Advanced Gantt chart functionalities

build/lib/scheptk/scheptk.py

@@ -853,6 +853,9 @@ def random_solution(self):
     # implementation of the completion times of each job on each machine for OpenShop
     # it has to be a full sequence
     def ct(self, sequence):
+
+       # job order to be returned
+       job_order = []
 
        # completion times of jobs and machines
        ct_jobs = [self.r[j] for j in range(self.jobs)]
@@ -865,6 +868,10 @@ def ct(self, sequence):
 
            # obtain decoded_job
            decoded_job = job % self.jobs
+
+           # if it is a new job, it is appended to the job_order
+           if len([e for e in job_order if e == decoded_job]) == 0:
+               job_order.append(decoded_job)
 
            # obtain decoded machine
            decoded_machine = int((job - decoded_job) / self.jobs)
@@ -874,9 +881,11 @@ def ct(self, sequence):
            ct_jobs[decoded_job]= curr_completion_time
            ct_machines[decoded_machine] = curr_completion_time
 
-           ct[decoded_machine][decoded_job] = curr_completion_time
+           # puts the completion time in the proper position the completion times matrix
+           order_decoded_job = job_order.index(decoded_job)
+           ct[decoded_machine][order_decoded_job] = curr_completion_time
 
-       return ct, ct_jobs
+       return ct, job_order
 
 
 

build/lib/scheptk/util.py

@@ -3,6 +3,57 @@
 import operator # for sorted functions
 from random import randint # generation of random integer numbers
 
+
+# utility function to edit the value of a tag in a file
+# returns -1 if the tag is not found, the line in the file where the tag is found otherwise
+def edit_tag(tag, value, filename):
+    # obtiene el valor de la etiqueta en formato lista
+    string_value = ''
+    if isinstance(value,list):
+        if isinstance(value[0],list):
+            # es una matriz
+            string_value = matrix_to_string(value)
+        else:
+            # es una lista
+            string_value = vector_to_string(value)
+    else:
+        string_value = str(value)
+
+    found_at = -1
+    # loading all tags
+    with open(filename,'r') as file:
+        list_lines = file.readlines()
+    # search the specific tag
+    for x, line in enumerate(list_lines):
+        if line.find('[' + tag + '=')!= -1:
+            found_at = x
+    # if found, changes the line
+    if found_at != -1:
+        # gets the part before the [
+        start = list_lines[found_at].index('=')
+        #new line
+        new_line = list_lines[found_at][:start] + '='+ string_value + "]\n"
+        list_lines[found_at] = new_line
+        # writes the file with the new value of the tag
+        with open(filename,'w') as file:
+            file.writelines(list_lines)
+    return found_at
+
+
+
+# find_index_max() returns the index where the maximum value is found
+def find_index_max(list):
+    tuple = enumerate(list)
+    sorted_tuple = sorted(tuple, key=operator.itemgetter(1), reverse=True)
+    return sorted_tuple[0][0]
+
+# find_index_min() returns the index where the minimum value is found
+def find_index_min(list):
+    tuple = enumerate(list)
+    sorted_tuple = sorted(tuple, key=operator.itemgetter(1), reverse=False)
+    return sorted_tuple[0][0]
+
+
 # utility function to get the proper type (int, string, float) of an argument
 def get_proper_type(x):
     if isinstance(ast.literal_eval(x), int):
@@ -14,6 +65,20 @@ def get_proper_type(x):
             return x
 
 
+# utility function to map a matrix into a string (mostly to be used internally)
+def matrix_to_string(matrix):
+    cadena = ''
+    for i in range(len(matrix)-1):
+        for j in range(len(matrix[i]) - 1):
+            cadena = cadena + str(matrix[i][j]) + ","
+        cadena = cadena + str(matrix[i][len(matrix[i])-1]) + ";"
+    # last row
+    for j in range(len(matrix[0])-1):
+        cadena = cadena + str(matrix[len(matrix)-1][j]) + ","
+    # last col of last row
+    return cadena + str(matrix[len(matrix)-1][len(matrix[0])-1]) 
+
+
 # utility function to print the content of val (escalar, vector, matrix) with a tag
 def print_tag(tag, value):
     # if it is a list
@@ -28,28 +93,17 @@ def print_tag(tag, value):
         # it is an scalar
         print("[" + tag + "=" + str(value) + "]")  
 
-
-# utility function to map a vector into a string (mostly to be used internally)
-def vector_to_string(vector):
-    cadena = ''
-    for i in range(len(vector)-1):
-        cadena = cadena + str(vector[i]) + ","
-    return cadena + str(vector[len(vector)-1]) 
+# utility function to generate a random sequence of length size
+def random_sequence(size):
+    sequence = []
+    for i in range(size):
+        number = randint(0, size-1)
+        while( sequence.count(number)!= 0):
+            number = randint(0, size-1)
+        sequence.append(number)
+    return sequence
 
 
-# utility function to map a matrix into a string (mostly to be used internally)
-def matrix_to_string(matrix):
-    cadena = ''
-    for i in range(len(matrix)-1):
-        for j in range(len(matrix[i]) - 1):
-            cadena = cadena + str(matrix[i][j]) + ","
-        cadena = cadena + str(matrix[i][len(matrix[i])-1]) + ";"
-    # last row
-    for j in range(len(matrix[0])-1):
-        cadena = cadena + str(matrix[len(matrix)-1][j]) + ","
-    # last col of last row
-    return cadena + str(matrix[len(matrix)-1][len(matrix[0])-1]) 
-
 
 # utility function to read a tag
 def read_tag(filename, tag):
@@ -112,28 +166,12 @@ def sorted_value_asc(list):
 def sorted_value_desc(list):
     return sorted_value(list, True)
 
-# utility function to generate a random sequence of length size
-def random_sequence(size):
-    sequence = []
-    for i in range(size):
-        number = randint(0, size-1)
-        while( sequence.count(number)!= 0):
-            number = randint(0, size-1)
-        sequence.append(number)
-    return sequence
-
-
-# find_index_max() returns the index where the maximum value is found
-def find_index_max(list):
-    tuple = enumerate(list)
-    sorted_tuple = sorted(tuple, key=operator.itemgetter(1), reverse=True)
-    return sorted_tuple[0][0]
-
-# find_index_min() returns the index where the minimum value is found
-def find_index_min(list):
-    tuple = enumerate(list)
-    sorted_tuple = sorted(tuple, key=operator.itemgetter(1), reverse=False)
-    return sorted_tuple[0][0]
+# utility function to map a vector into a string (mostly to be used internally)
+def vector_to_string(vector):
+    cadena = ''
+    for i in range(len(vector)-1):
+        cadena = cadena + str(vector[i]) + ","
+    return cadena + str(vector[len(vector)-1]) 
 
 # utility function to write a tag (scalar, vector, matrix) and its value into a file
 def write_tag(tag, value, filename):

scheptk.egg-info/PKG-INFO

@@ -1,28 +1,25 @@
 Metadata-Version: 2.1
 Name: scheptk
-Version: 0.0.5
+Version: 0.0.6
 Summary: Python scheduling package
 Home-page: https://github.com/framinan/scheptk
 Author: Jose M Framinan
 Author-email: framinan@us.es
 License: UNKNOWN
+Description: ## `scheptk` - Scheduling Python ToolKit
+
+        `scheptk` is a collection of classes and functions to model and solve machine scheduling problems using Python. It is intended basically for teaching purposes, even if the algorithms can be integrated with MOIST, a more advanced scheduling tool.
+
+        # How to use it
+
+        In order to use `scheptk` you can install it as a Python package using `pip`:
+
+        `pip install scheptk`
+
+        At this point, the clasess and functions of `scheptk` should be available. You might want to have a look at the [wiki pages](https://github.com/framinan/scheptk/wiki) to get a handle on the documentation.
+
+
 Platform: UNKNOWN
 Classifier: Programming Language :: Python :: 3.7
 Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
 Description-Content-Type: text/markdown
-License-File: LICENSE
-
-## `scheptk` - Scheduling Python ToolKit
-
-`scheptk` is a collection of classes and functions to model and solve machine scheduling problems using Python. It is intended basically for teaching purposes, even if the algorithms can be integrated with MOIST, a more advanced scheduling tool.
-
-# How to use it
-
-In order to use `scheptk` you can install it as a Python package using `pip`:
-
-`pip install scheptk`
-
-At this point, the clasess and functions of `scheptk` should be available. You might want to have a look at the [wiki pages](https://github.com/framinan/scheptk/wiki) to get a handle on the documentation.
-
-
-