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'])