RadCluster
Graph-based cluster dynamics for irradiated materials
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Namespaces | Functions | Variables
check_binwise_moments.py File Reference

Go to the source code of this file.

Namespaces

namespace  check_binwise_moments
 

Functions

 check_binwise_moments.load (pat)
 

Variables

str check_binwise_moments.OUT = "/Users/ghoni/Documents/GitHub/RadCluster/radcluster_code/output"
 
int check_binwise_moments.I = 1000
 
int check_binwise_moments.NB = int(sys.argv[1]) if len(sys.argv) > 1 else 32
 
 check_binwise_moments.sim
 
 check_binwise_moments.RE = sim.rate_equations
 
 check_binwise_moments.bins = list(RE.bins)
 
 check_binwise_moments.i_d
 
 check_binwise_moments.P
 
 check_binwise_moments.ref = load("*_M1_D1000_*")
 
 check_binwise_moments.bm = load(f"*_M2R_B{NB}_*")
 
 check_binwise_moments.yr = np.asarray(ref["results"]["y"], float)
 
 check_binwise_moments.yb = np.asarray(bm["results"]["y"], float)
 
 check_binwise_moments.C_floor = float(ref["input_data"].reactions.get("C_floor", 1e-15))
 
 check_binwise_moments.jr
 
 check_binwise_moments.jb
 
 check_binwise_moments.c_ref = np.maximum(yr[:I, jr], 0.0)
 
dict check_binwise_moments.tot = {"e0": 0.0, "b0": 0.0, "e1": 0.0, "b1": 0.0}
 
 check_binwise_moments.he = float(np.sum(np.maximum(c_ref[1:i_d] - C_floor, 0.0)))
 
 check_binwise_moments.hb = float(np.sum(np.maximum(yb[1:i_d, jb] - C_floor, 0.0)))
 
 check_binwise_moments.ns = np.arange(2, i_d + 1)
 
 check_binwise_moments.he1 = float(np.dot(ns, np.maximum(c_ref[1:i_d] - C_floor, 0.0)))
 
 check_binwise_moments.hb1 = float(np.dot(ns, np.maximum(yb[1:i_d, jb] - C_floor, 0.0)))
 
 check_binwise_moments.hi = min(nhi, I)
 
 check_binwise_moments.seg = c_ref[nlo - 1:hi]
 
 check_binwise_moments.sizes = np.arange(nlo, hi + 1)
 
 check_binwise_moments.e0 = float(np.dot(sizes, seg))
 
 check_binwise_moments.off = i_d + P * k
 
int check_binwise_moments.b0 = 2 else 0.0
 
tuple check_binwise_moments.d0 = (b0 - e0) / e0 * 100 if e0 else float("nan")
 
tuple check_binwise_moments.d1 = (b1 - e1) / e1 * 100 if e1 else float("nan")