Describe a Person Who Is Very Confident: IELTS Speaking Guide

Learn essential tips and strategies for discussing confident individuals in your IELTS Speaking test. Master vocabulary, example answers, and key phrases to describe a person who is very confident effectively. # Sumit-Mali/simple-calculator let input = document.getElementById(‘inputBox’); let buttons =document.querySelectorAll(‘button’); let string=””; let arr= Array.from(buttons); arr.forEach(button=>{ button.addEventListener(‘click’,(e)=>{ if(e.target.innerHTML== ‘=’){ string=eval(string); input.value=string; } else if(e.target.innerHTML==’AC’){ string=””; input.value=string; } else if(e.target.innerHTML==’DEL’){ string=string.substring(0,string.length-1); input.value=string; } else{ string +=e.target.innerHTML; input.value=string; } }) })from typing import Optional from pydantic import BaseModel, ValidationError from src.core import ConstraintParameters class VariableDesc(BaseModel): Name: str Unit: str Symbol: str def __repr__(self): output = f”Name: {self.Name}n” output += f”Symbol: {self.Symbol}n” output += f”Unit: {self.Unit}n” return output class Constraint(BaseModel): Description: str Equation: str Values: ConstraintParameters def __repr__(self): output = f”Description: {self.Description}n” output += f”Equation: {self.Equation}n” output += f”Values: {self.Values}n” return output class SystemVariable(BaseModel): Variable: VariableDesc Parameters: list[str] Constraints: Optional[list[Constraint]] def __repr__(self): output = f”Variable: {self.Variable}n” output += f”Parameters: {self.Parameters}n” output += f”Constraints: {self.Constraints}n” return output class System(BaseModel): Name: str Parameters: list[VariableDesc] Variables: list[SystemVariable] class VariableRules: def __init__(self, system_dict: dict): self.system = System(**system_dict) @property def parameters(self) -> list[VariableDesc]: return self.system.Parameters @property def variables(self) -> list[SystemVariable]: return self.system.Variables def get_system_parameter(self, param: str) -> Optional[VariableDesc]: for parameter in self.parameters: if parameter.Name == param: return parameter return None def get_variable_by_name(self, name: str) -> Optional[SystemVariable]: for variable in self.variables: if variable.Variable.Name == name: return variable return None def get_variable_by_symbol(self, symbol: str) -> Optional[SystemVariable]: for variable in self.variables: if variable.Variable.Symbol == symbol: return variable return None def get_all_variable_names(self): output = [] for variable in self.variables: output.append(variable.Variable.Name) return output def get_all_variable_symbols(self): output = [] for variable in self.variables: output.append(variable.Variable.Symbol) return output def get_all_parameter_names(self): output = [] for parameter in self.parameters: output.append(parameter.Name) return output def get_constraints_for_variable(self, var_name: str) -> Optional[list[Constraint]]: variable = self.get_variable_by_name(var_name) if variable is None: return None return variable.Constraints if variable.Constraints is not None else None def get_variable_dependent_variables(self, var_name: str) -> Optional[list[str]]: constraints = self.get_constraints_for_variable(var_name) if constraints is None: return None output = [] for constraint in constraints: value_dict = constraint.Values.model_dump() values_used = list(value_dict.keys()) for value in values_used: if value in self.get_all_variable_names() and value not in output: output.append(value) return output def get_variable_dependent_parameters(self, var_name: str) -> Optional[list[str]]: constraints = self.get_constraints_for_variable(var_name) if constraints is None: return None output = [] for constraint in constraints: value_dict = constraint.Values.model_dump() values_used = list(value_dict.keys()) for value in values_used: if value in self.get_all_parameter_names() and value not in output: output.append(value) return output if __name__ == “__main__”: from os import path from src.core import System import ujson with open(path.join(path.dirname(__file__), “..”, “resources”, “hydraulics”, “hydraulics_desc.json”), “r”) as file: data = ujson.load(file) system = VariableRules(data) constraints = system.get_constraints_for_variable(‘Cross-sectional Area’) print(constraints) deps = system.get_variable_dependent_variables(‘Cross-sectional Area’) print(deps) print(system.get_variable_dependent_parameters(‘Cross-sectional Area’)) End File# src/unit_parser.py from pint import UnitRegistry class UnitParser: def __init__(self): self.ureg = UnitRegistry() self.ureg.define(‘pascal = 1 * kg / (m * s^2) = Pa’) self.ureg.define(‘newton = 1 * kg * m / s^2 = N’) self.ureg.define(‘watt = 1 * kg * m^2 / s^3 = W’) self.Q_ = self.ureg.Quantity def add_unit(self, unit_name: str, unit_equation: str) -> None: “””Adds a new unit to the unit registry with a unit equation and name Args: unit_name (str): The name of the unit to add unit_equation (str): The equation to define what the unit is equal to “”” self.ureg.define(f'{unit_name} = {unit_equation}’) def get_conversion_factor(self, from_unit: str, to_unit: str) -> float: “””Gets the conversion factor between two units Args: from_unit (str): The unit to convert from to_unit (str): The unit to convert to Returns: float: The conversion factor “”” try: start = self.Q_(1, from_unit) return float(start.to(to_unit).magnitude) except: return float(‘nan’) def convert_value(self, value: float, from_unit: str, to_unit: str) -> float: “””Converts a value from one unit to another Args: value (float): The value to convert from_unit (str): The unit to convert from to_unit (str): The unit to convert to Returns: float: The converted value “”” try: value = self.Q_(value, from_unit) return float(value.to(to_unit).magnitude) except: return float(‘nan’) if __name__ == “__main__”: unit_parser = UnitParser() print(unit_parser.get_conversion_factor(‘meters’, ‘centimeters’)) print(unit_parser.convert_value(1, ‘meter’, ‘centimeter’)) End File# PatrickJGabriel/PVTMaster from hydrostatics_plus import UnitAwarePoint2D from hydrostatics_plus import Unit from hydrostatics_plus import UnitAwareShip from hydrostatics_plus import Condition from hydrostatics_plus import UnitAwareShipParameters from hydrostatics_plus import UnitAwareCrossSection draft_units = Unit.INCHES length_units = Unit.FEET volume_units = Unit.CUFT weight_units = Unit.LONG_TONS area_units = Unit.SQFT ## Vessel Properties ## # Vessel Dimensions # [LOA, LOH, LOS, BOA, PD] vessel_dimensions = [160.0, 160.0, 160.0, 32.0, 15.0] dimensions_dict = { “LOA”: vessel_dimensions[0], “LOH”: vessel_dimensions[1], “LOS”: vessel_dimensions[2], “BOA”: vessel_dimensions[3], “PD”: vessel_dimensions[4] } # Tank Properties tank_volume = 200000 # barrels tank_volume_cf = tank_volume * 5.6145833333 # cubic feet # Steel Weight # [hull, cargo tanks, misc] steel_weights = [300, 400, 200] steel_weights_dict = { “hull”: steel_weights[0], “cargo tanks”: steel_weights[1], “misc”: steel_weights[2] } steel_weights_sum = sum(steel_weights) total_steel_weight = steel_weights_sum # long tons # Point Mass data (steel) steel_point_masses = [ [0.5, 7.0, 100], # [VCG, LCG, Weight] [0.5, 7.0, 100], # [VCG, LCG, Weight] [0.5, 7.0, 100], # [VCG, LCG, Weight] ] steel_point_masses_dict = { “hull”: steel_point_masses[0], “cargo tanks”: steel_point_masses[1], “misc”: steel_point_masses[2] } # Vessel Endpoint Data # [half breadth, height] AP_data = [16.0, 20.0] FP_data = [16.0, 20.0] AP_point = UnitAwarePoint2D(AP_data[0], AP_data[1], draft_units) FP_point = UnitAwarePoint2D(FP_data[0], FP_data[1], draft_units) # Input station configuration station_data = { 0: [0.0, AP_data[0], AP_data[1]], 1: [40.0, 16.0, 20.0], 2: [80.0, 16.0, 20.0], 3: [120.0, 16.0, 20.0], 4: [160.0, FP_data[0], FP_data[1]] } station_point_dict = {} for station in station_data: station_point_dict[station] = UnitAwarePoint2D(station_data[station][1], station_data[station][2], draft_units) ## Condition ## lightship_draft = 48.0 # inches – measured to keel service_draft = 120.0 # inches – measured to keel ## Run Code ## ship = UnitAwareShip() # Build Sections cross_sections = {} for station in station_data: # Get point from dict half_breadth = station_point_dict[station].x height = station_point_dict[station].y # Create Section section = UnitAwareCrossSection.rectangle(half_breadth * 2, height, draft_units) section.heel = 0 section.shift(section.B/2, 0) cross_sections[station_data[station][0]] = section ship.define_ship_sections(cross_sections, length_units, draft_units) # Point Masses for item in steel_point_masses: point_mass = item[2] lcg = item[1] vcg = item[0] ship.add_pointmass((point_mass, weight_units), (lcg * ship.LBP, length_units), (vcg * ship.LBP, length_units)) # Configure Attributes parameters = UnitAwareShipParameters() parameters.length_units = length_units parameters.draft_units = draft_units parameters.weight_units = weight_units parameters.volume_units = volume_units parameters.area_units = area_units parameters.heel = 0 parameters.draft = service_draft parameters.trim = 0 parameters.LCG = None parameters.VCG = None print(f”Length: {ship.LBP}”) print(f”Draft: {ship.draft}”) print(f”Beam: {ship.beam}”) # Generate Results results = ship.solve_for_equil(parameters) print(results) print(results.get_values()) print(results.dimensions) End File# PatrickJGabriel/PVTMaster from typing import Optional from pydantic import BaseModel, ValidationError class ConstraintParameters(BaseModel): pass def __repr__(self): output = “” for key, value in self.model_dump().items(): output += f”{key}: {value}n” return output if __name__ == “__main__”: params = {“diameter”: “16”} constraint = ConstraintParameters(**params) print(constraint) End Fileimport pandas as pd import numpy as np from os import path from typing import Union, List class Units: “”” A class for handling unit conversions and unit calculations for the PVT Master application “”” def __init__(self): “”” Initializes all conversions. Populates the conversions dataframe with all available conversions. “”” self.load_conversion_table() def get_conversion_table(self) -> pd.DataFrame: “””Returns the available conversions. Returns: dataframe: The dataframe containing unit conversion information “”” return self.conversions def load_conversion_table(self) -> None: “””Loads the conversion file from resources/units.csv and populates the available units conversion table “”” self.conversions = pd.read_csv(path.join(path.dirname(__file__), “resources”, “units.csv”)) def get_conversion_multiplier(self, from_unit: str, to_unit: str) -> Union[float, None]: “””Returns the multiplier to convert between two units. Checks both ways to see if inversion is needed. Args: from_unit (str): Unit to convert from to_unit (str): Unit to convert to Returns: float: The conversion multiplier; returns None if conversion is not possible. “”” row = (self.conversions[“Unit from”] == from_unit) & (self.conversions[“Unit to”] == to_unit) if(len(self.conversions[row]) > 0): return self.conversions[row][“Factor”].iat[0] row = (self.conversions[“Unit from”] == to_unit) & (self.conversions[“Unit to”] == from_unit) if(len(self.conversions[row]) > 0): return 1/self.conversions[row][“Factor”].iat[0] return None def test_single_conversion(value: float, conversions: pd.DataFrame, to_unit: str, from_unit: str) -> Union[float, None]: “””Tests the conversion of a single value. Does not handle multiple converted values Args: value (float): Value to convert conversions (pd.Dataframe): Dataframe containing conversion multipliers to_unit (str): Unit to convert to from_unit (str): Unit to convert from “”” converted_value = None row = (conversions[“Unit