| ~~~ import numpy as np import matplotlib.pyplot as plt shot_no = 22471 identifier = "loop_voltage" # create data cache in the 'golem_cache' folder ds = np.DataSource('golem_cache') #Create a path to data and download and open the file base_url = "http://golem.fjfi.cvut.cz/utils/data/" data_file = ds.open(base_url + str(shot_no) + '/' + identifier) #Load data from the file and plot to screen and to disk data = np.loadtxt(data_file) plt.plot(data[:,0], data[:,1]) #1. column vs 2. column plt.savefig('graph.jpg') plt.show() #Run it: save it as script.py and run "python script.py" or execute in a ceel in a Jupyter Notebook ~~~ | |
| ~~~ import pandas as pd import matplotlib.pyplot as plt URL = 'http://golem.fjfi.cvut.cz/utils/data/{}/{}' # function for reading 1D y(t) signals def read_signal1d(shot_number, signal_id): url = URL.format(shot_number, signal_id) return pd.read_table(url,names=['time',signal_id], index_col='time') # read the specified signals shot_no = 29395 U_l = read_signal1d(shot_no, 'loop_voltage') I_p = read_signal1d(shot_no, 'plasma_current') P_OH = U_l*I_p # vectorized, time-aligned operation B_t = read_signal1d(shot_no, 'toroidal_field') H_a = read_signal1d(shot_no, 'photodiode_alpha') # combine into a data frame table df = pd.concat([U_l, I_p, B_t, H_a], axis='columns') # plot the data table in subplots from 4 to 25 ms df.loc[4e-3:25e-3].plot(subplots=True, ylim=(0,None)) plt.show() # display the figure in a window ~~~ |  |
| To the screen: ~~~ ShotNo=22471;\ echo "set ytics nomirror;\ plot '< wget -q -O - http://golem.fjfi.cvut.cz/utils/data/$ShotNo/loop_voltage'\ u 1:2 w l title 'Ul@$ShotNo'" | gnuplot -persist ~~~ To the file: ~~~ ShotNo=22471;\ echo "set terminal jpeg;set ytics nomirror;\ plot '< wget -q -O - http://golem.fjfi.cvut.cz/utils/data/$ShotNo/loop_voltage'\ u 1:2 w l title 'Ul@$ShotNo'" | gnuplot > graph.jpg ~~~ |  |
| ~~~ set macros; ShotNo = "22471"; baseURL = "http://golem.fjfi.cvut.cz/utils/data/"; identifier = "loop_voltage"; #Create a path to data DataURL= "@baseURL@ShotNo/@identifier"; #Write data from GOLEM server to a local file !wget -q @DataURL; #Plot the graph from a local file set datafile separator "\t"; plotstyle = "with lines linestyle -1" plot 'loop_voltage' using 1:2 @plotstyle; exit; ~~~ | |
| ~~~ ShotNo=22471; baseURL='http://golem.fjfi.cvut.cz/utils/data/'; identifier='loop_voltage'; %Create a path to data dataURL=strcat(baseURL,int2str(ShotNo),'/',identifier); % Write data from GOLEM server to a local file urlwrite(dataURL,identifier); % Load data data = load(identifier, '\t'); % Plot and save the graph plot(data(:,1)*1000, data(:,2), '.') ; xlabel('Time [ms]') ylabel('U_l [V]') saveas(gcf, 'plot', 'jpeg'); exit; ~~~ |  |
| ~~~ import numpy as np import matplotlib.pyplot as plt shot_no = 22471 identifier = "loop_voltage" # create data cache in the 'golem_cache' folder ds = np.DataSource('golem_cache') #Create a path to data and download and open the file base_url = "http://golem.fjfi.cvut.cz/utils/data/" def get_data(identifier): data_file = ds.open(base_url+ str(shot_no) + '/' + identifier) return np.loadtxt(data_file) fig = plt.figure(1) plt.subplots_adjust(hspace=0.001) sbp1=plt.subplot(511) data1 = get_data('loop_voltage') plt.ylim(0,26) plt.yticks(np.arange(0, 30, 5)) plt.title('#'+str(shot_no)) plt.ylabel('$U_l$ [V]') plt.plot(data1[:,0]*1000, data1[:,1], 'k-',label='Loop voltage $U_l$' ) plt.legend(loc=0) sbp1=plt.subplot(512, sharex=sbp1) data2 = get_data('toroidal_field') plt.yticks(np.arange(0, 0.5 , 0.1)) plt.ylim(0,0.35) plt.ylabel('$B_t$ [T]') plt.plot(data2[:,0]*1000, data2[:,1], 'k-',label='Toroidal mag. field $B_t$') plt.legend(loc=0) sbp1=plt.subplot(513, sharex=sbp1) data3 = get_data('plasma_current') plt.yticks(np.arange(0, 4.5, 1)) plt.ylim(0,4.5) plt.ylabel('$I_p$ [kA]') plt.plot(data3[:,0]*1000, data3[:,1]/1000, 'k-',label='Plasma current $I_p$') plt.legend(loc=0) sbp1=plt.subplot(514, sharex=sbp1) data4 = get_data('photodiode_alpha') plt.yticks(np.arange(0, 0.09 , 0.02)) plt.ylim(0,0.09) plt.ylabel('Intensity [a.u.]') plt.plot(data4[:,0]*1000, data4[:,1], 'k-',label='$H_\\alpha$ radiation') plt.legend(loc=0) sbp1=plt.subplot(515, sharex=sbp1) data5 = get_data('electron_density') plt.yticks(np.arange(0, 0.8 , 0.2)) plt.ylim(0,0.8) plt.ylabel('$n_e$') plt.xticks(np.arange(8, 30, 5)) plt.xlim(5,25) plt.xlabel('Time [ms]') plt.plot(data5[:,0]*1000, data5[:,1]*1e-19, 'k-',label='electron density $n_e$') plt.legend(loc=0) xticklabels = sbp1.get_xticklabels() plt.setp(xticklabels, visible=False) plt.savefig('basicgraph.pdf') plt.savefig('basicgraph.jpg') plt.show() ~~~ |  |