class Plot():
"""This class is used to generate the figures for the plots."""
def __init__(self):
""" Description of init """
# Create the option parser for the command line options
usage = (
'usage: %prog [options]\n\n'
'All options are strings. Boolean options are true when they \n'
'contains a certain specific keywords, which is written in \n'
'the option description in parantheses.')
parser = OptionParser(usage=usage)
# Add the options to the option parser
parser.add_option('-a',
'--type',
help='Type string from '
'graphsettings.xml')
parser.add_option('-b', '--idlist', help='List of id\'s to plot')
parser.add_option('-c',
'--from_d',
help='From timestamp, format: '
'YYYY-MM-DD HH:MM')
parser.add_option('-d',
'--to_d',
help='To timestamp, format: '
'YYYY-MM-DD HH:MM')
parser.add_option('-e', '--xmin', help='X-min for zoom')
parser.add_option('-f', '--xmax', help='X-max for zoom')
parser.add_option('-g', '--ymin', help='Y-min for zoom')
parser.add_option('-i', '--ymax', help='Y-max for zoom')
parser.add_option('-j',
'--offset',
help='List of offsets for the '
'graphs (for plots that goes on a log scale and has '
'negative values)')
parser.add_option(
'-k',
'--as_function_of_t',
help='Plot the graphs as '
'a function of temperature (boolean \'checked\'=True)')
parser.add_option('-l',
'--logscale',
help='Use a log for the right '
'axis (boolean \'checked\'=True)')
parser.add_option('-m',
'--shift_temp_unit',
help='Change between K '
'and C when values are plotted as a function of '
'temperature (boolean \'checked\'=True)')
parser.add_option('-n',
'--flip_x',
help='Exchange min and max for the '
'x-axis (boolean \'checked\'=True)')
parser.add_option('-o',
'--shift_be_ke',
help='Shift between binding '
'energy and kinetic energy for XPS plots (boolean '
'\'checked\'=True)')
# -p is availabel from previous options
parser.add_option(
'-q',
'--image_format',
help='Image format for the '
'figure exports, given as the figure extension. Can '
'be svg, eps, ps, pdf and default. Default means use '
'the one in graphsettings.xml or internal deaault.')
parser.add_option('-r',
'--small_plot',
help='Produce a small plot '
'(boolean \'checked\'=1)')
# Parse the options
(options, args) = parser.parse_args()
### Process options - all options are given as string, and they need to
### be converted into other data types
# Convert idlist
self.idlist = [
int(element) for element in options.idlist.split(',')[1:]
]
# Turn the offset 'key:value,' pair string into a dictionary
self.offsets = dict([[int(offset.split(':')[0]),
offset.split(':')[1]]
for offset in options.offset.split(',')[1:]])
# Gather from and to in a fictionary
self.from_to = {'from': options.from_d, 'to': options.to_d}
# Turn several options into booleans
self.as_function_of_t = True if options.as_function_of_t ==\
'checked' else False
self.shift_temp_unit = True if options.shift_temp_unit ==\
'checked' else False
self.logscale = True if options.logscale == 'checked' else False
self.flip_x = True if options.flip_x == 'checked' else False
self.shift_be_ke = True if options.shift_be_ke == 'checked' else False
self.small_plot = True if options.small_plot == '1' else False
### Create database backend object
self.db = dataBaseBackend(typed=options.type,
from_to=self.from_to,
id_list=self.idlist,
offsets=self.offsets,
as_function_of_t=self.as_function_of_t,
shift_temp_unit=self.shift_temp_unit,
shift_be_ke=self.shift_be_ke)
### Ask self.db for a measurement count
measurement_count = self.db.get_data_count()
# Set the image format to standard, overwite with gs value and again
# options value if i exits
if options.image_format:
if options.image_format == 'default':
if self.db.global_settings.has_key('image_format'):
self.image_format = self.db.global_settings['image_format']
else:
self.image_format = 'png'
else:
self.image_format = options.image_format
else:
self.image_format = 'png'
# Create a hash from the measurement_count, options and
#self.db.global_settings
hash = hashlib.md5()
hash.update(
str(options) + str(self.db.global_settings) +
str(measurement_count))
# self.namehash is unique for this plot and will form the filename
self.namehash = ('/var/www/cinfdata/figures/' + hash.hexdigest() +
'.' + self.image_format)
# For use in other methods
self.options = options
# object to give first good color, and then random colors
self.c = Color()
self.left_color = 'black'
self.right_color = 'black'
def main(self):
if os.path.exists(self.namehash) and False:
print self.namehash
else:
# Call a bunch of functions
self._init_plot()
self._plot()
if self.left_color != 'black':
if self.right_color != 'black':
self.c.color_axis(self.ax1, self.ax2, self.left_color,
self.right_color)
else:
self.c.color_axis(self.ax1, None, self.left_color, None)
self._legend()
self._zoom_and_flip()
self._transform_and_label_axis()
if not self.small_plot:
self._title()
self._grids()
self._save()
def _init_plot(self):
### Apply settings
# Small plots
if self.small_plot:
# Apply default settings
plt.rcParams.update({
'figure.figsize': [4.5, 3.0],
'ytick.labelsize': 'x-small',
'xtick.labelsize': 'x-small',
'legend.fontsize': 'x-small'
})
# Overwrite with values from graphsettings
plt.rcParams.update(self.db.global_settings['rcparams_small'])
else:
plt.rcParams.update({
'figure.figsize': [9.0, 6.0],
'axes.titlesize': '24',
'legend.fontsize': 'small'
})
plt.rcParams.update(self.db.global_settings['rcparams_regular'])
self.fig = plt.figure(1)
self.ax1 = self.fig.add_subplot(111)
self.ax2 = None
# Decide on the y axis type
self.gs = self.db.global_settings
if self.logscale:
self.ax1.set_yscale('log')
elif self.gs['default_yscale'] == 'log':
self.ax1.set_yscale('log')
def _plot(self):
# Make plot
data_in_plot = False
for data in self.db.get_data():
if len(data['data']) > 0:
data_in_plot = data_in_plot or True
# Speciel case for barplots
if self.db.global_settings.has_key('default_style') and\
self.db.global_settings['default_style'] == 'barplot':
self.ax1.bar(data['data'][:, 0],
data['data'][:, 1],
color=self.c.get_color())
# Normal graph styles
else:
# If the graph go on the right side of the plot
if data['info']['on_the_right']:
# Initialise secondary plot if it isn't already
if not self.ax2:
self._init_second_y_axis()
# If info has a color (i.e. it is given in gs ordering)
if data['info'].has_key('color'):
# Set the color for the graph and axis
color = data['info']['color']
self.right_color = data['info']['color']
else:
# Else get a new color from self.c
color = self.c.get_color()
# Make the actual plot
self.ax2.plot(data['data'][:, 0],
data['data'][:, 1],
color=color,
label=self._legend_item(data) + '(R)')
# If the graph does not go on the right side of the plot
else:
# If info has a color (i.e. it is given in gs ordering)
if data['info'].has_key('color'):
# Set the color for the graph and axis
color = data['info']['color']
self.left_color = data['info']['color']
else:
# Else get a new color from self.c
color = self.c.get_color()
# Make the actual plot
self.ax1.plot(data['data'][:, 0],
data['data'][:, 1],
color=color,
label=self._legend_item(data))
# If no data has been been put on the graph at all, explain why there
# is none
if not data_in_plot:
y = 0.00032 if self.logscale or self.gs[
'default_yscale'] == 'log' else 0.5
self.ax1.text(0.5,
y,
'No data',
horizontalalignment='center',
verticalalignment='center',
color='red',
size=60)
def _legend(self):
if self.db.global_settings['default_xscale'] != 'dat':
ax1_legends = self.ax1.get_legend_handles_labels()
if self.ax2:
ax2_legends = self.ax2.get_legend_handles_labels()
for color, text in zip(ax2_legends[0], ax2_legends[1]):
ax1_legends[0].append(color)
ax1_legends[1].append(text)
# loc for locations, 0 means 'best'. Why that isn't deafult I
# have no idea
self.ax1.legend(ax1_legends[0], ax1_legends[1], loc=0)
def _zoom_and_flip(self):
# Now we are done with the plotting, change axis if necessary
# Get current axis limits
self.axis = self.ax1.axis()
if self.options.xmin != self.options.xmax:
self.axis = (float(self.options.xmin), float(self.options.xmax)) +\
self.axis[2:4]
if self.options.ymin != self.options.ymax:
self.axis = self.axis[0:2] + (float(
self.options.ymin), float(self.options.ymax))
if self.flip_x:
self.axis = (self.axis[1], self.axis[0]) + self.axis[2:4]
self.ax1.axis(self.axis)
def _transform_and_label_axis(self):
""" Transform X-AXIS axis and label it """
# If it is a date plot
if self.db.global_settings['default_xscale'] == 'dat':
# Turn the x-axis into timemarks
# IMPLEMENT add something to TimeMarks initialisation to take care
# or morning_pressure
markformat = '%H:%M' if self.small_plot else '%b-%d %H:%M'
timemarks = TimeMarks(self.axis[0],
self.axis[1],
markformat=markformat)
(old_tick_labels, new_tick_labels) = timemarks.get_time_marks()
self.ax1.set_xticks(old_tick_labels)
self.bbox_xlabels = self.ax1.\
set_xticklabels(new_tick_labels, rotation=25,
horizontalalignment='right')
# Make a little extra room for the rotated x marks
#self.fig.subplots_adjust(bottom=0.12)
elif self.options.type == 'masstime':
gs_temp_unit = self.gs['temperature_unit']
other_temp_unit = 'C' if gs_temp_unit == 'K' else 'K'
cur_temp_unit = other_temp_unit if self.shift_temp_unit else\
gs_temp_unit
if self.as_function_of_t and not self.small_plot:
self.ax1.set_xlabel(self.gs['t_xlabel'] + cur_temp_unit)
elif not self.small_plot:
self.ax1.set_xlabel(self.gs['xlabel'])
elif self.options.type == 'xps':
if self.shift_be_ke and not self.small_plot:
self.ax1.set_xlabel(self.gs['alt_xlabel'])
elif not self.small_plot:
self.ax1.set_xlabel(self.gs['xlabel'])
elif not self.small_plot:
self.ax1.set_xlabel(self.gs['xlabel'])
# Label Y-axis
if not self.small_plot:
self.ax1.set_ylabel(self.gs['ylabel'], color=self.left_color)
if self.ax2:
self.ax2.set_ylabel(self.gs['right_ylabel'],
color=self.right_color)
def _title(self):
""" TITLE """
# Set the title and raise it a bit
if self.as_function_of_t:
self.bbox_title = self.ax1.set_title(self.gs['t_title'], y=1.03)
else:
self.bbox_title = self.ax1.set_title(self.gs['title'], y=1.03)
def _grids(self):
# GRIDS
self.ax1.grid(b=True, which='major')
#plt.xscale('linear')
#plt.xticks(range(0,100,10))
#plt.x_minor_ticks(range(0,100,10))
#plt.grid(b='on', which='minor')
#plt.grid(b='on', which='major')
def _save(self):
## Filesave
# Save
self.fig.savefig(self.namehash, bbox_inches='tight', pad_inches=0.03)
# This is the magical line that plot.php opens
# For the script to work this has to be the only print statement
print self.namehash
### Here start the small helper functions that are called from the main flow
def _init_second_y_axis(self):
self.ax2 = self.ax1.twinx()
if self.db.global_settings['right_yscale'] == 'log':
self.ax2.set_yscale('log')
def _legend_item(self, data):
if self.db.global_settings['default_xscale'] == 'dat':
return ''
elif data['gs'].has_key('legend_field_name') and\
data['info'][data['gs']['legend_field_name']]:
return data['info']['mass_label'] + '-' + str(data['info']['id'])
else:
return str(data['info']['id'])
class Plot():
"""This class is used to generate the figures for the plots."""
def __init__(self, options, ggs):
""" Description of init """
self.o = options
self.ggs = ggs
# Set the image format to standard, overwite with ggs value and again
# options value if it exits
if self.o['image_format'] == '':
self.image_format = self.ggs['image_format']
else:
self.image_format = self.o['image_format']
# Default values for matplotlib plots (names correspond to ggs names)
mpl_settings = {'width': 900,
'height': 600,
'title_size': '24',
'xtick_labelsize': '12',
'ytick_labelsize': '12',
'legend_fontsize': '10',
'label_fontsize': '16',
'linewidth': 1.0,
'grid': False}
# Owerwrite defaults with gs values and convert to appropriate types
for key, value in mpl_settings.items():
try:
mpl_settings[key] = type(value)(self.ggs['matplotlib_settings'][key])
except KeyError:
pass
# Write some settings to pyplot
rc_temp = {'figure.figsize': [float(mpl_settings['width'])/100,
float(mpl_settings['height'])/100],
'axes.titlesize': mpl_settings['title_size'],
'xtick.labelsize': mpl_settings['xtick_labelsize'],
'ytick.labelsize': mpl_settings['ytick_labelsize'],
'legend.fontsize': mpl_settings['legend_fontsize'],
'axes.labelsize': mpl_settings['label_fontsize'],
'lines.linewidth': mpl_settings['linewidth'],
'axes.grid': mpl_settings['grid']
}
plt.rcParams.update(rc_temp)
# Plotting options
self.maxticks=15
self.tz = GMT1()
self.right_yaxis = len(self.o['right_plotlist']) > 0
self.measurement_count = None
# object to give first good color, and then random colors
self.c = Color()
def new_plot(self, data, plot_info, measurement_count):
""" Form a new plot with the given data and info """
self.measurement_count = sum(measurement_count)
self._init_plot()
self._plot(data)
self._zoom_and_flip()
self._title_and_labels(plot_info)
self._save(plot_info)
def _init_plot(self):
""" Initialize plot """
self.fig = plt.figure(1)
self.ax1 = self.fig.add_subplot(111)
if self.right_yaxis:
self.ax2 = self.ax1.twinx()
if self.o['left_logscale']:
self.ax1.set_yscale('log')
if self.right_yaxis and self.o['right_logscale']:
self.ax2.set_yscale('log')
def _plot(self, data):
""" Determine the type of the plot and make the appropriate plot by use
of the functions:
_plot_dateplot
_plot_xyplot
"""
if self.ggs['default_xscale'] == 'dat':
self._plot_dateplot(data)
else:
self._plot_xyplot(data)
def _plot_dateplot(self, data):
""" Make the date plot """
# Rotate datemarks on xaxis
self.ax1.set_xticklabels([], rotation=25, horizontalalignment='right')
# Left axis
for dat in data['left']:
# Form legend
if dat['lgs'].has_key('legend'):
legend = dat['lgs']['legend']
else:
legend = None
# Plot
if len(dat['data']) > 0:
self.ax1.plot_date(mdates.epoch2num(dat['data'][:,0]),
dat['data'][:,1],
label=legend,
xdate=True,
color=self.c.get_color(),
tz=self.tz,
fmt='-')
# Right axis
for dat in data['right']:
# Form legend
if dat['lgs'].has_key('legend'):
legend = dat['lgs']['legend']
else:
legend = None
# Plot
if len(dat['data']) > 0:
self.ax2.plot_date(mdates.epoch2num(dat['data'][:,0]),
dat['data'][:,1],
label=legend,
xdate=True,
color=self.c.get_color(),
tz=self.tz,
fmt='-')
# No data
if self.measurement_count == 0:
y = 0.00032 if self.o['left_logscale'] is True else 0.5
self.ax1.text(0.5, y, 'No data', horizontalalignment='center',
verticalalignment='center', color='red', size=60)
def _plot_xyplot(self, data):
# Left axis
for dat in data['left']:
# Form legend
if dat['lgs'].has_key('legend'):
legend = dat['lgs']['legend']
else:
legend = None
# Plot
if len(dat['data']) > 0:
self.ax1.plot(dat['data'][:,0],
dat['data'][:,1],
'-',
label=legend,
color=self.c.get_color(),
)
# Right axis
for dat in data['right']:
# Form legend
if dat['lgs'].has_key('legend'):
legend = dat['lgs']['legend']
else:
legend = None
# Plot
if len(dat['data']) > 0:
self.ax2.plot(dat['data'][:,0],
dat['data'][:,1],
'-',
label=legend,
color=self.c.get_color()
)
# No data
if self.measurement_count == 0:
y = 0.00032 if self.o['left_logscale'] is True else 0.5
self.ax1.text(0.5, y, 'No data', horizontalalignment='center',
verticalalignment='center', color='red', size=60)
def _zoom_and_flip(self):
""" Apply the y zooms.
NOTE: self.ax1.axis() return a list of bounds [xmin,xmax,ymin,ymax] and
we reuse x and replace y)
"""
# Left axis
if self.o['left_yscale_bounding'] is not None:
self.ax1.axis(self.ax1.axis()[0:2] + self.o['left_yscale_bounding'])
# Right axis
if self.right_yaxis and self.o['right_yscale_bounding'] is not None:
self.ax2.axis(self.ax2.axis()[0:2] + self.o['right_yscale_bounding'])
if self.o['flip_x']:
self.ax1.axis((self.ax1.axis()[1], self.ax1.axis()[0]) + self.ax1.axis()[2:4])
def _title_and_labels(self, plot_info):
""" Put title and labels on the plot """
# xlabel
if plot_info.has_key('xlabel'):
label = plot_info['xlabel']
if plot_info['xlabel_addition'] != '':
label += '\n' + plot_info['xlabel_addition']
self.ax1.set_xlabel(label)
if self.o['xlabel'] != '': # Manual override
self.ax1.set_xlabel(r'{0}'.format(self.o['xlabel']))
# Left ylabel
if plot_info.has_key('left_ylabel'):
label = plot_info['left_ylabel']
if plot_info['y_left_label_addition'] != '':
label += '\n' + plot_info['y_left_label_addition']
self.ax1.set_ylabel(label, multialignment='center')
if self.o['left_ylabel'] != '': # Manual override
self.ax1.set_ylabel(self.o['left_ylabel'], multialignment='center')
# Right ylabel
if self.right_yaxis and plot_info.has_key('right_ylabel'):
label = plot_info['right_ylabel']
if plot_info['y_right_label_addition'] != '':
label += '\n' + plot_info['y_right_label_addition']
self.ax2.set_ylabel(label, multialignment='center', rotation=270)
if self.o['right_ylabel'] != '': # Manual override
self.ax2.set_ylabel(self.o['right_ylabel'],
multialignment='center', rotation=270)
# Title
if plot_info.has_key('title'):
self.ax1.set_title(plot_info['title'], y=1.03)
if self.o['title'] != '':
# experiment with 'r{0}'.form .. at some time
self.ax1.set_title('{0}'.format(self.o['title']), y=1.03)
# Legends
if self.measurement_count > 0:
ax1_legends = self.ax1.get_legend_handles_labels()
if self.right_yaxis:
ax2_legends = self.ax2.get_legend_handles_labels()
for color, text in zip(ax2_legends[0], ax2_legends[1]):
ax1_legends[0].append(color)
ax1_legends[1].append(text)
# loc for locations, 0 means 'best'. Why that isn't deafult I
# have no idea
self.ax1.legend(ax1_legends[0], ax1_legends[1], loc=0)
def _save(self, plot_info):
""" Save the figure """
# The tight method only works if there is a title (it caps of parts of
# the axis numbers, therefore this hack, this may also become a problem
# for the other edges of the figure if there are no labels)
tight = ''
if plot_info.has_key('title'):
tight = 'tight'
# For some wierd reason we cannot write directly to sys.stdout when it
# is a pdf file, so therefore we use a the StringIO object workaround
if self.o['image_format'] == 'pdf':
import StringIO
out = StringIO.StringIO()
self.fig.savefig(out, bbox_inches=tight, pad_inches=0.03,
format=self.o['image_format'])
sys.stdout.write(out.getvalue())
else:
self.fig.savefig(sys.stdout, bbox_inches=tight, pad_inches=0.03,
format=self.o['image_format'])
class Plot():
"""This class is used to generate the figures for the plots."""
def __init__(self):
""" Description of init """
# Create the option parser for the command line options
usage = ('usage: %prog [options]\n\n'
'All options are strings. Boolean options are true when they \n'
'contains a certain specific keywords, which is written in \n'
'the option description in parantheses.')
parser = OptionParser(usage=usage)
# Add the options to the option parser
parser.add_option('-a', '--type', help='Type string from '
'graphsettings.xml')
parser.add_option('-b', '--idlist', help='List of id\'s to plot')
parser.add_option('-c', '--from_d', help='From timestamp, format: '
'YYYY-MM-DD HH:MM')
parser.add_option('-d', '--to_d', help='To timestamp, format: '
'YYYY-MM-DD HH:MM')
parser.add_option('-e', '--xmin', help='X-min for zoom')
parser.add_option('-f', '--xmax', help='X-max for zoom')
parser.add_option('-g', '--ymin', help='Y-min for zoom')
parser.add_option('-i', '--ymax', help='Y-max for zoom')
parser.add_option('-j', '--offset', help='List of offsets for the '
'graphs (for plots that goes on a log scale and has '
'negative values)')
parser.add_option('-k', '--as_function_of_t', help='Plot the graphs as '
'a function of temperature (boolean \'checked\'=True)')
parser.add_option('-l', '--logscale', help='Use a log for the right '
'axis (boolean \'checked\'=True)')
parser.add_option('-m', '--shift_temp_unit', help='Change between K '
'and C when values are plotted as a function of '
'temperature (boolean \'checked\'=True)')
parser.add_option('-n', '--flip_x', help='Exchange min and max for the '
'x-axis (boolean \'checked\'=True)')
parser.add_option('-o', '--shift_be_ke', help='Shift between binding '
'energy and kinetic energy for XPS plots (boolean '
'\'checked\'=True)')
# -p is availabel from previous options
parser.add_option('-q', '--image_format', help='Image format for the '
'figure exports, given as the figure extension. Can '
'be svg, eps, ps, pdf and default. Default means use '
'the one in graphsettings.xml or internal deaault.')
parser.add_option('-r', '--small_plot', help='Produce a small plot '
'(boolean \'checked\'=1)')
# Parse the options
(options, args) = parser.parse_args()
### Process options - all options are given as string, and they need to
### be converted into other data types
# Convert idlist
self.idlist = [int(element) for element in options.idlist.split(',')[1:]]
# Turn the offset 'key:value,' pair string into a dictionary
self.offsets = dict([[int(offset.split(':')[0]), offset.split(':')[1]]
for offset in options.offset.split(',')[1:]])
# Gather from and to in a fictionary
self.from_to = {'from':options.from_d, 'to':options.to_d}
# Turn several options into booleans
self.as_function_of_t = True if options.as_function_of_t ==\
'checked' else False
self.shift_temp_unit = True if options.shift_temp_unit ==\
'checked' else False
self.logscale = True if options.logscale == 'checked' else False
self.flip_x = True if options.flip_x == 'checked' else False
self.shift_be_ke = True if options.shift_be_ke == 'checked' else False
self.small_plot = True if options.small_plot == '1' else False
### Create database backend object
self.db = dataBaseBackend(typed=options.type, from_to=self.from_to,
id_list=self.idlist, offsets=self.offsets,
as_function_of_t=self.as_function_of_t,
shift_temp_unit=self.shift_temp_unit,
shift_be_ke=self.shift_be_ke)
### Ask self.db for a measurement count
measurement_count = self.db.get_data_count()
# Set the image format to standard, overwite with gs value and again
# options value if i exits
if options.image_format:
if options.image_format == 'default':
if self.db.global_settings.has_key('image_format'):
self.image_format = self.db.global_settings['image_format']
else:
self.image_format = 'png'
else:
self.image_format = options.image_format
else:
self.image_format = 'png'
# Create a hash from the measurement_count, options and
#self.db.global_settings
hash = hashlib.md5()
hash.update(str(options) + str(self.db.global_settings) +
str(measurement_count))
# self.namehash is unique for this plot and will form the filename
self.namehash = ('/var/www/cinfdata/figures/' + hash.hexdigest() + '.' +
self.image_format)
# For use in other methods
self.options = options
# object to give first good color, and then random colors
self.c = Color()
self.left_color = 'black'
self.right_color = 'black'
def main(self):
if os.path.exists(self.namehash) and False:
print self.namehash
else:
# Call a bunch of functions
self._init_plot()
self._plot()
if self.left_color != 'black':
if self.right_color != 'black':
self.c.color_axis(self.ax1, self.ax2, self.left_color, self.right_color)
else:
self.c.color_axis(self.ax1, None, self.left_color, None)
self._legend()
self._zoom_and_flip()
self._transform_and_label_axis()
if not self.small_plot:
self._title()
self._grids()
self._save()
def _init_plot(self):
### Apply settings
# Small plots
if self.small_plot:
# Apply default settings
plt.rcParams.update({'figure.figsize':[4.5, 3.0],
'ytick.labelsize':'x-small',
'xtick.labelsize':'x-small',
'legend.fontsize':'x-small'})
# Overwrite with values from graphsettings
plt.rcParams.update(self.db.global_settings['rcparams_small'])
else:
plt.rcParams.update({'figure.figsize':[9.0, 6.0],
'axes.titlesize':'24',
'legend.fontsize':'small'})
plt.rcParams.update(self.db.global_settings['rcparams_regular'])
self.fig = plt.figure(1)
self.ax1 = self.fig.add_subplot(111)
self.ax2 = None
# Decide on the y axis type
self.gs = self.db.global_settings
if self.logscale:
self.ax1.set_yscale('log')
elif self.gs['default_yscale'] == 'log':
self.ax1.set_yscale('log')
def _plot(self):
# Make plot
data_in_plot = False
for data in self.db.get_data():
if len(data['data']) > 0:
data_in_plot = data_in_plot or True
# Speciel case for barplots
if self.db.global_settings.has_key('default_style') and\
self.db.global_settings['default_style'] == 'barplot':
self.ax1.bar(data['data'][:,0], data['data'][:,1],
color=self.c.get_color())
# Normal graph styles
else:
# If the graph go on the right side of the plot
if data['info']['on_the_right']:
# Initialise secondary plot if it isn't already
if not self.ax2:
self._init_second_y_axis()
# If info has a color (i.e. it is given in gs ordering)
if data['info'].has_key('color'):
# Set the color for the graph and axis
color = data['info']['color']
if 'overview' in self.options.type:
self.right_color = data['info']['color']
else:
# Else get a new color from self.c
color = self.c.get_color()
# Make the actual plot
self.ax2.plot(data['data'][:,0], data['data'][:,1],
color=color,
label=self._legend_item(data)+'(R)')
# If the graph does not go on the right side of the plot
else:
# If info has a color (i.e. it is given in gs ordering)
if data['info'].has_key('color'):
# Set the color for the graph and axis
color = data['info']['color']
if 'overview' in self.options.type:
self.left_color = data['info']['color']
else:
# Else get a new color from self.c
color = self.c.get_color()
# Make the actual plot
self.ax1.plot(data['data'][:,0], data['data'][:,1],
color=color,
label=self._legend_item(data))
# If no data has been been put on the graph at all, explain why there
# is none
if not data_in_plot:
y = 0.00032 if self.logscale or self.gs['default_yscale'] == 'log' else 0.5
self.ax1.text(0.5, y, 'No data', horizontalalignment='center',
verticalalignment='center', color='red', size=60)
def _legend(self):
if self.db.global_settings['default_xscale'] != 'dat':
ax1_legends = self.ax1.get_legend_handles_labels()
if self.ax2:
ax2_legends = self.ax2.get_legend_handles_labels()
for color, text in zip(ax2_legends[0], ax2_legends[1]):
ax1_legends[0].append(color)
ax1_legends[1].append(text)
# loc for locations, 0 means 'best'. Why that isn't deafult I
# have no idea
self.ax1.legend(ax1_legends[0], ax1_legends[1], loc=0)
def _zoom_and_flip(self):
# Now we are done with the plotting, change axis if necessary
# Get current axis limits
self.axis = self.ax1.axis()
if self.options.xmin != self.options.xmax:
self.axis = (float(self.options.xmin), float(self.options.xmax)) +\
self.axis[2:4]
if self.options.ymin != self.options.ymax:
self.axis = self.axis[0:2] + (float(self.options.ymin),
float(self.options.ymax))
if self.flip_x:
self.axis = (self.axis[1], self.axis[0]) + self.axis[2:4]
self.ax1.axis(self.axis)
def _transform_and_label_axis(self):
""" Transform X-AXIS axis and label it """
# If it is a date plot
if self.db.global_settings['default_xscale'] == 'dat':
# Turn the x-axis into timemarks
# IMPLEMENT add something to TimeMarks initialisation to take care
# or morning_pressure
markformat = '%H:%M' if self.small_plot else '%b-%d %H:%M'
timemarks = TimeMarks(self.axis[0], self.axis[1],
markformat=markformat)
(old_tick_labels, new_tick_labels) = timemarks.get_time_marks()
self.ax1.set_xticks(old_tick_labels)
self.bbox_xlabels = self.ax1.\
set_xticklabels(new_tick_labels, rotation=25,
horizontalalignment='right')
# Make a little extra room for the rotated x marks
#self.fig.subplots_adjust(bottom=0.12)
elif self.options.type == 'masstime':
gs_temp_unit = self.gs['temperature_unit']
other_temp_unit = 'C' if gs_temp_unit == 'K' else 'K'
cur_temp_unit = other_temp_unit if self.shift_temp_unit else\
gs_temp_unit
if self.as_function_of_t and not self.small_plot:
self.ax1.set_xlabel(self.gs['t_xlabel'] + cur_temp_unit)
elif not self.small_plot:
self.ax1.set_xlabel(self.gs['xlabel'])
elif self.options.type == 'xps':
if self.shift_be_ke and not self.small_plot:
self.ax1.set_xlabel(self.gs['alt_xlabel'])
elif not self.small_plot:
self.ax1.set_xlabel(self.gs['xlabel'])
elif not self.small_plot:
self.ax1.set_xlabel(self.gs['xlabel'])
# Label Y-axis
if not self.small_plot:
self.ax1.set_ylabel(self.gs['ylabel'], color=self.left_color)
if self.ax2:
self.ax2.set_ylabel(self.gs['right_ylabel'], color=self.right_color)
def _title(self):
""" TITLE """
# Set the title and raise it a bit
if self.as_function_of_t:
self.bbox_title = self.ax1.set_title(
self.gs['t_title'], y=1.03)
else:
self.bbox_title = self.ax1.set_title(
self.gs['title'], y=1.03)
def _grids(self):
# GRIDS
self.ax1.grid(b=True, which = 'major')
#plt.xscale('linear')
#plt.xticks(range(0,100,10))
#plt.x_minor_ticks(range(0,100,10))
#plt.grid(b='on', which='minor')
#plt.grid(b='on', which='major')
def _save(self):
## Filesave
# Save
self.fig.savefig(self.namehash, bbox_inches='tight', pad_inches=0.03)
# This is the magical line that plot.php opens
# For the script to work this has to be the only print statement
print self.namehash
### Here start the small helper functions that are called from the main flow
def _init_second_y_axis(self):
self.ax2 = self.ax1.twinx()
if self.db.global_settings['right_yscale'] == 'log':
self.ax2.set_yscale('log')
def _legend_item(self, data):
if self.db.global_settings['default_xscale'] == 'dat':
return ''
elif data['gs'].has_key('legend_field_name') and\
data['info'][data['gs']['legend_field_name']]:
return data['info']['mass_label'] + '-' + str(data['info']['id'])
else:
return str(data['info']['id'])
class Plot():
"""This class is used to generate the figures for the plots."""
def __init__(self, options, ggs):
""" Description of init """
self.o = options
self.ggs = ggs
# Set the image format to standard, overwite with ggs value and again
# options value if it exits
if self.o['image_format'] == '':
self.image_format = self.ggs['image_format']
else:
self.image_format = self.o['image_format']
# Default values for matplotlib plots (names correspond to ggs names)
mpl_settings = {'width': 900,
'height': 600,
'title_size': '24',
'xtick_labelsize': '12',
'ytick_labelsize': '12',
'legend_fontsize': '10',
'label_fontsize': '16',
'linewidth': 1.0,
'grid': False}
# Owerwrite defaults with gs values and convert to appropriate types
for key, value in mpl_settings.items():
try:
mpl_settings[key] = type(value)(self.ggs['matplotlib_settings'][key])
except KeyError:
pass
# Write some settings to pyplot
rc_temp = {'figure.figsize': [float(mpl_settings['width'])/100,
float(mpl_settings['height'])/100],
'axes.titlesize': mpl_settings['title_size'],
'xtick.labelsize': mpl_settings['xtick_labelsize'],
'ytick.labelsize': mpl_settings['ytick_labelsize'],
'legend.fontsize': mpl_settings['legend_fontsize'],
'axes.labelsize': mpl_settings['label_fontsize'],
'lines.linewidth': mpl_settings['linewidth'],
'axes.grid': mpl_settings['grid']
}
plt.rcParams.update(rc_temp)
# Plotting options
self.maxticks=15
self.tz = timezone('Europe/Copenhagen')
self.right_yaxis = None
self.measurement_count = None
# Colors object, will be filled in at new_plot
self.c = None
def new_plot(self, data, plot_info, measurement_count):
""" Form a new plot with the given data and info """
self.c = Color(data, self.ggs)
self.measurement_count = sum(measurement_count)
self._init_plot(data)
# _plot returns True or False to indicate whether the plot is good
if self._plot(data):
self._zoom_and_flip(data)
self._title_and_labels(plot_info)
self._save(plot_info)
def _init_plot(self, data):
""" Initialize plot """
self.fig = plt.figure(1)
self.ax1 = self.fig.add_subplot(111)
# We only activate the right y-axis, if there there points to put on it
self.right_yaxis = sum([len(dat['data']) for dat in data['right']]) > 0
if self.right_yaxis:
self.ax2 = self.ax1.twinx()
if self.o['left_logscale']:
self.ax1.set_yscale('log')
if self.right_yaxis and self.o['right_logscale']:
self.ax2.set_yscale('log')
def _plot(self, data):
""" Determine the type of the plot and make the appropriate plot by use
of the functions:
_plot_dateplot
_plot_xyplot
"""
if self.ggs['default_xscale'] == 'dat':
return self._plot_dateplot(data)
else:
return self._plot_xyplot(data)
def _plot_dateplot(self, data):
""" Make the date plot """
# Rotate datemarks on xaxis
self.ax1.set_xticklabels([], rotation=25, horizontalalignment='right')
# Test for un-workable plot configurations
error_msg = None
# Test if there is data on the left axis
if sum([len(dat['data']) for dat in data['left']]) == 0:
error_msg = 'There must\nbe data on\nthe left y-axis'
# Test if there is any data at all
if self.measurement_count == 0:
error_msg = 'No data'
# No data
if error_msg:
y = 0.00032 if self.o['left_logscale'] is True else 0.5
self.ax1.text(0.5, y, error_msg, horizontalalignment='center',
verticalalignment='center', color='red', size=60)
return False
# Left axis
for dat in data['left']:
# Form legend
if dat['lgs'].has_key('legend'):
legend = dat['lgs']['legend']
else:
legend = None
# Plot
if len(dat['data']) > 0:
self.ax1.plot_date(mdates.epoch2num(dat['data'][:,0]),
dat['data'][:,1],
label=legend,
xdate=True,
color=self.c.get_color(),
tz=self.tz,
fmt='-')
# Right axis
if self.right_yaxis:
for dat in data['right']:
# Form legend
if dat['lgs'].has_key('legend'):
legend = dat['lgs']['legend']
else:
legend = None
# Plot
if len(dat['data']) > 0:
self.ax2.plot_date(mdates.epoch2num(dat['data'][:,0]),
dat['data'][:,1],
label=legend,
xdate=True,
color=self.c.get_color(),
tz=self.tz,
fmt='-')
# Set xtick formatter (only if we have points)
if self.measurement_count > 0:
xlim = self.ax1.set_xlim()
diff = max(xlim) - min(xlim) # in days
format_out = '%H:%M:%S' # Default
# Diff limit to date format translation, will pick the format
# format of the largest limit the diff is larger than. Limits
# are in minutes.
formats = [
[1.0, '%a %H:%M'], # Larger than 1 day
[7.0, '%Y-%m-%d'], # Larger than 7 day
[7*30., '%Y-%m'], # Larger than 3 months
]
for limit, format in formats:
if diff > limit:
format_out = format
fm = mdates.DateFormatter(format_out, tz=self.tz)
self.ax1.xaxis.set_major_formatter(fm)
# Indicate that the plot is good
return True
def _plot_xyplot(self, data):
# Left axis
for dat in data['left']:
# Form legend
if dat['lgs'].has_key('legend'):
legend = dat['lgs']['legend']
else:
legend = None
# Plot
if len(dat['data']) > 0:
self.ax1.plot(dat['data'][:,0],
dat['data'][:,1],
'-',
label=legend,
color=self.c.get_color(dat['lgs']['id']),
)
# Right axis
for dat in data['right']:
# Form legend
if dat['lgs'].has_key('legend'):
legend = dat['lgs']['legend']
else:
legend = None
# Plot
if len(dat['data']) > 0:
self.ax2.plot(dat['data'][:,0],
dat['data'][:,1],
'-',
label=legend,
color=self.c.get_color(dat['lgs']['id'])
)
# No data
if self.measurement_count == 0:
y = 0.00032 if self.o['left_logscale'] is True else 0.5
self.ax1.text(0.5, y, 'No data', horizontalalignment='center',
verticalalignment='center', color='red', size=60)
# Indicate that the plot is good
return True
def _zoom_and_flip(self, data):
""" Apply the y zooms.
NOTE: self.ax1.axis() return a list of bounds [xmin,xmax,ymin,ymax] and
we reuse x and replace y)
"""
left_yscale_inferred = self.o['left_yscale_bounding']
right_yscale_inferred = self.o['right_yscale_bounding']
# X-axis zoom and infer y-axis zoom implications
if self.o['xscale_bounding'] is not None and\
self.o['xscale_bounding'][1] > self.o['xscale_bounding'][0]:
# Set the x axis scaling, unsure if we should do it for ax2 as well
self.ax1.set_xlim(self.o['xscale_bounding'])
# With no specific left y-axis zoom, infer it from x-axis zoom
if left_yscale_inferred is None:
left_yscale_inferred = self._infer_y_on_x_zoom(
data['left'], self.o['left_logscale'])
# With no specific right y-axis zoom, infer it from x-axis zoom
if right_yscale_inferred is None and self.right_yaxis:
right_yscale_inferred = self._infer_y_on_x_zoom(
data['right'])
# Left axis
if left_yscale_inferred is not None:
self.ax1.set_ylim(left_yscale_inferred)
# Right axis
if self.right_yaxis and right_yscale_inferred is not None:
self.ax2.set_ylim(right_yscale_inferred)
if self.o['flip_x']:
self.ax1.set_xlim((self.ax1.set_xlim()[1],self.ax1.set_xlim()[0]))
def _infer_y_on_x_zoom(self, list_of_data_sets, log=None):
"""Infer the implied Y axis zoom with an X axis zoom, for one y axis"""
yscale_inferred = None
min_candidates = []
max_candidates = []
for dat in list_of_data_sets:
# Make mask that gets index for points where x is within bounds
mask = (dat['data'][:, 0] > self.o['xscale_bounding'][0]) &\
(dat['data'][:, 0] < self.o['xscale_bounding'][1])
# Gets all the y values from that mask
reduced = dat['data'][mask, 1]
# Add min/max candidates
if len(reduced) > 0:
min_candidates.append(np.min(reduced))
max_candidates.append(np.max(reduced))
# If there are min/max candidates, set the inferred left y bounding
if len(min_candidates) > 0 and len(max_candidates) > 0:
min_, max_ = np.min(min_candidates), np.max(max_candidates)
height = max_ - min_
yscale_inferred = (min_ - height*0.05, max_ + height*0.05)
return yscale_inferred
def _title_and_labels(self, plot_info):
""" Put title and labels on the plot """
# xlabel
if plot_info.has_key('xlabel'):
label = plot_info['xlabel']
if plot_info['xlabel_addition'] != '':
label += '\n' + plot_info['xlabel_addition']
self.ax1.set_xlabel(label)
if self.o['xlabel'] != '': # Manual override
self.ax1.set_xlabel(r'{0}'.format(self.o['xlabel']))
# Left ylabel
if plot_info.has_key('left_ylabel'):
label = plot_info['left_ylabel']
if plot_info['y_left_label_addition'] != '':
label += '\n' + plot_info['y_left_label_addition']
self.ax1.set_ylabel(label, multialignment='center')
if self.o['left_ylabel'] != '': # Manual override
self.ax1.set_ylabel(self.o['left_ylabel'], multialignment='center')
# Right ylabel
if self.right_yaxis and plot_info.has_key('right_ylabel'):
label = plot_info['right_ylabel']
if plot_info['y_right_label_addition'] != '':
label += '\n' + plot_info['y_right_label_addition']
self.ax2.set_ylabel(label, multialignment='center', rotation=270)
if self.o['right_ylabel'] != '': # Manual override
self.ax2.set_ylabel(self.o['right_ylabel'],
multialignment='center', rotation=270)
# Title
if plot_info.has_key('title'):
self.ax1.set_title(plot_info['title'], y=1.03)
if self.o['title'] != '':
# experiment with 'r{0}'.form .. at some time
self.ax1.set_title('{0}'.format(self.o['title']), y=1.03)
# Legends
if self.measurement_count > 0:
ax1_legends = self.ax1.get_legend_handles_labels()
if self.right_yaxis:
ax2_legends = self.ax2.get_legend_handles_labels()
for color, text in zip(ax2_legends[0], ax2_legends[1]):
ax1_legends[0].append(color)
ax1_legends[1].append(text)
# loc for locations, 0 means 'best'. Why that isn't deafult I
# have no idea
legends = self.ax1.legend(ax1_legends[0], ax1_legends[1], loc=0)
# Make legend lines thicker
for legend_handle in legends.legendHandles:
legend_handle.set_linewidth(6)
def _save(self, plot_info):
""" Save the figure """
# The tight method only works if there is a title (it caps of parts of
# the axis numbers, therefore this hack, this may also become a problem
# for the other edges of the figure if there are no labels)
tight = ''
if plot_info.has_key('title'):
tight = 'tight'
# For some wierd reason we cannot write directly to sys.stdout when it
# is a pdf file, so therefore we use a the StringIO object workaround
if self.o['image_format'] == 'pdf':
import StringIO
out = StringIO.StringIO()
self.fig.savefig(out, bbox_inches=tight, pad_inches=0.03,
format=self.o['image_format'])
sys.stdout.write(out.getvalue())
else:
self.fig.savefig(sys.stdout, bbox_inches=tight, pad_inches=0.03,
format=self.o['image_format'])
