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plot_measurement_table.py
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plot_measurement_table.py
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# To use this file, best copy it to your result folder and run it there
import sys
sys.path.append('/home/ronny/Scripts/hiflex/')
sys.path.append('/hiflex/')
from procedures import *
import csv
params = dict()
savefile = 'measurement_table.pdf'
datafile = 'measurement_table.csv' # assumes that the objectnames are somewhat in column one or two
sensorsfile = 'TSP01_20210624-1822.csv' # optional
objectfile = 'objects_reduced.lst'
x_range = None
size_inches = [16.2, 10]
objects = ['*'] # Create a plot with everything
objects += read_text_file(objectfile, no_empty_lines=False)
if len(objects) == 1:
# Code defined what objects to use
objects = ['*', 'Sun', ['alpOri','alphori','alfori','alphaori'], 'AlphaAri', 'alpcmi', ['gamVirA','gamVir2'], ['gamVirB','gamVir1'], 'TauBoo', 'Tung' ]
select = []
if True:
selectd = [] # 'data'/'text', index x, index y, error index, label (empty to use header), color, linestyle, marker, markersize, [x_title, y_title]
#selectd.append([ 'y_range', -0.7, 0.7])
selectd.append([ 'data', 5, 8, None, '', 'g', '', 'o', 2, '', 'Offset [px]' ])
selectd.append([ 'data', 5, 10, 11, '', 'b', '', 'o', 2, '', 'Offset [px]' ])
selectd.append([ 'data', 5, 15, None, '', 'k', '', 'o', 2, '', 'Offset [px]' ])
select.append(selectd)
selectd = []
selectd.append([ 'data', 5, 9, None, '', 'g', '', 'o', 2, '', 'Width [px]' ])
selectd.append([ 'data', 5, 13, None, '', 'b', '', 'o', 2, '', 'Width [px]' ])
#selectd.append([ 'y_range', 0.5, 1.5])
select.append(selectd)
selectd = []
selectd.append([ 'data', 5, 12, None, '', 'k', '', 'o', 2, '', 'Number' ])
select.append(selectd)
selectd = []
selectd.append([ 'sensordata', 0, 1, None, 'Behind camera (water)', 'tab:blue', '', 'o', 2, '', '' ])
#selectd.append([ 'sensordata', 0, 2, None, 'Room - front right', 'tab:orange', '', 'o', 2, '', '' ])
selectd.append([ 'sensordata', 0, 3, None, 'Breadboard - next to grating holder', 'tab:green', '', 'o', 2, '', '' ])
#selectd.append([ 'sensordata', 0, 5, None, 'Spectrograph - low between fiber and AO', 'tab:red', '', 'o', 2, '', '' ])
selectd.append([ 'sensordata', 0, 6, None, 'Spectrograph - above fiber', 'tab:purple', '', 'o', 2, '', '' ])
#selectd.append([ 'sensordata', 0, 7, None, 'Spectrograph - front of grating', 'tab:brown', '', 'o', 2, '', '' ])
#selectd.append([ 'sensordata', 0, 9, None, 'On Breadboard - behind camera', 'tab:pink', '', 'o', 2, '', '' ])
selectd.append([ 'sensordata', 0, 10, None, 'Room/Water cooling', 'tab:gray', '', 'o', 2, '', '' ])
#selectd.append([ 'sensordata', 0, 11, None, 'Breadboard - next to grating holder', 'tab:olive', '', 'o', 2, 'JD [d]', 'Temperature' ])
selectd.append([ 'text', 2459342.011, 23, 'Helium off', 'k', 90, 'left', 'bottom' ])
selectd.append([ 'grid' ])
#selectd.append([ 'y_range', 20, 25])
#selectd.append([ 'text', 294, 40, 'Helium 1 l/min', 'k', 90, 'left', 'bottom' ])
select.append(selectd)
selectd = []
selectd.append([ 'data', 5, 6, None, '', 'k', '', 'o', 2, '', 'Flux (ADU)' ])
select.append(selectd)
selectd = []
#selectd.append([ 'y_range', -20, 70])
#selectd.append([ 'data', 17, 18, 20, '', 'grey', '', 'o', 2, '', 'RV [km/s]' ])
selectd.append([ 'data', 17, 19, 20, '', 'k', '', 'o', 2, '', 'RV [km/s]' ])
select.append(selectd)
selectd = []
selectd.append([ 'data', 17, 24, 25, '', 'r', '', 'o', 2, '', 'RV [m/s]' ])
selectd.append([ 'data', 17, 26, 27, '', 'c', '', 'o', 2, 'JD/BJD [d]', 'RV [m/s]' ])
#selectd.append([ 'text', 294, 40, 'Helium 1 l/min', 'k', 90, 'left', 'bottom' ])
#selectd.append([ 'y_range', -800, 400])
select.append(selectd)
#x_range = [-10, 470]
#size_inches = [10, 6]
if datafile.find(os.sep) == -1:
datafile = os.getcwd() + os.sep + datafile # To select settings depending on datafile
if os.path.isfile(sensorsfile):
with open(sensorsfile, 'r') as f:
header = list(csv.reader(f, delimiter=','))
data = np.array(header[1:])
times1 = [ get_julian_datetime( datetime.datetime.strptime(dat, '%Y%m%d-%H%M%S') ) for dat in data[:,0]]
times2 = [ get_julian_datetime( datetime.datetime.strptime(dat, '%Y%m%d-%H%M%S') ) for dat in data[:,-1]]
sensordata = np.vstack((times1, data[:,1:-1].astype(float).T, times2)).T
else:
sensordata = np.zeros((10,100))*np.nan
data = read_text_file(datafile, no_empty_lines=False)
if len(data) == 0:
print('Error: no datapoints found')
exit()
len_entries = len( data[0].split('\t') )
data = convert_readfile(data, [str]*len_entries, delimiter='\t', replaces=['\n', os.linesep])
data = np.array(data).T
header = data[:,0:3]
data = data[:,3:]
data[data==''] = 'nan'
converted = dict()
with PdfPages(savefile) as pdf:
for star in objects: # New page for each opject
x_range_data = [1E10, -1E10]
nr_g = len(select) # How many graphs
if type(star).__name__ in ['str']:
star = [star]
starindata = ( data[1,:] == star[0] )
for entry in copy.copy(star):
if entry == '*':
starindata[:] = True
break
starindata_e1 = [ (ii.lower().find(entry.lower()) > -1) for ii in data[0,:] ]
starindata_e2 = [ (ii.lower().find(entry.lower()) > -1) for ii in data[1,:] ]
starindata = (starindata + starindata_e1 + starindata_e2) > 0
if not np.any(starindata): # Only plot objects, that are in the data
continue
fig, frame = plt.subplots(nr_g,1, sharex=True)
fig.set_size_inches(size_inches[0], size_inches[1])
plt.subplots_adjust(left=0.05, right=0.85, top=0.95, bottom=0.14)
x_titles, y_titles = [], []
for ii_g in range(nr_g):
selectd = select[ii_g]
nr_d = len(selectd) # How many data sets
if nr_g == 1:
frame_ii_g = frame
else:
frame_ii_g = frame[ii_g]
if ii_g == 0:
frame_ii_g.set_title('{0}'.format(star))
x_title, y_title, y_range = '', '', None
for ii_d in range(nr_d):
if selectd[ii_d][0] in ['data','sensordata']:
[dset, indexx, indexy, indexe, label, color, linestyle, marker, markersize ] = selectd[ii_d][0:9]
if dset == 'sensordata':
x_range_tmp = copy.copy(frame_ii_g.get_xlim())
if indexy < 0:
indexy = abs(indexy)
sign = -1
else:
sign = 1
for index in [indexx, indexy, indexe]:
if index is None: continue
if '{0}_{1}'.format(index, dset) not in converted.keys():
if dset == 'data':
converted['{0}_{1}'.format(index, dset)] = data[index,:].astype(float)
elif dset == 'sensordata':
converted['{0}_{1}'.format(index, dset)] = sensordata[:,index]
#x_title = header[1,indexx]+' '+header[2,indexx]
#if x_title not in x_titles:
# x_titles.append(x_title)
if label == '' and dset == 'data':
label = header[indexy, 1]
if len(label) > 25:
for ii in list(range(25, 18, -1)) + list(range(25,min(len(label),35))):
if label[ii] == ' ':
label = label[:ii] + os.linesep + label[ii+1:]
break
if dset == 'data':
good_data = ~np.isnan(converted['{0}_{1}'.format(indexx, dset)]) & ~np.isnan(converted['{0}_{1}'.format(indexy, dset)]) & starindata
else:
good_data = np.ones_like(converted['{0}_{1}'.format(indexx, dset)], dtype=bool)
if np.sum(good_data) > 0: # Only plot if data is available
xx = converted['{0}_{1}'.format(indexx, dset)][good_data]
yy = sign*converted['{0}_{1}'.format(indexy, dset)][good_data]
if y_range is not None:
yy[ yy > y_range[1] ] = y_range[1]
yy[ yy < y_range[0] ] = y_range[0]
if dset == 'data':
x_range_data = [ min(np.min(xx), x_range_data[0]), max(np.max(xx), x_range_data[1]) ]
if indexe is None: # No error bars
frame_ii_g.plot(xx, yy, label=label, color=color, linestyle=linestyle, marker=marker, markersize=markersize)
else: # error bars
frame_ii_g.errorbar(xx, yy, yerr=converted['{0}_{1}'.format(indexe, dset)][good_data], label=label, color=color, linestyle=linestyle, marker=marker, markersize=markersize)
if len(selectd[ii_d]) == 11:
if len(selectd[ii_d][9]) > 0: x_title = selectd[ii_d][9]
if len(selectd[ii_d][10]) > 0: y_title = selectd[ii_d][10]
if dset == 'sensordata':
frame_ii_g.set_xlim(x_range_tmp[0],x_range_tmp[1])
elif selectd[ii_d][0] == 'text':
[posx, posy, text, color, rotation, hpos, vpos ] = selectd[ii_d][1:8]
frame_ii_g.text( posx, posy, text, horizontalalignment=hpos, verticalalignment=vpos, rotation=rotation, color=color, zorder=5 )
elif selectd[ii_d][0] == 'y_range':
y_range = selectd[ii_d][1:3]
elif selectd[ii_d][0] == 'grid':
frame_ii_g.grid(which='both', axis='both')
frame_ii_g.legend(loc='upper left', bbox_to_anchor=( 1.0,1.01), fontsize=11, handletextpad=0.2)
frame_ii_g.set_xlabel(x_title, fontsize=11)
frame_ii_g.set_ylabel(y_title, fontsize=11)
frame_ii_g.yaxis.set_ticks_position('both')
if y_range is not None:
frame_ii_g.set_ylim(y_range[0],y_range[1])
if x_range is not None:
frame_ii_g.set_xlim(x_range[0],x_range[1])
elif x_range_data[0] < 1E9 and x_range_data[1] > -1E9:
b = 0.01 * (x_range_data[1] - x_range_data[0])
frame_ii_g.set_xlim(x_range_data[0]-b,x_range_data[1]+b)
pdf.savefig() # saves the current figure into a pdf page
plt.close()