
import numpy as np
import matplotlib.pyplot as plt
import requests
from scipy import integrate, signal, interpolate
import pandas as pd
import holoviews as hv
hv.extension('bokeh')
import hvplot.pandas
import os, glob
ds = np.DataSource()

def remove_old(name):
    if os.path.exists(name):
        os.remove(name)
        
names = ['analysis.html', 'scan.html', 'icon.html', 'icon-fig.png','icon-fig_Radial.png','icon-fig_Vertical.png','Camera_vs_Mirnov_Radial.png','Camera_vs_Mirnov__Vertical.png','InnerQuadr.csv']
for name in names:
    remove_old(name)
    
if os.path.exists('Results/'):
    file=glob.glob('Results/*')
    for f in file:
        os.remove(f)


shot_no = 38479
def open_remote(shot_no, identifier, url_template):
    return ds.open(url_template.format(shot_no=shot_no, identifier=identifier))

def read_signal(shot_no, identifier, url, data_type='csv'): 
    file = open_remote(shot_no, identifier, url)
    if data_type == 'lvm':
        channels = channels = ['Time', 'mc1','mc5','mc9','mc13','Saddle','InnerQuadr', 'IexRad','IexVert','9', '10', '11', '12']
        return pd.read_table(file, sep = '\t', names=channels, index_col = 'Time')
    else:
        return pd.read_csv(file, names=['Time', identifier],
                     index_col = 'Time', squeeze=True)
def read_tab(shot_no,url):
    tab=ds.open(url)
    df=pd.read_csv(tab)
    end=df['Time'].iat[-1]
    start=df['Time'].iat[0]
    df=df.set_index('Time')
    return df, start, end
    
def remove_offset(data, window):
    data-=data.loc[:window].mean()
    return data

def smooth(data,win=11): #41
    smooth_data = signal.savgol_filter(data, win, 3)
    return smooth_data

url = f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/LimiterMirnovCoils/plasma_position.csv'
kI=1/0.05 #Rogowski coil (Flux loop) constant


try:
    df,start,end=read_tab(shot_no,url)
    mirnov=True
except OSError:
    mirnov=False
    
try:
    
    #!!! Prohozene I s U
    url_I_vert  = f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Operation/Discharge/Position_Stabilization/DAS_raw_data_dir_vertical/U%5evertical_fg.csv'
    url_U_vert  = f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Operation/Discharge/Position_Stabilization/DAS_raw_data_dir_vertical/U%5evertical_currclamp.csv'
    
    url_I_rad  = f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Operation/Discharge/Position_Stabilization/DAS_raw_data_dir_radial/U%5eradial_fg.csv'
    url_U_rad  = f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Operation/Discharge/Position_Stabilization/DAS_raw_data_dir_radial/U%5eradial_currclamp.csv'
    
    U_exStabVert = read_signal(shot_no, 'U_fg_Vert', url_U_vert)
    
    url_dt=requests.get(f'http://golem.fjfi.cvut.cz/shotdir/{shot_no}/Devices/Oscilloscopes/RigolMSO5204-b/ScopeSetup/XINC')

    dt=float(url_dt.text)*1e5
    print('dt:',dt)
    t_shift=-1
    t_osc = pd.Series(np.linspace(0,dt*10, len(U_exStabVert))).rename('Time')+t_shift
    
    U_exStabVert = pd.Series(U_exStabVert.index[:], index = t_osc)
    RogCoilVert = read_signal(shot_no, 'I_fg_Vert', url_I_vert)
    I_exStabVert = pd.Series(smooth(RogCoilVert.index[:]*kI), index = t_osc) #the data was multiplied by the consntant [V->A]
#     I_exStabVert = pd.Series(smooth(RogCoilVert.index[:]), index = t_osc) #the data is already recalculated
         
    U_exStabRad = read_signal(shot_no, 'U_fg_Rad', url_U_rad)
    
    U_exStabRad = pd.Series(U_exStabRad.index[:], index = t_osc)
    RogCoilRad = read_signal(shot_no, 'I_fg_Rad', url_I_rad)
    I_exStabRad = pd.Series(smooth(RogCoilRad.index[:]*kI), index = t_osc) #the data was multiplied by the consntant [V->A]
#     I_exStabRad = pd.Series(smooth(RogCoilRad.index[:]), index = t_osc) #the data is already recalculated
        
    exStab=True
    
except OSError:
    
    exStab=False

dt: 2.0


if exStab:
    names=['$I_{vert}$','$I_{rad}$','$U_{vert}$','$U_{rad}$','Vertical', 'Radial']
    Stab=pd.DataFrame({'$I_{vert}$': I_exStabVert, '$I_{rad}$': I_exStabRad, 
                       '$U_{vert}$': U_exStabVert, '$U_{rad}$': U_exStabRad})
    maxI=0
    for stab in range(2):
        I=names[stab]
        U=names[stab+2]
        
        fig, ax = plt.subplots(dpi=100)
        ax = Stab[I].plot(grid=True,label = I, c = 'r') #ocilloscope data
        ax2 = ax.twinx()
        ax2 = Stab[U].plot(label = '$U_{fg}$',c='tab:blue')
        ax.set(ylim=(-max(abs(Stab[I]))-0.5, max(abs(Stab[I]))+0.5), ylabel='I [A]',
               title=f'Shot No.{shot_no}, {names[stab+4]} Stabilization' )
        ax2.set(ylim=(-max(abs(Stab[U]))-0.5, max(abs(Stab[U]))+0.5), ylabel='U [V]')
        ax.legend(loc='upper left');ax2.legend(loc='upper right')
        
        if mirnov==True:
            plt.savefig('icon-fig_'+names[stab+4]+'.png')
        else:
            plt.savefig('icon-fig.png')
            
        maxI_stab=max(abs(Stab[I]))
        if maxI<maxI_stab:
            maxI=maxI_stab
        print('Maximum current:', round(maxI_stab,2), 'A')

        with open('Results/MaxI_'+names[stab+4], 'w') as f:
            f.write(str(round(maxI_stab,2)))

Maximum current: 7.07 A
Maximum current: 9.36 A


if exStab:
    df_processed = pd.concat([Stab], axis='columns')
    df_processed


if exStab:
    data_URL = f"http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/LimiterMirnovCoils/DAS_raw_data_dir/NIdata_6133.lvm"
    dataNI = read_signal(shot_no, ' ', data_URL, 'lvm').replace([np.inf, -np.inf, np.nan], value = 0)
    dataNI.index*=1e3
    Ivert=dataNI['IexVert']*kI
    Irad=dataNI['IexRad']*kI
    InnerQuadr=dataNI['InnerQuadr']
    
    InnerQuadr.to_csv('Results/InnerQuadr.csv')
    df_processed = pd.concat([Ivert, Irad],axis='columns')
    if mirnov:
        df_processed = pd.concat([df, Ivert, Irad],axis='columns')
    names=['IexVert','IexRad']
df_processed.to_csv('Results/ExStab.csv')


print('Position from Mirnov coils:', mirnov)
if mirnov:
    hline = hv.HLine(0)
    hline.opts(color='k', line_dash='dashed', alpha = 0.4, line_width=1.0)
    I_v=names[0]; I_r=names[1]
    if exStab: 
        ax_param=dict(ylim=(-85, 85),xlim=(start, end),height=250,width=600, grid = True)
        axIvert_param=dict(title = '',ylabel='I_exStab [A]', xlabel='Time [ms]', yaxis='left', height=250, width=600, 
             color='b', ylim=(-maxI-1.5, maxI+1.5),grid=True)

        axIrad_param=dict(title = '',ylabel='I_exStab [A]', xlabel='Time [ms]', yaxis='left', height=250, width=600, 
             color='r', ylim=(-maxI-1.5,maxI+1.5),grid=True)

        plot = df_processed['r'].hvplot(title = '', ylabel='r [mm]/ I[A]', xlabel='', **ax_param) *\
                    df_processed[I_v].hvplot(**axIvert_param) *\
                        df_processed[I_r].hvplot(**axIrad_param)+\
        df_processed['z'].hvplot(title = '',ylabel='z [mm] / I[A]',  xlabel='Time [ms]', **ax_param) *\
            df_processed[I_v].hvplot(**axIvert_param) *\
                df_processed[I_r].hvplot(**axIrad_param)+\
        df_processed['a'].hvplot(title = '',ylabel='a[mm]/ I[A]', xlabel='Time [ms]', **ax_param) *\
            df_processed[I_v].hvplot(**axIvert_param) *\
                    df_processed[I_r].hvplot(**axIrad_param)
        plot=plot*hline
        plot.cols(2)
        
    else:
        layout = hv.Layout([df_processed[v].hvplot.line(
            xlabel='', ylabel=l,ylim=(-85,85), xlim=(start,end),legend=False, title='', grid=True, group_label=v)
                            for (v, l) in [('r', ' r [mm]'), ('z', 'z [mm]'), ('a', 'a [mm]')] ])*hline
        plot=layout.cols(1).opts(hv.opts.Curve(width=600, height=200),  hv.opts.Curve('a', xlabel='time [ms]'))

    hvplot.save(plot, 'icon.html')

Position from Mirnov coils: True


if mirnov:
    fig, axs = plt.subplots(3, 1, sharex=True, dpi=200)
    df_processed['r'].plot(grid=True, ax=axs[0])
    df_processed['z'].plot(grid=True, ax=axs[1])
    df_processed['a'].plot(grid=True, ax=axs[2])
    for i in range(3):
        ax4=axs[i].twinx()
        ax4=df_processed[names[0]].plot(grid=True, c='b',alpha=0.3,label=names[0])
        ax4=df_processed[names[1]].plot(grid=True, c='r',alpha=0.3,label=names[1])
        plt.legend()
        ax4.set(xlim=(start,end), ylim=(-2*maxI,maxI*2),xlabel= 'Time [ms]', ylabel = 'I$_{exStab}$ [A]')
        
    axs[2].set(ylim=(-85,85), xlim=(start,end), xlabel= 'Time [ms]', ylabel = '$a$ [mm]')
    axs[1].set(ylim=(-85,85), xlim=(start,end), xlabel= 'Time [ms]', ylabel = '$\Delta$z [mm]')
    axs[0].set(ylim=(-85,85), xlim=(start,end), xlabel= 'Time [ms]', ylabel = '$\Delta$r [mm]', 
               title = 'Horizontal, vertical plasma position and radius #{}'.format(shot_no))
    plt.savefig('icon-fig')


try:
    ScanDef_url = requests.get("http://golem.fjfi.cvut.cz/shots/%i/Production/Parameters/ScanDefinition" % shot_no)
    ScanDef = ScanDef_url.text
    ScanDef=ScanDef.split(" ")
    for i in range(len(ScanDef)):
        ScanDef[i]=int(ScanDef[i])
    Scan=True
except ValueError:
    Scan=False
    ScanDef=[]
    print('Scan not defined')

Scan not defined


#TODO - osa x, zredukovat pocet smycek
if Scan and mirnov:
    for shot in ScanDef:
        url=f'http://golem.fjfi.cvut.cz/shots/{shot}/Diagnostics/LimiterMirnovCoils/plasma_position.csv'
        df2,start,end=read_tab(shot_no, url)
        param = ['r','z', 'a']
        for j in param:
            df_processed = df_processed.join(df2[j],rsuffix=f'_{shot}')
            
        url=f'http://golem.fjfi.cvut.cz/shots/{shot}/Operation/Discharge/Position_Stabilization/Results/ExStab.csv'
        tab=ds.open(url)
        Stab2=pd.read_csv(tab).set_index('Time')  
        
        for name in range(2):
            df_processed = df_processed.join(Stab2[names[name]], rsuffix=f'_{shot}')
     
    ax_param=dict(xlim=(start,end),ylim=(-85, 85),height=250,width=600, grid = True)
    axStab=dict(xlim=(start,end),ylim=(-110,110),height=250,width=600, grid = True)
    hline = hv.HLine(0)
    hline.opts(color='k', line_dash='dashed', alpha = 0.4, line_width=1.0)
    
    display(df_processed)
    plotScan = df_processed['r'].hvplot(title = '', ylabel='r [mm]', xlabel='', **ax_param) +\
                df_processed['z'].hvplot(title = '',ylabel='z [mm]',  xlabel='', **ax_param) +\
                df_processed['a'].hvplot(title = '',ylabel='a[mm]', xlabel='Time [ms]', **ax_param) +\
                df_processed[names[1]].hvplot(title = '',ylabel='I_rad[A]', xlabel='Time [ms]',**axStab)+\
                df_processed[names[0]].hvplot(title = '',ylabel='I_vert[A]', xlabel='Time [ms]',**axStab) 
                
    for shot in ScanDef:
        plotScan=plotScan[0]*df_processed['r_%i'%shot].hvplot(title = '', ylabel='r [mm]', xlabel='', **ax_param)+\
            plotScan[1]*df_processed['z_%i'%shot].hvplot(title = '', ylabel='z [mm]', xlabel='', **ax_param)+\
            plotScan[2]*df_processed['a_%i'%shot].hvplot(title = '', ylabel='a [mm]', xlabel='Time', **ax_param)+\
            plotScan[3]*df_processed[names[1]+'_%i'%shot].hvplot(title = '',ylabel='I_rad[A]', xlabel='Time [ms]',**axStab) +\
            plotScan[4]*df_processed[names[0]+'_%i'%shot].hvplot(title = '',ylabel='I_vert[A]', xlabel='Time [ms]',**axStab)
                    
        plotScan=plotScan*hline
        plotScan.cols(3)
        hvplot.save(plotScan, 'scan.html')


def scan():
    tdur=[]; StabVertParam=[]; StabRadParam=[]; MaxIvertStab=[]; MaxIradStab=[]
    ScanDef.append(shot_no)
    for shot in ScanDef:
        url_tdur=requests.get('http://golem.fjfi.cvut.cz/shots/%i/Diagnostics/BasicDiagnostics/Results/t_plasma_duration'%shot)
        tdur.append(float(url_tdur.text))

        url_StabVert=requests.get('http://golem.fjfi.cvut.cz/shots/%i/Operation/Discharge/Position_Stabilization/Parameters/vertical_waveform'%shot)
        StabVertParam.append(url_StabVert.text) 
        url_StabRad=requests.get('http://golem.fjfi.cvut.cz/shots/%i/Operation/Discharge/Position_Stabilization/Parameters/radial_waveform'%shot)
        StabRadParam.append(url_StabRad.text) 
        
        url_maxIvert=requests.get('http://golem.fjfi.cvut.cz/shots/%i/Operation/Discharge/Position_Stabilization/Results/MaxI_Vertical'%shot)
        MaxIvertStab.append(url_maxIvert.text)
        url_maxIrad=requests.get('http://golem.fjfi.cvut.cz/shots/%i/Operation/Discharge/Position_Stabilization/Results/MaxI_Radial'%shot)
        MaxIradStab.append(url_maxIrad.text)
    data={'Plasma duration': tdur, 'Vertical Stabilization parameters': StabVertParam, 
            'Radial Stabilization parameters': StabRadParam, 'Max current in VertStab': MaxIvertStab,
              'Max current in RadStab': MaxIradStab, 'Shot_no': ScanDef}
    df_results=pd.DataFrame(data)
    df_results=df_results.set_index('Shot_no')
    df_results.to_csv('Results/scanResults.csv')
    return df_results

if mirnov and Scan:
    display(scan())


def comparison_image(shot_no, Position):
    
    url=f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/LimiterMirnovCoils/plasma_position.csv'
    tab=ds.open(url)
    df=pd.read_csv(tab)
    end=df['Time'].iat[-1]
    start=df['Time'].iat[0]
    df=df.set_index('Time')
    
    url_VertCam = f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/FastCameras/Camera_Vertical/CameraVerticalPosition'
    url_RadCam = f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/FastCameras/Camera_Radial/CameraRadialPosition'
    
    if Position=='Radial':
        symb='r'
        camera_position=read_signal(shot_no, symb, url_RadCam, data_type='csv')
    if Position=='Vertical': 
        symb='z'
        camera_position=read_signal(shot_no, symb, url_VertCam, data_type='csv')

    fig = plt.figure(figsize=(12,4),dpi=70)
    
    FONT = 'DejaVu Sans'

    ax = df[symb].plot(label='Mirnov coils')
    ax = camera_position.plot(label = 'Fast Camera')

    ax.set_ylabel('$\Delta$'+symb+' [mm]',fontname = FONT, fontsize = 12)
    ax.set_xlabel('Time [ms]',fontname = FONT, fontsize = 12)
    ax.set_ylim(-85,85) 

    loclegend='best'
    leg = plt.legend(loc = loclegend, shadow = True, fancybox=False) #with marker

    leg.get_frame().set_linewidth(1)
    leg.get_frame().set_edgecolor('k')
    for text in leg.get_texts():
          plt.setp(text, fontname=FONT, fontsize = 12)
    for line, text in zip(leg.get_lines(), leg.get_texts()):
          text.set_color(line.get_color())

    ax.grid(which = 'major', c = 'gray', linewidth = 0.5, linestyle = 'solid') 
    ax.grid(which = 'minor', c = 'gray', linewidth = 0.3, linestyle = 'dashed') 

    ax.axhline(y=0, color='k', ls='--', lw=1, alpha=0.4)

    fig.savefig(f'Camera_vs_Mirnov_{Position}')


for position in ['Radial','Vertical']:
    try:
        comparison_image(shot_no, position)
    except:
        print(f'{position} camera data is missing')

External stabilization¶

Current shot

Scan

Stabilization¶

Plasma position - Mirnov coils¶

New iconfig¶

Scan over the session¶

Cameras vs Mirnov Coils¶