# compute pairwise distance
D = compute_pairwise_distance(resampled_ground_truth_curve)
ind = listIndices(n, 1) # get the upper triangular index of the matrix
# compute expect number of interactions
MU = b * pow(D, a)
# simulate from independent poisson distribution
c = np.random.poisson(MU[ind[:, 0], ind[:, 1]])
# construct the pairwise interaction matrix
C = np.zeros([n, n])
C[ind[:, 0], ind[:, 1]] = c # only the upper triangular part
C = C + C.T # make the matrix symetric
# save the simulated matrix
np.savetxt("data/simulate_data_" + str(n) + ".csv", C, delimiter=',')
fig1, ax1 = pt.plot_curve(resampled_ground_truth_curve, tn)
pt.plot_pts(resampled_ground_truth_curve, t, ax=ax1, fig=fig1)
fig1.suptitle('Ground Truth Curve', fontsize=18)
fig1.savefig('images/ground_truth_curve.png')
fig2, ax2, m = pt.matshow(1.0 * (C > 0))
fig2.suptitle('Non-Zero Simulated Data', fontsize=18)
fig2.savefig('images/simulated_data_nonzeros.png')
fig3, ax3, m = pt.matshow(C)
fig3.suptitle('Simulated Data', fontsize=18)
fig3.savefig('images/simulated_data.png')
if display_the_result:
plt.show(block=True
) # If you want to display the results uncomment the thing above
def main(args=None):
"""
main function for the simba3d display command line utility
"""
if args is None:
args = sys.argv[:]
ii = 1
param_name = []
param_min = []
param_max = []
center_to_filename = None
report_directory = '.'
image_ext = 'png'
summary_name = 'results_summary'
print_each = False
latex_print = False
inputfiles = []
while ii < len(args):
print(args[ii])
if (args[ii] == '-h') | (args[ii] == '--help'):
printhelp()
sys.exit()
if (args[ii] == '-p') | (args[ii] == '--print-each'):
ii += 1
summary_name = str(args[ii])
print('\t' + args[ii])
print_each = True
latex_print = True
if (args[ii] == '-o') | (args[ii] == '--output-directory'):
ii += 1
report_directory = str(args[ii])
print('\t' + args[ii])
print_each = True
latex_print = True
if (args[ii] == '-f') | (args[ii] == '--format'):
ii += 1
image_ext = str(args[ii])
print('\t' + args[ii])
print_each = True
latex_print = True
if (args[ii] == '-c') | (args[ii] == '--center-to'):
ii += 1
center_to_filename = str(args[ii])
print('\t' + args[ii])
if (args[ii] == '-i') | (args[ii] == '--input-files'):
inputfiles = []
ii += 1
while ii < len(args):
inputfiles.append(args[ii])
print('\t' + args[ii])
ii += 1
ii += 1
image_directory = os.path.join(report_directory, 'figures')
# create the report directory if it does not exist
if print_each:
try:
if not os.path.exists(report_directory):
os.mkdir(report_directory)
print("Directory ", report_directory, " Created ")
if not os.path.exists(image_directory):
os.mkdir(image_directory)
print("Directory ", image_directory, " Created ")
except:
print("Potentially failed to create report directories")
#print inputfiles
curves = []
scurves = []
scurves_init = []
length = []
energy = []
if not inputfiles:
print('No inputs provided')
printhelp()
else:
# specify the file all the other figures will rotate to
if center_to_filename is None:
center_to_filename = inputfiles[0]
summary = mp.load_result(center_to_filename)
X0 = np.array(summary['X_evol'][-1]) # get the last curve
# get dimension
if 'd' in summary:
d = summary['d']
else:
d, n0 = np.shape(X0)
if 'n' in summary:
n = summary['n']
else:
d, n = np.shape(X0)
X0 = X0.reshape((d, n)) # correct dimensions
center_curve, mu = srvf.center_curve(X0)
scenter_curve, scale = srvf.scale_curve(center_curve)
latex = make_latex_report_header('figures')
for inputfile in inputfiles:
summary = mp.load_result(inputfile)
if result_passes_filter(summary, param_name, param_min, param_max):
#print summary.keys()
if 'uuid' in summary:
print(summary['uuid'])
if 'E_evol' in summary:
energy.append(summary['E_evol'])
#print summary.keys()
if 'X_evol' in summary:
X0 = np.array(summary['X_evol'][-1]) # get the last curve
# get dimension
if 'd' in summary:
d = summary['d']
else:
d, n = np.shape(X0)
if 'n' in summary:
n = summary['n']
else:
d, n = np.shape(X0)
X0 = X0.reshape((d, n)) # correct dimensions
curves.append(X0)
length.append(n)
curve, mu = srvf.center_curve(X0)
scurve, scale = srvf.scale_curve(curve)
scurves.append(scurve)
scurve, rot = srvf.find_best_rotation(scenter_curve, scurve)
scurves[-1] = scurve
weight_uniform_spacing = None
if "weight_uniform_spacing" in summary:
weight_uniform_spacing = summary['weight_uniform_spacing']
weight_smoothing = None
if "weight_smoothing" in summary:
weight_smoothing = summary['weight_smoothing']
weight_population_prior = None
if "weight_population_prior" in summary:
weight_population_prior = summary['weight_population_prior']
computation_time = None
if "computation_time" in summary:
computation_time = summary['computation_time']
nonspecified_zeros_as_missing = None
if "nonspecified_zeros_as_missing" in summary:
nonspecified_zeros_as_missing = summary[
'nonspecified_zeros_as_missing']
if 'initialized_curve' in summary:
X0 = np.array(
summary['initialized_curve']) # get the last curve
# get dimension
if 'd' in summary:
d = summary['d']
else:
d, n = np.shape(X0)
if 'n' in summary:
n = summary['n']
else:
d, n = np.shape(X0)
X0 = X0.reshape((d, n)) # correct dimensions
curves.append(X0)
length.append(n)
curve, mu = srvf.center_curve(X0)
scurve, scale = srvf.scale_curve(curve)
scurves_init.append(scurve)
scurve, rot = srvf.find_best_rotation(scenter_curve, scurve)
scurves_init[-1] = scurve
plt.close('all')
fig1 = plt.figure()
plt.figure(fig1.number)
plt.plot(energy[-1])
plt.title("Energy Evolution")
fig3 = plt.figure()
plt.subplots_adjust(left=0.0,
right=1.0,
bottom=0.0,
top=1.0,
wspace=0.0,
hspace=0.0)
#fig2.tight_layout()
ax3 = fig3.add_subplot(111, projection='3d')
ax3.set_axis_off()
(m, n) = np.shape(scurves_init[-1])
t = np.linspace(0, 1, n)
pt.plot_curve(scurves_init[-1], t, ax=ax3, fig=fig3)
pt.plot_pts(scurves_init[-1], t, ax=ax3, fig=fig3)
plt.title("Initialized Curve")
plt.figure(fig3.number)
fig2 = plt.figure()
plt.subplots_adjust(left=0.0,
right=1.0,
bottom=0.0,
top=1.0,
wspace=0.0,
hspace=0.0)
#fig2.tight_layout()
ax2 = fig2.add_subplot(111, projection='3d')
ax2.set_axis_off()
(m, n) = np.shape(scurves[-1])
t = np.linspace(0, 1, n)
pt.plot_curve(scurves[-1], t, ax=ax2, fig=fig2)
pt.plot_pts(scurves[-1], t, ax=ax2, fig=fig2)
plt.figure(fig2.number)
plt.title("Estimated Curve")
if not print_each:
plt.show()
if print_each:
if image_ext not in ["png", 'pdf', 'svg', 'ps', 'eps']:
print('invalid image format:' + image_ext)
else:
base = os.path.basename(inputfile)
base = base.split('.')[0]
image_name_tmp = os.path.join(image_directory, base)
print(image_name_tmp)
try:
fig1.savefig(image_name_tmp + '_energies.' + image_ext)
fig3.savefig(image_name_tmp + '_initial_curves.' +
image_ext)
fig2.savefig(image_name_tmp + '_estimated_curves.' +
image_ext)
if latex_print:
params = dict()
params['inputfile'] = inputfile
params['table width'] = 3
params['images'] = [
base + '_energies.' + image_ext,
base + '_initial_curves.' + image_ext,
base + '_estimated_curves.' + image_ext
]
params['statistics'] = {
'Final Energy':
energy[-1][-1],
'Total Iterations':
len(energy[-1]),
'Total Computation Time':
computation_time,
'Uniform Spacing Penalty':
weight_uniform_spacing,
'Smoothing Penalty':
weight_smoothing,
'Population Penalty':
weight_population_prior,
'Nonspecified Zeros As Missing':
nonspecified_zeros_as_missing
}
latex_table = make_latex_table(params)
latex += latex_table
except:
print("unable to create image for:" + inputfile)
if latex_print:
latex += make_latex_report_footer()
print(latex)
with open(os.path.join(report_directory, summary_name + '.tex'),
'w') as result:
result.write(latex)
#%% load the output report file curve
report_file ='results/simulated_data_b7b1fe84-8b80-4bb4-9af8-8f0f9e7aa3b7_400.npz'
summary=mp.load_result(report_file)
curves=summary['X_evol']
#remove translation and scale of the ground truth curve
curve,mu=srvf.center_curve(curves[-1]) # remove translation
curve,scale=srvf.scale_curve(curve) # remove scale
#align estimated curve to the ground truth curve
curve,rot=srvf.find_best_rotation(center_curve,curve)# align to the first curve
# plot the estimated curve
d,n=np.shape(curve);
t=np.linspace(0,1,n)
fig1,ax1=pt.plot_curve(curve,t)
pt.plot_pts(curve,t,ax=ax1,fig=fig1)
fig1.suptitle('Estimated Curve',fontsize=18)
fig1.savefig('images/estimated_curve.png');
# add the ground truth curve on top
d,n=np.shape(center_curve);
t=np.linspace(0,1,n)
fig1,ax1=pt.plot_curve(center_curve,ax=ax1,fig=fig1)
pt.plot_pts(center_curve,ax=ax1,fig=fig1)
fig1.suptitle('Estimated Curve with Ground Truth',fontsize=18)
fig1.savefig('images/estimated_and_groundtruth_curve.png');
# print the weight settings
print("uniform spacing penalty:"+str(summary['weight_uniform_spacing']))
print("smoothing penalty:"+str(summary['weight_smoothing']))
print("population prior penalty:"+str(summary['weight_population_prior']))
def main(args=None):
"""
main function for the simba3d display command line utility
"""
if args is None:
args = sys.argv[:]
ii = 1
report_directory = '.'
image_ext = 'png'
summary_name = 'tasks_summary'
print_each = False
latex_print = False
colormap_name = 'pink'
p = 100
while ii < len(args):
print(args[ii])
if (args[ii] == '-h') | (args[ii] == '--help'):
printhelp()
sys.exit()
if (args[ii] == '-p') | (args[ii] == '--print-each'):
ii += 1
summary_name = str(args[ii])
print('\t' + args[ii])
print_each = True
latex_print = True
if (args[ii] == '-o') | (args[ii] == '--output-directory'):
ii += 1
report_directory = str(args[ii])
print('\t' + args[ii])
print_each = True
latex_print = True
if (args[ii] == '-f') | (args[ii] == '--format'):
ii += 1
image_ext = str(args[ii])
print('\t' + args[ii])
print_each = True
latex_print = True
if (args[ii] == '-c') | (args[ii] == '--colormap'):
ii += 1
colormap_name = str(args[ii])
print('\t' + args[ii])
if (args[ii] == '-i') | (args[ii] == '--input-files'):
inputfiles = []
ii += 1
while ii < len(args):
inputfiles.append(args[ii])
print('\t' + args[ii])
ii += 1
ii += 1
image_directory = os.path.join(report_directory, 'figures')
# create the report directory if it does not exist
if print_each:
try:
if not os.path.exists(report_directory):
os.mkdir(report_directory)
print("Directory ", report_directory, " Created ")
if not os.path.exists(image_directory):
os.mkdir(image_directory)
print("Directory ", image_directory, " Created ")
except:
print("Potentially failed to create report directories")
latex = lr.make_latex_report_header('figures')
tasks = []
scenter_curve = None
for inputfile in inputfiles:
curves = []
scurves = []
scurves_init = []
length = []
energy = []
print('Reading:' + inputfile)
basename = os.path.basename(inputfile)
filepath = os.path.dirname(inputfile)
latex += r'\pagebreak' + u'\n'
latex += lr.make_latex_section('Task Summary', inputfile)
with open(inputfile, 'r') as tasklist:
tasks = json.load(tasklist)
number_of_tasks = str(len(tasks))
number_of_tasks_remaining = str(len(check_tasks_index(
tasks))) # find which tasks still need to run
for task in tasks:
index_remaining = check_tasks_index(task)
number_of_subtasks = str(len(task))
number_of_subtasks_remaining = str(len(check_tasks_index(
task))) # find which tasks still need to run
for subtask in task:
UUID = None
if 'uuid' in subtask:
UUID = subtask['uuid']
latex += lr.make_latex_subsection('Subtask Summary', UUID)
if UUID is None:
UUID = str(uuid.uuid4())
matrix_files = []
is_sparse = []
initialized_curve_files = []
data = load_data(subtask)
#
# get the file input names
latex += r'\subsubsection{Inputs}' + u'\n'
if 'file_names' in subtask:
inputdir = '.'
if 'inputdir' in subtask['file_names']:
inputdir = subtask['file_names']['inputdir']
input_parameters = ''
for key in subtask.keys():
skip = 'data' in key
skip += 'file_names' in key
if skip == 0:
if type(subtask[key]) == type(dict()):
for subkey in subtask[key].keys():
if type(subtask[key][subkey]) == type(
dict()):
for subsubkey in subtask[key][
subkey].keys():
name = key + ' ' + subkey + ' ' + subsubkey
input_parameters += name + ':' + str(
subtask[key][subkey]
[subsubkey]) + u'\n'
else:
name = key + ' ' + subkey
input_parameters += name + ':' + str(
subtask[key][subkey]) + u'\n'
else:
name = key
input_parameters += name + ':' + str(
subtask[key]) + u'\n'
latex += lr.make_latex_table(
{'inputfile': input_parameters})
for key in subtask['file_names'].keys():
if 'output' not in key:
params = dict()
params['inputfile'] = key + ':' + subtask[
'file_names'][key]
params['table width'] = 2
if key in data:
filename = UUID + key
if 'initialized_curve' in key:
curve, mu = srvf.center_curve(
data[key])
scurve, scale = srvf.scale_curve(curve)
if scenter_curve is None:
scenter_curve = scurve
else:
scurve, rot = srvf.find_best_rotation(
scenter_curve, scurve)
fig3 = plt.figure()
plt.subplots_adjust(left=0.0,
right=1.0,
bottom=0.0,
top=1.0,
wspace=0.0,
hspace=0.0)
#fig2.tight_layout()
ax3 = fig3.add_subplot(111,
projection='3d')
ax3.set_axis_off()
(m, n) = np.shape(scurve)
t = np.linspace(0, 1, n)
pt.plot_curve(scurve,
t,
ax=ax3,
fig=fig3)
pt.plot_pts(scurve,
t,
ax=ax3,
fig=fig3)
plt.title("Initialized Curve")
if not print_each:
plt.show()
else:
imagename = os.path.join(
image_directory,
filename + '.' + image_ext)
fig3.savefig(imagename)
params['images'] = [
filename + '.' + image_ext
]
params['statistics'] = {
'm': str(m),
'n': str(n),
}
if '_matrix' in key:
# you have a matrix
if 'sparse_' in key:
# it is sparse
matrix = data[key].todense()
else:
# it is not sparse
matrix = data[key]
q = np.percentile(matrix, p)
plt.close('all')
fig1 = plt.figure()
plt.figure(fig1.number)
plt.imshow(matrix, colormap_name)
plt.clim([0, q])
plt.colorbar()
if not print_each:
plt.show()
else:
imagename = os.path.join(
image_directory,
filename + '.' + image_ext)
fig1.savefig(imagename)
(m, n) = np.shape(matrix)
params['images'] = [
filename + '.' + image_ext
]
params['statistics'] = {
'Row Length':
str(m),
'Column Length':
str(n),
'Total Entries':
str(n * m),
'Non-zero Entries':
str(np.sum(matrix > 0)),
'Sum':
str(np.sum(matrix)),
'Max':
str(np.max(matrix)),
'Non-trivial Rows':
str(np.sum(
sum(matrix > 0) > 0))
}
latex += lr.make_latex_table(params)
# summarize input files\
latex += r'\subsubsection{Results}' + u'\n'
summary = mp.load_result(get_outputfilepath(subtask))
if not summary:
latex += u'No output result file found.\n'
else:
if 'uuid' in summary:
print(summary['uuid'])
if 'E_evol' in summary:
energy.append(summary['E_evol'])
#print summary.keys()
if 'X_evol' in summary:
X0 = np.array(
summary['X_evol'][-1]) # get the last curve
# get dimension
if 'd' in summary:
d = summary['d']
else:
d, n = np.shape(X0)
if 'n' in summary:
n = summary['n']
else:
d, n = np.shape(X0)
X0 = X0.reshape((d, n)) # correct dimensions
curves.append(X0)
length.append(n)
curve, mu = srvf.center_curve(X0)
scurve, scale = srvf.scale_curve(curve)
scurves.append(scurve)
scurve, rot = srvf.find_best_rotation(
scenter_curve, scurve)
scurves[-1] = scurve
weight_uniform_spacing = None
if "weight_uniform_spacing" in summary:
weight_uniform_spacing = summary[
'weight_uniform_spacing']
weight_smoothing = None
if "weight_smoothing" in summary:
weight_smoothing = summary['weight_smoothing']
weight_population_prior = None
if "weight_population_prior" in summary:
weight_population_prior = summary[
'weight_population_prior']
computation_time = None
if "computation_time" in summary:
computation_time = summary['computation_time']
if 'initialized_curve' in summary:
X0 = np.array(summary['initialized_curve']
) # get the last curve
# get dimension
if 'd' in summary:
d = summary['d']
else:
d, n = np.shape(X0)
if 'n' in summary:
n = summary['n']
else:
d, n = np.shape(X0)
X0 = X0.reshape((d, n)) # correct dimensions
curves.append(X0)
length.append(n)
curve, mu = srvf.center_curve(X0)
scurve, scale = srvf.scale_curve(curve)
scurves_init.append(scurve)
scurve, rot = srvf.find_best_rotation(
scenter_curve, scurve)
scurves_init[-1] = scurve
plt.close('all')
fig1 = plt.figure()
plt.figure(fig1.number)
plt.plot(energy[-1])
plt.title("Energy Evolution")
fig3 = plt.figure()
plt.subplots_adjust(left=0.0,
right=1.0,
bottom=0.0,
top=1.0,
wspace=0.0,
hspace=0.0)
#fig2.tight_layout()
ax3 = fig3.add_subplot(111, projection='3d')
ax3.set_axis_off()
(m, n) = np.shape(scurves_init[-1])
t = np.linspace(0, 1, n)
pt.plot_curve(scurves_init[-1],
t,
ax=ax3,
fig=fig3)
pt.plot_pts(scurves_init[-1], t, ax=ax3, fig=fig3)
plt.title("Initialized Curve")
plt.figure(fig3.number)
fig2 = plt.figure()
plt.subplots_adjust(left=0.0,
right=1.0,
bottom=0.0,
top=1.0,
wspace=0.0,
hspace=0.0)
#fig2.tight_layout()
ax2 = fig2.add_subplot(111, projection='3d')
ax2.set_axis_off()
(m, n) = np.shape(scurves[-1])
t = np.linspace(0, 1, n)
pt.plot_curve(scurves[-1], t, ax=ax2, fig=fig2)
pt.plot_pts(scurves[-1], t, ax=ax2, fig=fig2)
plt.figure(fig2.number)
plt.title("Estimated Curve")
if not print_each:
plt.show()
else:
fig1.savefig(
os.path.join(
image_directory,
UUID + '_energies.' + image_ext))
fig3.savefig(
os.path.join(
image_directory,
UUID + '_initial_curves.' + image_ext))
fig2.savefig(
os.path.join(
image_directory, UUID +
'_estimated_curves.' + image_ext))
if latex_print:
params = dict()
params['inputfile'] = get_outputfilepath(
subtask)
params['table width'] = 3
params['images'] = [
UUID + '_energies.' + image_ext,
UUID + '_initial_curves.' + image_ext,
UUID + '_estimated_curves.' + image_ext
]
params['statistics'] = {
'Final Energy': energy[-1][-1],
'Total Iterations': len(energy[-1]),
'Total Computation Time': computation_time,
}
latex_table = lr.make_latex_table(params)
latex += latex_table
if latex_print:
latex += r'\end{document}' + u'\n'
print(latex)
with open(os.path.join(report_directory, summary_name + '.tex'),
'w') as result:
result.write(latex)