x, y, kind=None, by=None, use_index=True,
group_label='Variable', value_label='value',
backlog=1000, persist=False, use_dask=False,
crs=None, fields={}, groupby=None, dynamic=True,
grid=None, legend=None, rot=None, title=None,
xlim=None, ylim=None, clim=None, symmetric=None,
logx=None, logy=None, loglog=None, hover=None,
subplots=False, label=None, invert=False,
stacked=False, colorbar=None, fontsize=None,
datashade=False, rasterize=False,
row=None, col=None, figsize=None, debug=False,
framewise=True, aggregator=None,