def __init__(self, *args, **kwargs):
super(TaskPlugin, self).__init__(*args, **kwargs)
self.copasi_model = CopasiModel(
os.path.join(self.task.directory, self.task.original_model))
def __init__(self, *args, **kwargs):
super(TaskPlugin, self).__init__(*args, **kwargs)
self.copasi_model = CopasiModel(os.path.join(self.task.directory, self.task.original_model))
class TaskPlugin(BaseTask):
subtasks = 2
def __init__(self, *args, **kwargs):
super(TaskPlugin, self).__init__(*args, **kwargs)
self.copasi_model = CopasiModel(
os.path.join(self.task.directory, self.task.original_model))
def validate(self):
#TODO:Abstract this to a new COPASI class in this plugin package
return self.copasi_model.is_valid('SO')
def initialize_subtasks(self):
#Create new subtask objects, and save them
#Create the main subtask
self.create_new_subtask('main')
#And a subtask to process any results
self.create_new_subtask('process', local=True)
def prepare_subtask(self, index):
"""Prepare the indexed subtask"""
if index == 1:
return self.process_first_subtask()
elif index == 2:
return self.process_second_subtask()
else:
raise Exception('No subtasks remaining')
def process_first_subtask(self):
#Get the first subtask
subtask = self.get_subtask(1)
#Construct the model files for this task
model_path, model_filename = os.path.split(self.task.original_model)
#If no load balancing step required:
model_files = self.copasi_model.prepare_so_task()
condor_pool = self.task.condor_pool
condor_job_file = self.copasi_model.prepare_so_condor_job(
condor_pool.pool_type,
condor_pool.address,
subtask_index=1,
rank='')
log.debug('Prepared copasi files %s' % model_files)
log.debug('Prepared condor job %s' % condor_job_file)
model_count = len(model_files)
self.task.set_custom_field('model_count', model_count)
subtask.spec_file = condor_job_file
subtask.status = 'ready'
subtask.save()
return subtask
def process_second_subtask(self):
subtask = self.get_subtask(2)
assert isinstance(subtask, Subtask)
subtask.start_time = now()
#Go through and collate the results
#This is a computationally simple task, so we will run locally, not remotely
directory = self.task.directory
original_subtask = self.get_subtask(1)
output_filename = 'output_1.%d.txt'
results = self.copasi_model.get_so_results(save=True)
log.debug('Results:')
log.debug(results)
subtask.task.set_custom_field('results_file', 'results.txt')
log.debug('Setting subtask as finished')
subtask.status = 'finished'
subtask.finish_time = now()
subtask.set_run_time(time_delta=subtask.finish_time -
subtask.start_time)
subtask.save()
return subtask
def get_results_view_template_name(self, request):
"""Return a string with the HTML code to be used in the task results view page
"""
#Get the name of the page we're displaying. If not specified, assume main
page_name = request.GET.get('name', 'main')
if page_name == 'main':
return self.get_template_name('results_view')
elif page_name == 'plot':
return self.get_template_name('progress_plot')
else:
return ''
def get_results_view_data(self, request):
#Get the name of the page we're displaying. If not specified, assume main
page_name = request.GET.get('name', 'main')
if page_name == 'main':
results = self.copasi_model.get_so_results(save=False)
output = {'results': results}
output[
'sensitivity_object'] = self.copasi_model.get_sensitivities_object(
)
return output
elif page_name == 'plot':
output = {}
results = self.copasi_model.get_so_results()
variable_choices = []
for result in results:
variable_choices.append(result['name'] + '_max')
variable_choices.append(result['name'] + '_min')
if request.GET.get('custom'):
form = SOPlotUpdateForm(request.GET,
variable_choices=variable_choices)
else:
form = SOPlotUpdateForm(
variable_choices=variable_choices,
initial={'variables': range(len(variable_choices))})
output['form'] = form
if form.is_valid():
variables = map(int, form.cleaned_data['variables'])
log = form.cleaned_data['logarithmic']
legend = form.cleaned_data['legend']
grid = form.cleaned_data['grid']
fontsize = form.cleaned_data['fontsize']
else:
variables = range(len(variable_choices))
log = False
legend = True
grid = True
fontsize = '12'
#construct the string to load the image file
img_string = '?variables=' + str(variables).strip('[').rstrip(
']').replace(' ', '')
img_string += '&name=plot'
if log:
img_string += '&log=true'
if legend:
img_string += '&legend=true'
if grid:
img_string += '&grid=true'
if fontsize:
img_string += '&fontsize=' + str(fontsize)
output['img_string'] = img_string
return output
else:
return {}
def get_results_download_data(self, request):
page_name = request.GET.get('name', 'main')
if page_name == 'main':
#Return the file results.txt
filename = os.path.join(self.task.directory, 'results.txt')
if not os.path.isfile(filename):
request.session['errors'] = [
('Cannot Return Output',
'There was an internal error processing the results file')
]
return HttpResponseRedirect(
reverse_lazy('task_details',
kwargs={'task_id': self.task.id}))
result_file = open(filename, 'r')
response = HttpResponse(result_file,
content_type='text/tab-separated-values')
response[
'Content-Disposition'] = 'attachment; filename=%s_results.txt' % (
self.task.name.replace(' ', '_'))
response['Content-Length'] = os.path.getsize(filename)
return response
elif page_name == 'plot':
return self.get_progress_plot(request)
def get_progress_plot(self, request):
"""Return the plot image for the progress of a single sensitivity optimization parameter"""
results = self.copasi_model.get_so_results()
#Get parameter names, min and max
variable_choices = []
for result in results:
variable_choices.append(result['name'] + '_max')
variable_choices.append(result['name'] + '_min')
#Look at the GET data to see what chart options have been set:
get_variables = request.GET.get('variables')
log = request.GET.get('log', 'false')
legend = request.GET.get('legend', 'false')
grid = request.GET.get('grid', 'false')
fontsize = int(request.GET.get('fontsize', '12'))
#Check to see if we should return as an attachment in .png or .svg or .pdf
download_png = 'download_png' in request.POST
download_svg = 'download_svg' in request.POST
download_pdf = 'download_pdf' in request.POST
try:
variables = map(int, get_variables.split(','))
assert max(variables) < len(variable_choices)
except:
raise
variables = range(len(results))
matplotlib.rc('font', size=fontsize)
fig = plt.figure()
# plt.title(job.name + ' (' + str(job.runs) + ' repeats)', fontsize=12, fontweight='bold')
plt.xlabel('Iterations')
plt.ylabel('Optimization value')
color_list = [
'red', 'blue', 'green', 'cyan', 'magenta', 'yellow', 'black'
]
j = 0 #used to keep cycle through colors in order
jobs = CondorJob.objects.filter(subtask__task=self.task).order_by('id')
for i in variables:
#Go through each result and plot the progress
label = variable_choices[i]
#Check if we're plotting a min or a max. Min will be all even numbers, max all odd
file_index = int(math.floor(i / 2))
filename = os.path.join(self.task.directory,
jobs.get(process_id=i).job_output)
all_evals = []
all_values = []
linenumber = 0
#Go through line by line; lines repeat every 4th line
for line in open(filename, 'r'):
if linenumber % 4 == 0:
pass
elif linenumber % 4 == 1:
evals = int(
line.split()[2]) # Extract number from 'Evals = n'
all_evals.append(evals)
elif linenumber % 4 == 2:
pass
#time = float(line.split()[2])
elif linenumber % 4 == 3:
value = float(line)
all_values.append(value)
linenumber += 1
#Plot the progress
plt.plot(all_evals,
all_values,
lw=1,
label=label,
color=color_list[j % len(color_list)])
j += 1
#Set a logarithmic scale if requested
if log != 'false':
plt.yscale('log')
if legend != 'false':
plt.legend(loc=0, prop={'size': fontsize})
if grid != 'false':
plt.grid(True)
plt.show()
#Remove spaces from the task name for saving
name = self.task.name.replace(' ', '_')
if download_png:
response = HttpResponse(mimetype='image/png',
content_type='image/png')
fig.savefig(response, format='png', transparent=False, dpi=120)
response[
'Content-Disposition'] = 'attachment; filename=%s.png' % name
elif download_svg:
response = HttpResponse(mimetype='image/svg',
content_type='image/svg')
fig.savefig(response, format='svg', transparent=False, dpi=120)
response[
'Content-Disposition'] = 'attachment; filename=%s.svg' % name
elif download_pdf:
response = HttpResponse(mimetype='application/pdf',
content_type='application/pdf')
fig.savefig(response, format='pdf', transparent=False, dpi=120)
response[
'Content-Disposition'] = 'attachment; filename=%s.pdf' % name
else:
response = HttpResponse(mimetype='image/png',
content_type='image/png')
fig.savefig(response, format='png', transparent=False, dpi=120)
return response
class TaskPlugin(BaseTask):
subtasks = 2
def __init__(self, *args, **kwargs):
super(TaskPlugin, self).__init__(*args, **kwargs)
self.copasi_model = CopasiModel(os.path.join(self.task.directory, self.task.original_model))
def validate(self):
#TODO:Abstract this to a new COPASI class in this plugin package
return self.copasi_model.is_valid('SO')
def initialize_subtasks(self):
#Create new subtask objects, and save them
#Create the main subtask
self.create_new_subtask('main')
#And a subtask to process any results
self.create_new_subtask('process', local=True)
def prepare_subtask(self, index):
"""Prepare the indexed subtask"""
if index == 1:
return self.process_first_subtask()
elif index == 2:
return self.process_second_subtask()
else:
raise Exception('No subtasks remaining')
def process_first_subtask(self):
#Get the first subtask
subtask = self.get_subtask(1)
#Construct the model files for this task
model_path, model_filename = os.path.split(self.task.original_model)
#If no load balancing step required:
model_files = self.copasi_model.prepare_so_task()
condor_pool = self.task.condor_pool
condor_job_file = self.copasi_model.prepare_so_condor_job(condor_pool.pool_type, condor_pool.address, subtask_index=1, rank='')
log.debug('Prepared copasi files %s'%model_files)
log.debug('Prepared condor job %s' %condor_job_file)
model_count = len(model_files)
self.task.set_custom_field('model_count', model_count)
subtask.spec_file = condor_job_file
subtask.status = 'ready'
subtask.save()
return subtask
def process_second_subtask(self):
subtask=self.get_subtask(2)
assert isinstance(subtask, Subtask)
subtask.start_time = now()
#Go through and collate the results
#This is a computationally simple task, so we will run locally, not remotely
directory = self.task.directory
original_subtask = self.get_subtask(1)
output_filename = 'output_1.%d.txt'
results = self.copasi_model.get_so_results(save=True)
log.debug('Results:')
log.debug(results)
subtask.task.set_custom_field('results_file', 'results.txt')
log.debug('Setting subtask as finished')
subtask.status = 'finished'
subtask.finish_time = now()
subtask.set_run_time(time_delta=subtask.finish_time - subtask.start_time)
subtask.save()
return subtask
def get_results_view_template_name(self, request):
"""Return a string with the HTML code to be used in the task results view page
"""
#Get the name of the page we're displaying. If not specified, assume main
page_name = request.GET.get('name', 'main')
if page_name == 'main':
return self.get_template_name('results_view')
elif page_name == 'plot':
return self.get_template_name('progress_plot')
else: return ''
def get_results_view_data(self, request):
#Get the name of the page we're displaying. If not specified, assume main
page_name = request.GET.get('name', 'main')
if page_name == 'main':
results = self.copasi_model.get_so_results(save=False)
output = {'results': results}
output['sensitivity_object'] = self.copasi_model.get_sensitivities_object()
return output
elif page_name == 'plot':
output = {}
results = self.copasi_model.get_so_results()
variable_choices=[]
for result in results:
variable_choices.append(result['name'] + '_max')
variable_choices.append(result['name'] + '_min')
if request.GET.get('custom'):
form=SOPlotUpdateForm(request.GET, variable_choices=variable_choices)
else:
form=SOPlotUpdateForm(variable_choices=variable_choices, initial={'variables' : range(len(variable_choices))})
output['form'] = form
if form.is_valid():
variables = map(int,form.cleaned_data['variables'])
log = form.cleaned_data['logarithmic']
legend = form.cleaned_data['legend']
grid = form.cleaned_data['grid']
fontsize = form.cleaned_data['fontsize']
else:
variables=range(len(variable_choices))
log=False
legend=True
grid=True
fontsize = '12'
#construct the string to load the image file
img_string = '?variables=' + str(variables).strip('[').rstrip(']').replace(' ', '')
img_string += '&name=plot'
if log:
img_string += '&log=true'
if legend:
img_string += '&legend=true'
if grid:
img_string += '&grid=true'
if fontsize:
img_string += '&fontsize=' + str(fontsize)
output['img_string']=img_string
return output
else:
return {}
def get_results_download_data(self, request):
page_name = request.GET.get('name', 'main')
if page_name == 'main':
#Return the file results.txt
filename = os.path.join(self.task.directory, 'results.txt')
if not os.path.isfile(filename):
request.session['errors'] = [('Cannot Return Output', 'There was an internal error processing the results file')]
return HttpResponseRedirect(reverse_lazy('task_details', kwargs={'task_id':self.task.id}))
result_file = open(filename, 'r')
response = HttpResponse(result_file, content_type='text/tab-separated-values')
response['Content-Disposition'] = 'attachment; filename=%s_results.txt' % (self.task.name.replace(' ', '_'))
response['Content-Length'] = os.path.getsize(filename)
return response
elif page_name == 'plot':
return self.get_progress_plot(request)
def get_progress_plot(self, request):
"""Return the plot image for the progress of a single sensitivity optimization parameter"""
results = self.copasi_model.get_so_results()
#Get parameter names, min and max
variable_choices = []
for result in results:
variable_choices.append(result['name'] + '_max')
variable_choices.append(result['name'] + '_min')
#Look at the GET data to see what chart options have been set:
get_variables = request.GET.get('variables')
log = request.GET.get('log', 'false')
legend = request.GET.get('legend', 'false')
grid = request.GET.get('grid', 'false')
fontsize = int(request.GET.get('fontsize', '12'))
#Check to see if we should return as an attachment in .png or .svg or .pdf
download_png = 'download_png' in request.POST
download_svg = 'download_svg' in request.POST
download_pdf = 'download_pdf' in request.POST
try:
variables = map(int, get_variables.split(','))
assert max(variables) < len(variable_choices)
except:
raise
variables = range(len(results))
matplotlib.rc('font', size=fontsize)
fig = plt.figure()
# plt.title(job.name + ' (' + str(job.runs) + ' repeats)', fontsize=12, fontweight='bold')
plt.xlabel('Iterations')
plt.ylabel('Optimization value')
color_list = ['red', 'blue', 'green', 'cyan', 'magenta', 'yellow', 'black']
j=0 #used to keep cycle through colors in order
jobs = CondorJob.objects.filter(subtask__task=self.task).order_by('id')
for i in variables:
#Go through each result and plot the progress
label = variable_choices[i]
#Check if we're plotting a min or a max. Min will be all even numbers, max all odd
file_index = int(math.floor(i/2))
filename = os.path.join(self.task.directory, jobs.get(process_id=i).job_output)
all_evals=[]
all_values=[]
linenumber=0
#Go through line by line; lines repeat every 4th line
for line in open(filename, 'r'):
if linenumber%4 == 0:
pass
elif linenumber%4 == 1:
evals = int(line.split()[2]) # Extract number from 'Evals = n'
all_evals.append(evals)
elif linenumber%4 == 2:
pass
#time = float(line.split()[2])
elif linenumber%4 == 3:
value = float(line)
all_values.append(value)
linenumber += 1
#Plot the progress
plt.plot(all_evals, all_values, lw=1, label=label, color=color_list[j%len(color_list)])
j+=1
#Set a logarithmic scale if requested
if log != 'false':
plt.yscale('log')
if legend != 'false':
plt.legend(loc=0, prop={'size':fontsize} )
if grid != 'false':
plt.grid(True)
plt.show()
#Remove spaces from the task name for saving
name = self.task.name.replace(' ', '_')
if download_png:
response = HttpResponse(mimetype='image/png', content_type='image/png')
fig.savefig(response, format='png', transparent=False, dpi=120)
response['Content-Disposition'] = 'attachment; filename=%s.png' % name
elif download_svg:
response = HttpResponse(mimetype='image/svg', content_type='image/svg')
fig.savefig(response, format='svg', transparent=False, dpi=120)
response['Content-Disposition'] = 'attachment; filename=%s.svg' % name
elif download_pdf:
response = HttpResponse(mimetype='application/pdf', content_type='application/pdf')
fig.savefig(response, format='pdf', transparent=False, dpi=120)
response['Content-Disposition'] = 'attachment; filename=%s.pdf' % name
else:
response = HttpResponse(mimetype='image/png', content_type='image/png')
fig.savefig(response, format='png', transparent=False, dpi=120)
return response
