def main(argv):
# Create an OptionParser for reading optional parameters
parser = OptionParser(version='0.10')
parser.prog = 'Model Runner Plots Test'
print 'Running ' + parser.prog + ' ' + parser.version
options, args = parser.parse_args(argv)
log = False
# Use a hardcoded value for the input filename, probably adding in an option argument later
# for more flexibility
filename = 'output_test/BigHorn_Temperature.txt'
# Create the data frames and plots from the input file
(df, df_closest_fit) = ModelRunnerPlots.create_dataframes(filename, log)
# Get the plot and create a matplotlib figure.
df_plot = ModelRunnerPlots.create_line_plot('Temperature', 'Temperature in Farenheit', df=df, log=log, value_vars=list(df.columns - ['year']))
df_plot.savefig('graph_test.png', format='png')
# Create our GUI componenets. Note, the data frame and plot must be created beforehand for the GUI to work properly.
root = Tkinter.Tk()
root.title(parser.prog + ' ' + parser.version)
root.grid()
model_runner_gui = ModelRunnerGraphGUI.GraphFrame(root, df=df, plot=df_plot)
model_runner_gui.set_grid()
# Run the window main loop
root.mainloop()
def create_plots(output_files_list, log, gui_frame=None):
print('Number of plots in output: ' + str(len(output_files_list)))
for output_file_and_job in output_files_list:
output_file = output_file_and_job[0]
# NOTE: Skip files with "Avg" in the filename. The problem occurs when creating line graphs with intervals like:
# 1950-1959, 1951-1960, 1952-1961, etc. This is because the y-value is a range associated with a discrete range of data,
# but not a continuous range. Would a bar chart be more applicable?
if output_file.find('Avg') != -1:
print('Could not find the output file!')
continue
if log:
logging.info('Creating plots for file: ' + output_file)
else:
print('Creating plots for file: ' + output_file)
#(df, df_closest_fit) = ModelRunnerPlots.create_dataframes(output_file, log)
datatype = output_file[output_file.rindex('_')+1:output_file.rindex('.')]
df = ModelRunnerPlots.create_dataframes(output_file, datatype, log)
plot_title = create_plot_title(output_file, log)
window_title = None
if len(output_file_and_job) == 2:
window_title = create_plot_title(output_file, log) + ': ' + output_file_and_job[1]
else:
window_title = plot_title
if log:
logging.info('Plot Title: ' + plot_title)
all_plot = ModelRunnerPlots.create_line_plot(plot_title, get_plot_y_label(output_file, log), df, log, value_vars=list(df.columns - ['year']))
#closest_fit_plot = ModelRunnerPlots.create_line_plot(create_plot_title(output_file, log) + ' Closest Fit', get_plot_y_label(output_file, log), df_closest_fit, log, value_vars=list(df_closest_fit.columns - ['year']))
# Create two instances of graph windows for each graph
if gui_frame != None:
print('Creating plots!')
#plot_title = create_plot_title(output_file, log)
y_label = get_plot_y_label(output_file, log)
#all_plot_gui = ModelRunnerGraphGUI.GraphWindow(parent=None, df=df, plot=all_plot, plot_title=plot_title, y_label=y_label)
#closest_fit_plot_gui = ModelRunnerGraphGUI.GraphWindow(parent=None, df=df_closest_fit, plot=closest_fit_plot, plot_title=plot_title + ' Closest Fit', y_label=y_label)
gui_frame.add_plot({'df': df, 'plot': all_plot, 'plot_title': plot_title, 'y_label': y_label, 'window_title': window_title, 'output_file': output_file})
#print 'Adding plots'
# Or, just save the files if a GUI is not being used
else:
print('Just outputting image files!')
plot_base_fname = output_file[0:output_file.rindex('.')]
all_plot_fname = plot_base_fname + '_all_plot.png'
all_plot.savefig(all_plot_fname, format='png')
if log:
logging.info('Created a plot file of all output columns called ' + all_plot_fname)
closest_fit_plot_fname = plot_base_fname + '_closest_fit_plot.png'
closest_fit_plot.savefig(closest_fit_plot_fname, format='png')
if log:
logging.info('Created a plot file of the best fitting output called ' + closest_fit_plot_fname)
def __init__(self, parent, paned_window, **kwargs):
Frame.__init__(self, paned_window)
self.parent = parent
self.df_column_frame = ScrolledFrame(self, vertflex='expand')
self.graph_frame = ScrolledFrame(self, horizflex='expand', vertflex='expand')
self.plot_figure = kwargs['plot'] if 'plot' in kwargs else None
self.plot_title = kwargs['plot_title'] if 'plot_title' in kwargs else 'Line Plot'
self.y_label = kwargs['y_label'] if 'y_label' in kwargs else 'y'
self.df = kwargs['df'] if 'df' in kwargs else DataFrame() # If the dataframe wasn't passed in, then create an empty dataframe
plot_selected_avg = ModelRunnerPlots.get_avg_plot(self.plot_title, self.y_label, self.df, None)
self.plot_figure = plot_selected_avg
self.graph_canvas = FigureCanvasTkAgg(plot_selected_avg, master=self.graph_frame.interior())
self.col_list = list()
for col in self.df.columns:
if col != 'year' and 'Average' not in col:
col_var = IntVar()
col_var.set(0)
col_checkbox = Checkbutton(self.df_column_frame.interior(), text=col, variable=col_var, command=self.on_col_check)
self.col_list.append([col_var, col_checkbox, col])
avg_dataframe, dataframe = ModelRunnerPlots.find_avg_dataframe(self.df)
for col in avg_dataframe.columns:
if col != 'year':
col_var = IntVar()
col_var.set(0)
col_checkbox = Checkbutton(self.df_column_frame.interior(), text=col, variable=col_var, command=self.on_col_check)
self.col_list.append([col_var, col_checkbox, col])
self.log_filename_frame = Frame(self)
self.log_label = Label(self.log_filename_frame, text='Logfile: ' + kwargs['log_filename']) if 'log_filename' in kwargs else None
self.button_frame = Frame(self)
self.close_button = Button(self.button_frame, text='Close', command=self.on_close)
self.save_button = Button(self.button_frame, text='Save', command=self.on_save)
def on_col_check(self):
# Based upon what is checked, a new plot should be created
value_vars = list()
for col in self.col_list:
if col[0].get() == 1:
#print col[2] + ' is checked'
value_vars.append(col[2])
else:
pass
#print col[2] + ' is not checked'
plot_selected = ModelRunnerPlots.create_line_plot(self.plot_title, self.y_label, self.df, None, value_vars=value_vars)
#if len(value_vars) == 0:
#plot_selected = ModelRunnerPlots.get_avg_plot(self.plot_title, self.y_label, self.df, None)
plt.close(self.plot_figure)
try:
self.graph_canvas.get_tk_widget().grid_remove()
self.graph_canvas = FigureCanvasTkAgg(plot_selected, master=self.graph_frame.interior())
self.graph_canvas.get_tk_widget().grid(row=0, column=1, sticky=Tkinter.N + Tkinter.S + Tkinter.E + Tkinter.W)
except AttributeError:
pass
self.plot_figure = plot_selected
def create_plots(output_files_list, log, gui_frame=None):
# print 'Number of plots in output: ' + str(len(output_files_list))
for output_file_and_job in output_files_list:
output_file = output_file_and_job[0]
# NOTE: Skip files with "Avg" in the filename. The problem occurs when creating line graphs with intervals like:
# 1950-1959, 1951-1960, 1952-1961, etc. This is because the y-value is a range associated with a discrete range of data,
# but not a continuous range. Would a bar chart be more applicable?
if output_file.find("Avg") != -1:
continue
if log:
logging.info("Creating plots for file: " + output_file)
else:
print ("Creating plots for file: " + output_file)
# (df, df_closest_fit) = ModelRunnerPlots.create_dataframes(output_file, log)
datatype = output_file[output_file.rindex("_") + 1 : output_file.rindex(".")]
df = ModelRunnerPlots.create_dataframes(output_file, datatype, log)
plot_title = create_plot_title(output_file, log)
window_title = None
if len(output_file_and_job) == 2:
window_title = create_plot_title(output_file, log) + ": " + output_file_and_job[1]
else:
window_title = plot_title
if log:
logging.info("Plot Title: " + plot_title)
all_plot = ModelRunnerPlots.create_line_plot(
plot_title, get_plot_y_label(output_file, log), df, log, value_vars=list(df.columns - ["year"])
)
# closest_fit_plot = ModelRunnerPlots.create_line_plot(create_plot_title(output_file, log) + ' Closest Fit', get_plot_y_label(output_file, log), df_closest_fit, log, value_vars=list(df_closest_fit.columns - ['year']))
# Create two instances of graph windows for each graph
if gui_frame != None:
# plot_title = create_plot_title(output_file, log)
y_label = get_plot_y_label(output_file, log)
# all_plot_gui = ModelRunnerGraphGUI.GraphWindow(parent=None, df=df, plot=all_plot, plot_title=plot_title, y_label=y_label)
# closest_fit_plot_gui = ModelRunnerGraphGUI.GraphWindow(parent=None, df=df_closest_fit, plot=closest_fit_plot, plot_title=plot_title + ' Closest Fit', y_label=y_label)
gui_frame.add_plot(
{
"df": df,
"plot": all_plot,
"plot_title": plot_title,
"y_label": y_label,
"window_title": window_title,
"output_file": output_file,
}
)
# print 'Adding plots'
# Or, just save the files if a GUI is not being used
else:
plot_base_fname = output_file[0 : output_file.rindex(".")]
all_plot_fname = plot_base_fname + "_all_plot.png"
all_plot.savefig(all_plot_fname, format="png")
if log:
logging.info("Created a plot file of all output columns called " + all_plot_fname)
closest_fit_plot_fname = plot_base_fname + "_closest_fit_plot.png"
closest_fit_plot.savefig(closest_fit_plot_fname, format="png")
if log:
logging.info("Created a plot file of the best fitting output called " + closest_fit_plot_fname)
