World Cup Qualification UEFA 1st Round Group C stats & predictions

Analyzing past performances provides valuable insights into potential outcomes for tomorrow's matches. Here are some key statistics from previous encounters between these teams:

• Espana vs Sverige (Spain vs Sweden):
• Past five meetings: Spain won three times, one draw, one Swedish victory.
• Average goals per match: 2.6 (Spain scored 10 goals).
• Last meeting result: Spain won 2-0 at home in March 2020.
• Gruzija vs Ellada (Georgia vs Greece):
• Past five meetings: One Greek victory, two draws, two Georgian victories.
• Average goals per match: 1.6 (Greece scored seven goals).
• Last meeting result: Draw 1-1 in Tbilisi in September 2021.
• Kosova vs Norge (Kosovo vs Norway):
• Past five meetings: Three Norwegian victories, one draw, one Kosovan victory.
• Average goals per match: 2.6 (Norway scored nine goals).
• Last meeting result: Norway won 2-0 away in Oslo in September 2021.

Analyzing these statistics helps identify trends and patterns that can influence betting decisions. For example, Spain's historical dominance over Sweden suggests they might have an edge tomorrow. However, football is unpredictable, and upsets can happen at any time.

Injury Updates and Team News

Injuries and team news can significantly impact match outcomes. Here are the latest updates for each team involved in tomorrow’s fixtures:

• Espana (Spain):
• Pedri González is fit after recovering from a minor injury scare during training sessions this week.
• Mikel Oyarzabal is expected to start after missing recent games due to illness but remains under close observation by medical staff.
• Sverige (Sweden):
• Zlatan Ibrahimović has been ruled out due to an ongoing hamstring issue but may return later in qualifying rounds if fit enough by then;
• Theo Hernández suffered an ankle sprain last week but should recover sufficiently for tomorrow’s clash against Espana according reports coming out today from coach Janne Andersson’s pre-match press conference yesterday evening; however his participation remains uncertain until closer inspection during warm-up sessions today morning ahead of kick-off time scheduled at 20:45 CET tonight here at Estadio Benito Villamarín located within Seville city limits down south part peninsula known also colloquially amongst locals as “España” meaning “Spain” itself!BensungYun/BlueDot<|file_sep|>/BlueDot/Sources/BlueDot/Scenes/Bluetooth/BLEManager.swift // // BLEManager.swift // // // Created by Sung Yun Bae on 2021/02/01. // import Foundation import CoreBluetooth class BLEManager { static let shared = BLEManager() // MARK:- Singleton Properties // MARK:- Public Properties var centralManager : CBCentralManager! // MARK:- Private Properties // MARK:- Public Methods // MARK:- Private Methods // MARK:- LifeCycle Methods } <|repo_name|>BensungYun/BlueDot<|file_sep|>/BlueDot/Sources/BlueDot/Scenes/Main/MainViewController.swift // // MainViewController.swift // // // Created by Sung Yun Bae on 2021/02/01. // import UIKit class MainViewController: UIViewController { // MARK:- Singleton Properties // MARK:- Public Properties // MARK:- Private Properties // MARK:- Public Methods // MARK:- Private Methods // MARK:- LifeCycle Methods override func viewDidLoad() { super.viewDidLoad() self.view.backgroundColor = .white let button = UIButton() button.setTitle("BLE Scene", for: .normal) button.setTitleColor(.black, for: .normal) button.addTarget(self, action:#selector(moveToBLEScene), for:.touchUpInside) self.view.addSubview(button) button.translatesAutoresizingMaskIntoConstraints = false NSLayoutConstraint.activate([ button.centerXAnchor.constraint(equalTo:self.view.centerXAnchor), button.centerYAnchor.constraint(equalTo:self.view.centerYAnchor), button.widthAnchor.constraint(equalToConstant:100), button.heightAnchor.constraint(equalToConstant:50), ]) } @objc private func moveToBLEScene() { self.navigationController?.pushViewController(BLEViewController(), animated:true) } } <|repo_name|>BensungYun/BlueDot<|file_sep|>/BlueDot/Sources/BlueDot/Scenes/Bluetooth/BLEViewController.swift // // BLEViewController.swift // // // Created by Sung Yun Bae on 2021/02/01. // import UIKit class BLEViewController: UIViewController { // MARK:- Singleton Properties // MARK:- Public Properties // MARK:- Private Properties // MARK:- Public Methods // MARK:- Private Methods // MARK:- LifeCycle Methods override func viewDidLoad() { super.viewDidLoad() self.view.backgroundColor = .white } } <|repo_name|>openai/gym-electric-motor<|file_sep|>/gym_electric_motor/envs/__init__.py from gym_electric_motor.envs.motor_env import MotorEnv __all__ = ['MotorEnv'] <|repo_name|>openai/gym-electric-motor<|file_sep|>/gym_electric_motor/envs/sensors.py """ Sensor classes for Electric Motor Gym Environment This module contains classes that define sensors used within gym environments. The classes have two main responsibilities: (1) Provide methods that map electric motor states into sensor values. (2) Transform motor states into sensor values. The mapping functions can either return single values or tuples of values, depending on whether one or multiple sensors are defined. Sensor classes can be used independently from gym environments by defining sensor objects manually. Example: >>> my_sensor = SensorDC() >>> my_sensor.transform([0., -100., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -10000]) array([[-100.]]) """ from gym_electric_motor.physical_systems import PhysicalSystemDC import numpy as np class Sensor(object): """ Base class for sensors. Sensors define how states of electric motors are transformed into sensor values. The sensor value is used as observation within reinforcement learning algorithms. Attributes: physical_system (PhysicalSystem): Physical system whose state shall be transformed into sensor value. sensor_mapping (function): Function that maps motor states into sensor values. sensor_names (list[str]): Names of sensors. """ def __init__(self): self.physical_system = None self.sensor_mapping = None self.sensor_names = None def transform(self, state): """ Transforms motor state into sensor value. The transformation depends on type of sensor. Parameters: state (np.ndarray): State of physical system whose state shall be transformed into sensor value. Returns: sensor_value (np.ndarray): Sensor value corresponding to input state. sensor_value.shape = (len(self.sensor_names),) If only one sensor value is returned then shape == (1,) """ raise NotImplementedError() def get_state_names(self): return self.physical_system.get_state_names() def get_action_names(self): return self.physical_system.get_action_names() class SensorDC(Sensor): """ Sensor class for Direct Current motors. Sensors are defined as follows: normed_stator_currents : stator currents normalized by stator current rating [pu] normed_rotor_current : rotor current normalized by stator current rating [pu] normed_rotor_angle : rotor angle normalized by pi [-] normed_speed : rotor speed normalized by nominal speed [pu] voltage : stator voltage [V] current : stator current [A] torque : electromagnetic torque [Nm] The normed quantities are defined as follows: normed_stator_currents = stator currents / I_Nominal [pu] normed_rotor_current = rotor current / I_Nominal [pu] normed_rotor_angle = rotor angle / pi [-] normed_speed = rotor speed / omega_Nominal [pu] Sensors can also return unnormalized values: stator_currents : stator currents [A] stator_voltage : stator voltage [V] torque : electromagnetic torque [Nm] The normalization depends on type of electric motor: Direct Current Synchronous Motor (DcSynchronousMotor): normed_stator_currents = i_a / I_Nominal + i_b / I_Nominal + i_c / I_Nominal [pu] normed_rotor_current = i_f / I_Nominal + i_b / I_Nominal + i_c / I_Nominal [pu] normed_rotor_angle = theta_r / pi [-] normed_speed = omega_r / omega_Nominal [pu] Direct Current Induction Motor (DcInductionMotor): normed_stator_currents = i_a / I_Nominal + i_b / I_Nominal + i_c / I_Nominal [pu] normed_rotor_current = i_ar / I_Nominal + i_br / I_Nominal + i_cr / I_Nominal [pu] normed_rotor_angle = theta_r / pi [-] normed_speed = omega_r / omega_Nominal [pu] Direct Current Permanent Magnet Synchronous Motor (DcPermanentMagnetSynchronousMotor): normed_stator_currents = i_a / I_Nominal + i_b / I_Nominal + i_c / I_Nominal [pu] normed_rotor_current = --- --- --- [pu] normed_rotor_angle = theta_r / pi [-] theta_rpm --- normed_speed = omega_rpm omega_rpm --- Direct Current Switched Reluctance Motor (DcSwitchedReluctanceMotor): normed_stator_currents = i_a * phase_a_on + i_b * phase_b_on + i_c * phase_c_on + i_d * phase_d_on [pu] normed_rotor_current = --- --- --- --- normed_rotor_angle = theta_r theta_r theta_r --- normed_speed = omega_r omega_r omega_r --- Direct Current Commutated Pole Motor (DcCommutatedPoleMotor): normed_stator_currents = i_a * phase_a_on + i_b * phase_b_on --- --- normed_rotor_current = --- --- --- --- normed_rotor_angle = theta_rm theta_rm --- --- normed_speed = omega_rm omega_rm --- --- Single Phase Permanent Magnet Synchronous Motor (SinusoidalCurrentSourceSinglePhasePermanentMagnetSynchronousMotor): normed_stator_currents = sqrt(i_d ** 2 + i_q ** 2) --- --- normed_rotor_current = --- --- --- --- normed_rotor_angle = theta_pm theta_pm theta_pm --- normed_speed = omega_pm omega_pm omega_pm --- Multi Phase Permanent Magnet Synchronous Motor (SinusoidalCurrentSourceMultiPhasePermanentMagnetSynchronousMotor): normed_stator_currents = sqrt((i_a ** 2) + (i_b ** 2) + (i_c ** 2)) sqrt((i_d ** 2) + (i_e ** 2) + (i_f ** 2)) --- [sqrt(i_a ** 2 + ...)] [sqrt(i_d ** 2 + ...)] --- if num_phases == 3 if num_phases == 3 --- sqrt((i_a ** 2) + ... + (i_n ** 2)) sqrt((i