mirror of https://github.com/Askill/claude.git
84 lines
2.0 KiB
Python
84 lines
2.0 KiB
Python
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# claude low level library
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import numpy as np
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cimport numpy as np
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ctypedef np.float64_t DTYPE_f
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sigma = 5.67E-8
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# define various useful differential functions:
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# gradient of scalar field a in the local x direction at point i,j
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def scalar_gradient_x(a,dx,nlon,i,j,k):
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return (a[i,(j+1)%nlon,k]-a[i,(j-1)%nlon,k])/dx[i]
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def scalar_gradient_x_2D(a,dx,nlon,i,j)
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return (a[i,(j+1)%nlon]-a[i,(j-1)%nlon])/dx[i]
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# gradient of scalar field a in the local y direction at point i,j
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def scalar_gradient_y(a,dy,nlat,i,j,k):
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if i == 0:
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return 2*(a[i+1,j]-a[i,j])/dy
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elif i == nlat-1:
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return 2*(a[i,j]-a[i-1,j])/dy
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else:
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return (a[i+1,j]-a[i-1,j])/dy
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def scalar_gradient_y_2d(a,dy,nlat,i,j)
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if i == 0:
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return 2*(a[i+1,j]-a[i,j])/dy
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elif i == nlat-1:
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return 2*(a[i,j]-a[i-1,j])/dy
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else:
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return (a[i+1,j]-a[i-1,j])/dy
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def scalar_gradient_z(a,dz,i,j,k):
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output = np.zeros_like(a)
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nlevels = len(dz)
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if output.ndim == 1:
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if k == 0:
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return (a[k+1]-a[k])/dz[k]
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elif k == nlevels-1:
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return (a[k]-a[k-1])/dz[k]
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else:
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return (a[k+1]-a[k-1])/(2*dz[k])
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else:
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if k == 0:
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return (a[i,j,k+1]-a[i,j,k])/dz[k]
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elif k == nlevels-1:
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return (a[i,j,k]-a[i,j,k-1])/dz[k]
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else:
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return (a[i,j,k+1]-a[i,j,k-1])/(2*dz[k])
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def surface_optical_depth(lat):
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return 4 + np.cos(lat*np.pi/90)*2.5/2
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def thermal_radiation(a):
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return sigma*(a**4)
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# power incident on (lat,lon) at time t
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def solar(insolation, lat, lon, t, day, year, axial_tilt):
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sun_longitude = -t % day
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sun_longitude *= 360/day
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sun_latitude = axial_tilt*np.cos(t*2*np.pi/year)
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value = insolation*np.cos((lat-sun_latitude)*np.pi/180)
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if value < 0:
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return 0
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else:
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lon_diff = lon-sun_longitude
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value *= np.cos(lon_diff*np.pi/180)
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if value < 0:
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if lat + sun_latitude > 90:
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return insolation*np.cos((lat+sun_latitude)*np.pi/180)*np.cos(lon_diff*np.pi/180)
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elif lat + sun_latitude < -90:
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return insolation*np.cos((lat+sun_latitude)*np.pi/180)*np.cos(lon_diff*np.pi/180)
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else:
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return 0
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else:
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return value
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def profile(a):
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return np.mean(np.mean(a,axis=0),axis=0)
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