def vis(dd, ax=None, size=1, show=False, inds = None, debug=False):
""" return the indices in dd which are currently visible and greater
in size than size (>=). Use after visual.sp
size = 0 will return all points and sizes
"""
from pyfusion.data.convenience import btw
if inds is None: raise Exception('inds must be set (-1 for all) for now')
if ax is None:
ax=pl.gca()
x = ax.get_xlabel()
xlim = ax.get_xlim()
y = ax.get_ylabel()
ylim = ax.get_ylim()
if len(np.shape(inds)) == 0 and inds == -1:
inds = np.arange(len(dd[x]))
# w = np.where(btw(dd[x],xlim) & btw(dd[y],ylim))[0]
w = np.where(btw(dd[x][inds],xlim) & btw(dd[y][inds],ylim))[0]
if len(w) == 0:
raise LookupError('No points found')
if show:
pl.scatter(dd[x][w], dd[y][w],'+')
if debug: 1/0
return(w)
def vis(dd, ax=None, size=1, show=False, inds=None, debug=False):
""" return the indices in dd which are currently visible and greater
in size than size (>=). Use after visual.sp
size = 0 will return all points and sizes
"""
from pyfusion.data.convenience import btw
if inds is None: raise Exception('inds must be set (-1 for all) for now')
if ax is None:
ax = pl.gca()
x = ax.get_xlabel()
xlim = ax.get_xlim()
y = ax.get_ylabel()
ylim = ax.get_ylim()
if len(np.shape(inds)) == 0 and inds == -1:
inds = np.arange(len(dd[x]))
# w = np.where(btw(dd[x],xlim) & btw(dd[y],ylim))[0]
w = np.where(btw(dd[x][inds], xlim) & btw(dd[y][inds], ylim))[0]
if len(w) == 0:
raise LookupError('No points found')
if show:
pl.scatter(dd[x][w], dd[y][w], '+')
if debug: 1 / 0
return (w)
cind = 0
colorset=('b,g,r,c,m,y,k,orange,purple,lightgreen,gray'.split(',')) # to be rotated
DA65MPH=DA('DA65MP2010HMPno612b5_M_N_fmax.npz',load=1)
DA65MPH.extract(locals())
pyfusion.config.set('Plots',"FT_Axis","[0.5,4,0,80000]")
"""
run -i pyfusion/examples/plot_specgram.py shot_number=65139 channel_number=1 NFFT=1024
pl.set_cmap(cm.gray_r)
pl.clim(-60,-0)
"""
sc_kw=dict(edgecolor='k',linewidth = 0.3)
for n in (-1,0,1):
for m in (-2, -1,1,2):
w =np.where((N==n) & (M==m) & (_binary_svs < 99) & btw(freq,frlow,frhigh))[0]
if len(w) != 0:
col = colorset[cind]
pl.scatter(t_mid[w], freq[w], size_scale*amp[w], color=col, label='m,n=~{m},{n}'.format(m=m, n=n),**sc_kw)
cind += 1
w=np.where((_binary_svs < 99) & btw(freq,frlow,frhigh) & btw(MM, 0,130) & (NN== -4))[0]
col = colorset[cind] ; cind+=1
m = 1; n=0
pl.scatter(t_mid[w], freq[w], size_scale*amp[w], color=col, label='m,n=~{m},{n}'.format(m=m, n=n),**sc_kw)
DA65H=DA('DA65HMPno612b_M.npz',load=1)
DA65H.extract(locals())
w=np.where((_binary_svs < 99999) & btw(freq,frlow*0.8,frhigh*1.2) & btw(MM, -60,-5))[0]
#col = colorset[cind] ; cind+=1
m = 1; n=0
import numpy as np
from numpy import where, array
from pyfusion.data.DA_datamining import DA
from pyfusion.acquisition.read_text_pyfusion import read_text_pyfusion, plot_fs_DA, merge_ds
from pyfusion.visual.window_manager import rmw, cmw, omw, lmw, smw
from pyfusion.utils.utils import fix2pi_skips, modtwopi
from pyfusion.visual.sp import off, on, tog
from pyfusion.data.convenience import between, bw, btw, decimate, his, broaden
dd=DA('W7X_MIR/DAMIRNOV_41_13_nocache_15_3m_2018fl.zip')
dd.info()
fig4, axs4=plt.subplots(4,1)
figfs, axf=plt.subplots(1,1)
plot_fs_DA(dd, ax=axf)
w6=where((btw(dd['freq'],4,8)) & (dd['amp']>0.0015) & (dd['t_mid']>3.2) &(dd['shot'] == 180904035))[0]
plot_fs_DA(dd, ax=axf, inds=w6,marker='s',ms=300,alpha=0.5)
axs4[0].plot(array([modtwopi(ph,offset=0) for ph in dd['phases'][w6]]).T,'c',lw=.5)
w6=where((btw(dd['freq'],4,8)) & (dd['amp']>0.015) & (dd['t_mid']>3.2) &(dd['shot'] == 180904035))[0]
axs4[0].plot(array([modtwopi(ph,offset=0) for ph in dd['phases'][w6]]).T,'b',lw=.5)
axs4[0].set_title('4-8kHz, after 3.2s')
w0=where((btw(dd['freq'],0,2)) & (dd['amp']>0.0015) & (dd['t_mid']>3.2) &(dd['shot'] == 180904035))[0]
plot_fs_DA(dd, ax=axf, inds=w0,marker='s',ms=300,alpha=0.5)
axs4[1].plot(array([modtwopi(ph,offset=0) for ph in dd['phases'][w0]]).T,'b',lw=.5)
axs4[1].set_title('0-2kHz, > 3.2s')
w6e=where((btw(dd['freq'],4,12)) & (dd['amp']>0.015) & (dd['t_mid']<3.2) &(dd['shot'] == 180904035))[0]
plot_fs_DA(dd, ax=axf, inds=w6e,marker='^',ms=300,alpha=0.5)
axs4[2].plot(array([modtwopi(ph,offset=0) for ph in dd['phases'][w6e]]).T,'c',lw=.5)
w6e=where((btw(dd['freq'],4,12)) & (dd['amp']>0.025) & (dd['t_mid']<3.2) &(dd['shot'] == 180904035))[0]
axs4[2].plot(array([modtwopi(ph,offset=0) for ph in dd['phases'][w6e]]).T,'b',lw=1)
axs4[2].set_title('4-12kHz, before 3.2s')
def remove_baseline(input_data,
baseline=None,
delta_t=0.01,
chan=None,
copy=True):
""" Remove a tilted baseline from a signal
If baseline is None, then average over delta_t at either end
If it is two times, then subtract the average between those (no tilt)
If it is 4 times, then bl[0,1] and bl[2,3] are averaged - so
the correction is at two points (mid point of those intervals)
baseline in the same units as the timebase
baseline == None is NOT the same as for integrate
"""
from pyfusion.data.convenience import whr, btw
if copy:
input_data = deepcopy(input_data)
if (len(np.shape(input_data.signal)) == 2) and chan is None:
for (s, sig) in enumerate(input_data.signal):
input_data.signal[s][:] = remove_baseline(input_data,
chan=s,
baseline=baseline,
delta_t=delta_t).signal
else:
if chan is None:
signal = input_data.signal
else:
signal = input_data.signal[chan]
tb = input_data.timebase
bl = np.array(baseline).flatten()
if baseline is None or len(baseline) == 0:
bl = [
np.min(tb),
np.min(tb) + delta_t,
np.max(tb) - delta_t,
np.max(tb)
]
wst = np.where(btw(tb, bl[0:2]))[0]
bl_st = np.average(signal[wst])
time_st = np.average(tb[wst])
if len(bl) == 4:
wend = np.where(btw(tb, bl[2:4]))[0]
bl_end = np.average(signal[wend])
time_end = np.average(tb[wend])
input_data.signal = signal - (bl_st * (time_end - tb) /
(time_end - time_st) - bl_end *
(time_st - tb) /
(time_end - time_st))
else:
bl_end, time_end = None, None
input_data.signal = signal - bl_st # these are to avoid upsetting print
if pyfusion.VERBOSE > 0:
print('baseline removal start, end, indicies', bl_st, bl_end,
time_st, time_end)
return (input_data)
from pyfusion.data.convenience import between, bw, btw, decimate, his, broaden
# paste NOt %PASTE
#_PYFUSION_TEST_@@SCRIPT
run -i pyfusion/examples/gen_fs_bands.py dev_name='W7X' diag_name=W7X_MIRNOV_41_BEST_LOOP shot_range="[[20180912,s] for s in range(43,44)]" max_bands=1 info=0 min_svs=2 max_H=0.999 min_p=0 exception=() outfile='W7X_MIR/preproc/201809/PMIRNOV_41_BEST_LOOP_10_3m_20180912043' fmax=10e3 seg_dt=3e-3 min_svs=2
# clean up not usually needed
run -i pyfusion/examples/clean_up_pyfusion_text_mp.py MP=0 fileglob="'W7X_MIR/preproc/201809/P*'"
run -i pyfusion/examples/merge_text_pyfusion.py file_list="np.sort(glob('W7X_MIR/preproc/201809/PMIRNOV_41_BEST_LOOP_10_3m_20180912043'))"
run pyfusion/examples/plot_specgram.py diag_name='W7X_MIR_4136' shot_number=[20180912,43] NFFT=2048*4
plot_fs_DA(dd);pl.ylim(0,30)
from pyfusion.data.DA_datamining import DA, report_mem, append_to_DA_file
DA43MIRNOV_13_BEST_LOOP=DA(dd)
DA43MIRNOV_13_BEST_LOOP.save('/tmp/DAMIRNOV_41_13_BEST_LOOP_10_3ms_20180912043.npz")
dd = DA("DAMIRNOV_41_13_BEST_LOOP_10_3ms_20180912043.npz")
w=where((btw(dd['freq'],2,4)) & (dd['amp']>0.012) )[0]
plt.plot(dd['phases'][w].T)
# prettier plots
plt.rcParams['font.size']=20
phs=array([modtwopi(ph,offset=-1) for ph in dd['phases']])
w3=where((btw(dd['freq'],2,4)) & (dd['amp']>0.012) )[0]
plt.plot(phs[w3].T)
plt.figure()
w6=where((btw(dd['freq'],5,7)) & (dd['amp']>0.015) )[0];len(w6)
plt.plot(phs[w6].T)
title('6kHz mode')
ylabel('phase dif n, n-1')
xlabel('probe pairs (n,n-1)')
w=where((btw(dd['freq'],2,4)) & (dd['amp']>0.05) )[0]
kh_req # these lines are just to keep the lint checker quiet
except:
kh_req = None
kappa_v = None
shot = None
indx = None
noverlap = 20 - 1
lrun = 20
scans = [[
[shot[ind] for ind in inds],
unique(kh_req[inds]),
unique(kappa_v[inds]), inds
] for inds in [indx[ind:ind + lrun] for ind in indx[::lrun // (noverlap + 1)]]
if ((btw(len(unique(kappa_v[inds])), 2, 5)) and (
btw(len(unique(kh_req[inds])), 2, 10)))]
sorti = argsort([len(scan[2]) for scan in scans]) # sort by number of kv's
sorti = argsort([scan[0][0] for scan in scans]) # sort by number of kv's
header = str('ind numkh range numkv range shots from to')
print(header)
for ind, scan in zip(sorti, array(scans)[sorti]):
print('{ind:3}: {nkh:3} {khr} {nkv:4} {kvr} {ns:6} {mins:6}-{maxs:6}'.
format(ind=ind,
nkh=len(scan[1]),
nkv=len(scan[2]),
ns=len(scan[0]),
mins=min(scan[0]),
maxs=max(scan[0]),