Module visualization.GraphController

Classes

class GraphController (filename='sim', isDark=False, colorVision='None', error='0', age_unit='Month', cohort_unit='Month', separator=',', decimal='.', language='English')

Contains all the information necessary to generate graphs

initialize graphController parameter: - filename (str): a string indicating the name of the graph. - isDark (bool): If True, use colorblind-friendly colors in the visualizations. (Default is False) - colorVision (str): mode of color vision dificiency. possible choice: "redGreen", "blueYellow","full". (default is "full") - error: a string indicating the error to add to the slope of the predicted data (default is "0") - ageUnit (str): unit of age. Possible value: "Month", "Year", "Day". (default is "Month") - cohortUnit (str): unit of cohort. Possible value: "Month", "Year", "Day". (default is "Month") - separator (str): separator of database. (default is ",") - decimal (str): decimal of database. (default is ".") - language (str): Language user choose. (default is "English")

Expand source code

class GraphController:
    """
    Contains all the information necessary to generate graphs
    """
    filename = "sim"
    isDark = False
    error = "0"
    age_unit = "Month"
    cohort_unit = "Month"
    data = None
    colorVision = "None"
    language = "English"

    
    def __init__(self, filename="sim", isDark=False, colorVision = "None",error="0", 
                 age_unit="Month", cohort_unit="Month", separator=",", decimal=".",language="English"):
        """
        initialize graphController
        parameter:
        - filename (str): a string indicating the name of the graph.
        - isDark (bool): If True, use colorblind-friendly colors in the visualizations. (Default is False)
        - colorVision (str): mode of color vision dificiency. possible choice: "redGreen", "blueYellow","full". (default is "full")
        - error: a string indicating the error to add to the slope of the predicted data (default is "0")
        - ageUnit (str): unit of age. Possible value: "Month", "Year", "Day". (default is "Month")
        - cohortUnit (str): unit of cohort. Possible value: "Month", "Year", "Day". (default is "Month")
        - separator (str): separator of database. (default is ",")
        - decimal (str): decimal of database. (default is ".")
        - language (str): Language user choose. (default is "English")
        
        """
        self.filename =filename
        try:   # TODO
            self.data = pd.read_csv(f"../../visualization/{filename}.csv", decimal=decimal, sep=separator)
        except:
            self.data = pd.read_csv(f"{filename}.csv", decimal=decimal, sep=separator)
        self.isDark = isDark
        self.colorVision = colorVision
        self.error = error
        self.age_unit = age_unit
        self.cohort_unit = cohort_unit
        self.language = language
        self.data['pd'] = self.data['pd']
        if(age_unit == "Day"):
            self.data["t"] = self.data["t"]/365.25 * 12 
            self.data = self.data.astype({'t':'int'})
        elif(age_unit == "Year"):
            self.data["t"] = self.data["t"] * 12
            self.data = self.data.astype({'t':'int'})
        if(cohort_unit == "Day"):
            self.data["v"] = self.data["v"]/365.25 * 12
            self.data = self.data.astype({'v':'int'})
            self.data = self.data.iloc[:][self.data["v"] <= 36]   #TODO
        elif(cohort_unit == "Year"):
            self.data["v"] = self.data["v"] * 12
            self.data = self.data.astype({'v':'int'})

    def data_filter(self,feature,condition,value):
        """
        filter data according to given conditinos
        parameter:
        feature (str): String of feature
        condition (str): condition. Possible value: "<",">"
        value (str): value.
        i.e. featuer condition value   e.g. x1 < 400
        """
        if condition == ">":
            data = self.data.iloc[:][self.data[feature] > int(value)]
        elif condition == "<":
            data = self.data.iloc[:][self.data[feature] < int(value)]
        else:
            data = self.data
        return data

Class variables

var age_unit

var cohort_unit

var colorVision

var data

var error

var filename

var isDark

var language

Methods

def data_filter(self, feature, condition, value)

filter data according to given conditinos parameter: feature (str): String of feature condition (str): condition. Possible value: "<",">" value (str): value. i.e. featuer condition value e.g. x1 < 400

Expand source code

def data_filter(self,feature,condition,value):
    """
    filter data according to given conditinos
    parameter:
    feature (str): String of feature
    condition (str): condition. Possible value: "<",">"
    value (str): value.
    i.e. featuer condition value   e.g. x1 < 400
    """
    if condition == ">":
        data = self.data.iloc[:][self.data[feature] > int(value)]
    elif condition == "<":
        data = self.data.iloc[:][self.data[feature] < int(value)]
    else:
        data = self.data
    return data