def plot_matrix(self, parameters):
matrix_image_file_path = os.path.join(self.workspaceHandler["matrix"], parameters["data"]["matrix"]["image"]["filename"])
max_dim = parameters.get_value("data.matrix.image.dimension", default_value = 1000)
plotTools.matrixToImage(self.matrixHandler.distance_matrix, matrix_image_file_path, max_dim=max_dim, observer=self.observer)
self.generatedFiles.append({"description":"Matrix image",
"path":os.path.abspath(matrix_image_file_path),
"type":"image"})
def create_matrix(self, parameters):
self.matrixHandler = MatrixHandler(parameters["data"]["matrix"])
self.notify("Matrix calculation", [])
self.timer.start("Matrix Generation")
self.matrixHandler.create_matrix(self.trajectoryHandler)
statistics_file_path = self.matrixHandler.save_statistics(self.workspaceHandler["matrix"])
self.generatedFiles.append({"description":"Matrix statistics",
"path":os.path.abspath(statistics_file_path),
"type":"text"})
self.timer.stop("Matrix Generation")
if "filename" in parameters["data"]["matrix"]:
self.timer.start("Matrix Save")
self.matrixHandler.save_matrix(os.path.join(self.workspaceHandler["matrix"], parameters["data"]["matrix"]["filename"]))
self.timer.stop("Matrix Save")
#########################
# Matrix plot
#########################
if "image" in parameters["data"]["matrix"].keys():
self.timer.start("Matrix Imaging")
matrix_image_file_path = os.path.join(self.workspaceHandler["matrix"], parameters["data"]["matrix"]["image"]["filename"])
max_dim = parameters["data"]["matrix"]["image"]["dimension"] if "dimension" in parameters["data"]["matrix"]["image"] else 1000
plotTools.matrixToImage(self.matrixHandler.distance_matrix, matrix_image_file_path, max_dim=max_dim, observer=self.observer)
self.generatedFiles.append({"description":"Matrix image",
"path":os.path.abspath(matrix_image_file_path),
"type":"image"})
self.timer.stop("Matrix Imaging")
def plot_matrix(cls, matrix_handler, workspace_handler, parameters, generated_files):
matrix_image_file_path = os.path.join(workspace_handler["matrix"],
parameters["image"]["filename"])
max_dim = parameters.get_value("image.dimension", default_value = 1000)
plotTools.matrixToImage(matrix_handler.distance_matrix,
matrix_image_file_path,
max_dim=max_dim)
generated_files.append({
"description":"Matrix image",
"path":os.path.abspath(matrix_image_file_path),
"type":"image"
})
def process_matrix(folders, image_path, sim_type):
data = []
for i in range(0,len(folders)-1):
A_folder = folders[i]
for j in range(i+1,len(campari_folders)):
B_folder = folders[j]
results_file = os.path.join("comparisons",sim_type, "%svs%s"%(A_folder, B_folder), "results", "conf_space_comp.json")
print results_file
if os.path.exists(results_file):
data.append(load_dic_in_json(results_file)["overlap"])
else:
data.append(0.)
print data
matrixToImage(CondensedMatrix(data), image_path, diagonal_value=1.)
def print_matrix(input_coordsets, output):
# Generate the matrix and print it
calculator = RMSDCalculator(calculatorType="QCP_OMP_CALCULATOR",
fittingCoordsets=input_coordsets)
matrixToImage(CondensedMatrix(calculator.pairwiseRMSDMatrix()),
output + ".png")
parameters["data"]["files"] = [sys.argv[1], sys.argv[2]]
frames_ini = get_number_of_frames(sys.argv[1])
frames_proto = get_number_of_frames(sys.argv[2])
print sys.argv[1],"->",frames_ini
print sys.argv[2],"->",frames_proto
try:
Driver(Observer()).run(parameters)
except SystemExit:
# Expected improductive search
# Load again the matrix
handler = MatrixHandler({
"method": "load",
"parameters": {
"path": parameters["workspace"]["base"]+"/matrix/matrix"
}
})
matrix = handler.create_matrix(None)
submatrix = get_submatrix(matrix, range(frames_ini,frames_ini+frames_proto))
matrixToImage(submatrix, parameters["workspace"]["base"] +"/submatrix.png")
print "Original mean:",get_submatrix(matrix, range(0,frames_ini)).calculateMean()
values = []
for i in range(0,frames_ini):
for j in range(frames_ini,frames_ini+frames_proto):
values.append((handler.distance_matrix[i,j],i,j-frames_ini))
for d,i,j in sorted(values):
print "%d %d %.2f"% (i,j,d)
print "Combined mean:", numpy.mean(values)
print sys.argv[1], "->", frames_ini
print sys.argv[2], "->", frames_proto
try:
Driver(Observer()).run(parameters)
except SystemExit:
# Expected improductive search
# Load again the matrix
handler = MatrixHandler({
"method": "load",
"parameters": {
"path": parameters["workspace"]["base"] + "/matrix/matrix"
}
})
matrix = handler.create_matrix(None)
submatrix = get_submatrix(matrix,
range(frames_ini, frames_ini + frames_proto))
matrixToImage(submatrix,
parameters["workspace"]["base"] + "/submatrix.png")
print "Original mean:", get_submatrix(matrix, range(
0, frames_ini)).calculateMean()
values = []
for i in range(0, frames_ini):
for j in range(frames_ini, frames_ini + frames_proto):
values.append((handler.distance_matrix[i,
j], i, j - frames_ini))
for d, i, j in sorted(values):
print "%d %d %.2f" % (i, j, d)
print "Combined mean:", numpy.mean(values)
def print_matrix(input_coordsets, output):
# Generate the matrix and print it
calculator = RMSDCalculator(calculatorType="QCP_OMP_CALCULATOR", fittingCoordsets = input_coordsets)
matrixToImage(CondensedMatrix(calculator.pairwiseRMSDMatrix()), output + ".png")