+ init

NassiShneidermann.py

@@ -0,0 +1,63 @@
+from code_to_image import NSD_save
+from Iinstruction import Iinstruction
+import logging
+import re
+
+class NassiShneidermanDiagram:
+
+    def __init__(self, debug: bool=False) -> None:
+        self.instructions: dict[str, Iinstruction] = {}
+        self.init_logging(debug)
+
+    def init_logging(self, debug: bool):
+        logLevel = logging.INFO
+        if debug:
+            logLevel = logging.DEBUG
+        
+        logging.basicConfig(level=logLevel)
+    
+    def add_instruction(self, instruction: Iinstruction):
+        instruction_key = "instruction#" + str(len(self.instructions))
+        self.instructions[instruction_key] = instruction
+        logging.debug("added instruction %s : %s", instruction_key, instruction.instruction_text)
+
+    def convert_to_image(self, filename: str, x_size=200):
+        logging.info(f"Saving NSD to {filename}.png")
+        cti.NSD_init(x_size, 1000)
+        x, y, x_sz = 0, 0, x_size
+        for _k, instruction in self.instructions.items():
+            x, y = instruction.to_image(x, y, x_sz, 200)
+        cti.NSD_save(filename)
+
+    @staticmethod
+    def load_code_lines(filepath):
+        lines = []
+        try:
+            with open(filepath) as file:
+                for _line in file:
+                    line:str = _line.strip()
+                    if line and not re.match(r"""^//|^#|^COMMENT|^--""", line):
+                        lines.append(line)
+        except:
+            logging.error(f"Failed to open input path {filepath}!")
+        
+        return lines
+
+    def load_from_file(self, filepath: str):
+        filtered_lines = self.load_code_lines(filepath)
+        print(filtered_lines)
+        num_brace
+        for line in filtered_lines:
+            if line.startswith("while("):
+
+    
+if __name__ == "__main__":
+    """for debugging"""
+
+    from Iinstruction import *
+
+    NSD = NassiShneidermanDiagram(True)
+
+    NSD.load_from_file("res/input/input.java")
+
+    NSD.convert_to_image("Nina", 500)