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commit | author | age
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#!/usr/bin/python3 |
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from trisurf import tsmgr |
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from trisurf import trisurf |
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from trisurf import statistics |
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print("Running trisurf version "+ tsmgr.getTrisurfVersion()) |
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Runs=[] |
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Nshell=25 |
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#--------- F = 0 ------------ |
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#kapa_list=[10,20,30,40,50] |
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#p=[5,10,15,20,25] |
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#N=5*Nshell**2+2 |
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#Nc_list=[int(N*pp/100) for pp in p] |
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#for kapa in kapa_list: |
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# for Nc in Nc_list: |
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# run=trisurf.Runner(tape='tape_Nc'+str(Nc)+'_k'+str(kapa)) |
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# run.setMaindir(("N", "k", "V", "_Nc", "_c","_w"), ("nshell","xk0","constvolswitch","number_of_vertices_with_c0","c0", "w")) |
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# run.setSubdir("run0") |
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# Runs.append(run) |
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#---------------------------- |
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#--------- F = 0 ------------ |
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kapa_list=[15,16,17,18,19,20,21,22] |
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#p=[5,7.5,10,12.5] |
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p=[8,8.5,9,9.5,10.5,11,11.5,12] |
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N=5*Nshell**2+2 |
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Nc_list=[int(N*pp/100) for pp in p] |
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#print(Nc_list) |
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#spremenil sem, ker nimam vseh podatkov!!! |
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kapa_list=[15,16,18,19,20,21,21,22] |
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Nc_list=[156,234,312,390] |
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for kapa in kapa_list: |
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for Nc in Nc_list: |
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#print('tape_Nc'+str(Nc)+'_k'+str(kapa)) |
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run=trisurf.Runner(tape='tape_Nc'+str(Nc)+'_k'+str(kapa)) |
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run.setMaindir(("N", "k", "V", "_Nc", "_c","_w"), ("nshell","xk0","constvolswitch","number_of_vertices_with_c0","c0", "w")) |
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run.setSubdir("run0") |
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Runs.append(run) |
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#---------------------------- |
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#kapa_list=[20,30] |
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#p=[10] |
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# |
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#N=5*Nshell**2+2 |
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#Nc_list=[int(N*pp/100) for pp in p] |
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# |
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#for kapa in kapa_list: |
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# for Nc in Nc_list: |
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# run=trisurf.Runner(snapshot='is_from_N25k'+str(kapa)+'V0_Nc312_c1.0.vtu') |
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# run.setMaindir(("N", "k", "V", "_Nc", "_c","_w","_F"), ("nshell","xk0","constvolswitch","number_of_vertices_with_c0","c0", "w","F")) |
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# run.setSubdir("run0") |
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# |
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# Runs.append(run) |
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#---------------------------- |
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#Nov format: |
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#hosts=({'name':'Hestia','address':'127.0.0.1', 'runs':Runs, 'username':'samo'},) |
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def analyze(run, **kwargs): |
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host=kwargs.get('host', None) |
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print("Demo analysis") |
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print("Analysis on host "+host['name']+" for run "+run.Dir.fullpath()+" completed") |
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print("here comes info on the run variable:") |
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print(run) |
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print("here comes info on the host variable:") |
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print(host) |
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print("here comes info on the args variable:") |
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print(kwargs.get('args',None)) |
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def plothbar(run, **kwargs): |
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import matplotlib.pyplot as plt |
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def smooth(y, box_pts): |
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import numpy as np |
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box = np.ones(box_pts)/box_pts |
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y_smooth = np.convolve(y, box, mode='same') |
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return y_smooth |
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table=trisurf.Statistics(run.Dir.fullpath(),filename='data_tspoststat.csv').getTable() |
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plt.plot(table['hbar'], '.') |
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plt.title(run.Dir.fullpath()) |
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plt.xlabel('Iteration') |
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plt.ylabel('hbar') |
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smooth_window=10 |
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smoothed=smooth(table['hbar'],smooth_window) |
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plt.plot(tuple(range(int(smooth_window/2),len(smoothed)-int(smooth_window/2))),smoothed[int(smooth_window/2):-int(smooth_window/2)]) |
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plt.show() |
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print |
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#if return False or no return statement, the analysis will continue with next running instance in the list. if return True, the analysis will stop after this run. |
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return False |
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def plotrunningavg(run, **kwargs): |
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import matplotlib.pyplot as plt |
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table=trisurf.Statistics(run.Dir.fullpath(),filename='data_tspoststat.csv').getTable() |
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def running_avg(col): |
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import numpy as np |
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avg=[] |
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for i in range(0,len(col)): |
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avg.append(np.average(col[:-i])) |
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return avg |
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ra=running_avg(table['hbar']) |
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plt.plot(ra) |
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plt.title('Running average') |
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plt.ylabel('1/n sum_i=niter^n(hbar_i)') |
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plt.xlabel('n') |
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plt.show() |
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#start manager with configured runs |
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tsmgr.start(Runs, analyses={'analyze1':analyze, 'plotrunningavg':plotrunningavg, 'plothbar':plothbar}) |
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#statistics.combine(Runs) |
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#statistics.combine([Runs[1],Runs[2]]) |
