prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Hyperopt Resamples
     Python Version: 3.6.7
      CCXT version: 1.18.507
      Branch: Develop
      Last Commit ID: 4ae743e
  
    
  ## Step 3: Describe the problem:
  
  self.ticker_interval is not implemented in the hyperopt interface, so you cannot resample data to higher timeframes.
  
  
  
  </issue>
  <code>
  [start of freqtrade/optimize/hyperopt_interface.py]
  1 """
  2 IHyperOpt interface
  3 This module defines the interface to apply for hyperopts
  4 """
  5 
  6 from abc import ABC, abstractmethod
  7 from typing import Dict, Any, Callable, List
  8 
  9 from pandas import DataFrame
  10 from skopt.space import Dimension
  11 
  12 
  13 class IHyperOpt(ABC):
  14     """
  15     Interface for freqtrade hyperopts
  16     Defines the mandatory structure must follow any custom strategies
  17 
  18     Attributes you can use:
  19         minimal_roi -> Dict: Minimal ROI designed for the strategy
  20         stoploss -> float: optimal stoploss designed for the strategy
  21         ticker_interval -> int: value of the ticker interval to use for the strategy
  22     """
  23 
  24     @staticmethod
  25     @abstractmethod
  26     def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
  27         """
  28         Populate indicators that will be used in the Buy and Sell strategy
  29         :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
  30         :return: a Dataframe with all mandatory indicators for the strategies
  31         """
  32 
  33     @staticmethod
  34     @abstractmethod
  35     def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
  36         """
  37         Create a buy strategy generator
  38         """
  39 
  40     @staticmethod
  41     @abstractmethod
  42     def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
  43         """
  44         Create a sell strategy generator
  45         """
  46 
  47     @staticmethod
  48     @abstractmethod
  49     def indicator_space() -> List[Dimension]:
  50         """
  51         Create an indicator space
  52         """
  53 
  54     @staticmethod
  55     @abstractmethod
  56     def sell_indicator_space() -> List[Dimension]:
  57         """
  58         Create a sell indicator space
  59         """
  60 
  61     @staticmethod
  62     @abstractmethod
  63     def generate_roi_table(params: Dict) -> Dict[int, float]:
  64         """
  65         Create an roi table
  66         """
  67 
  68     @staticmethod
  69     @abstractmethod
  70     def stoploss_space() -> List[Dimension]:
  71         """
  72         Create a stoploss space
  73         """
  74 
  75     @staticmethod
  76     @abstractmethod
  77     def roi_space() -> List[Dimension]:
  78         """
  79         Create a roi space
  80         """
  81
  [end of freqtrade/optimize/hyperopt_interface.py]
  [start of freqtrade/resolvers/hyperopt_resolver.py]
  1 # pragma pylint: disable=attribute-defined-outside-init
  2 
  3 """
  4 This module load custom hyperopts
  5 """
  6 import logging
  7 from pathlib import Path
  8 from typing import Optional, Dict
  9 
  10 from freqtrade.constants import DEFAULT_HYPEROPT
  11 from freqtrade.optimize.hyperopt_interface import IHyperOpt
  12 from freqtrade.resolvers import IResolver
  13 
  14 logger = logging.getLogger(__name__)
  15 
  16 
  17 class HyperOptResolver(IResolver):
  18     """
  19     This class contains all the logic to load custom hyperopt class
  20     """
  21 
  22     __slots__ = ['hyperopt']
  23 
  24     def __init__(self, config: Optional[Dict] = None) -> None:
  25         """
  26         Load the custom class from config parameter
  27         :param config: configuration dictionary or None
  28         """
  29         config = config or {}
  30 
  31         # Verify the hyperopt is in the configuration, otherwise fallback to the default hyperopt
  32         hyperopt_name = config.get('hyperopt') or DEFAULT_HYPEROPT
  33         self.hyperopt = self._load_hyperopt(hyperopt_name, extra_dir=config.get('hyperopt_path'))
  34 
  35         if not hasattr(self.hyperopt, 'populate_buy_trend'):
  36             logger.warning("Custom Hyperopt does not provide populate_buy_trend. "
  37                            "Using populate_buy_trend from DefaultStrategy.")
  38         if not hasattr(self.hyperopt, 'populate_sell_trend'):
  39             logger.warning("Custom Hyperopt does not provide populate_sell_trend. "
  40                            "Using populate_sell_trend from DefaultStrategy.")
  41 
  42     def _load_hyperopt(
  43             self, hyperopt_name: str, extra_dir: Optional[str] = None) -> IHyperOpt:
  44         """
  45         Search and loads the specified hyperopt.
  46         :param hyperopt_name: name of the module to import
  47         :param extra_dir: additional directory to search for the given hyperopt
  48         :return: HyperOpt instance or None
  49         """
  50         current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
  51 
  52         abs_paths = [
  53             current_path.parent.parent.joinpath('user_data/hyperopts'),
  54             current_path,
  55         ]
  56 
  57         if extra_dir:
  58             # Add extra hyperopt directory on top of search paths
  59             abs_paths.insert(0, Path(extra_dir))
  60 
  61         for _path in abs_paths:
  62             try:
  63                 hyperopt = self._search_object(directory=_path, object_type=IHyperOpt,
  64                                                object_name=hyperopt_name)
  65                 if hyperopt:
  66                     logger.info("Using resolved hyperopt %s from '%s'", hyperopt_name, _path)
  67                     return hyperopt
  68             except FileNotFoundError:
  69                 logger.warning('Path "%s" does not exist', _path.relative_to(Path.cwd()))
  70 
  71         raise ImportError(
  72             "Impossible to load Hyperopt '{}'. This class does not exist"
  73             " or contains Python code errors".format(hyperopt_name)
  74         )
  75
  [end of freqtrade/resolvers/hyperopt_resolver.py]
  </code>
  
  I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
  <patch>
  diff --git a/file.py b/file.py
  --- a/file.py
  +++ b/file.py
  @@ -1,27 +1,35 @@
   def euclidean(a, b):
  -    while b:
  -        a, b = b, a % b
  -    return a
  +    if b == 0:
  +        return a
  +    return euclidean(b, a % b)
   
   
   def bresenham(x0, y0, x1, y1):
       points = []
       dx = abs(x1 - x0)
       dy = abs(y1 - y0)
  -    sx = 1 if x0 < x1 else -1
  -    sy = 1 if y0 < y1 else -1
  -    err = dx - dy
  +    x, y = x0, y0
  +    sx = -1 if x0 > x1 else 1
  +    sy = -1 if y0 > y1 else 1
   
  -    while True:
  -        points.append((x0, y0))
  -        if x0 == x1 and y0 == y1:
  -            break
  -        e2 = 2 * err
  -        if e2 > -dy:
  -            err -= dy
  -            x0 += sx
  -        if e2 < dx:
  -            err += dx
  -            y0 += sy
  +    if dx > dy:
  +        err = dx / 2.0
  +        while x != x1:
  +            points.append((x, y))
  +            err -= dy
  +            if err < 0:
  +                y += sy
  +                err += dx
  +            x += sx
  +    else:
  +        err = dy / 2.0
  +        while y != y1:
  +            points.append((x, y))
  +            err -= dx
  +            if err < 0:
  +                x += sx
  +                err += dy
  +            y += sy
  +
  +    points.append((x, y))
       return points
  
  </patch>
golden_diff: diff --git a/freqtrade/optimize/hyperopt_interface.py b/freqtrade/optimize/hyperopt_interface.py
  --- a/freqtrade/optimize/hyperopt_interface.py
  +++ b/freqtrade/optimize/hyperopt_interface.py
  @@ -20,6 +20,7 @@
           stoploss -> float: optimal stoploss designed for the strategy
           ticker_interval -> int: value of the ticker interval to use for the strategy
       """
  +    ticker_interval: str
   
       @staticmethod
       @abstractmethod
  diff --git a/freqtrade/resolvers/hyperopt_resolver.py b/freqtrade/resolvers/hyperopt_resolver.py
  --- a/freqtrade/resolvers/hyperopt_resolver.py
  +++ b/freqtrade/resolvers/hyperopt_resolver.py
  @@ -32,6 +32,9 @@
           hyperopt_name = config.get('hyperopt') or DEFAULT_HYPEROPT
           self.hyperopt = self._load_hyperopt(hyperopt_name, extra_dir=config.get('hyperopt_path'))
   
  +        # Assign ticker_interval to be used in hyperopt
  +        self.hyperopt.__class__.ticker_interval = str(config['ticker_interval'])
  +
           if not hasattr(self.hyperopt, 'populate_buy_trend'):
               logger.warning("Custom Hyperopt does not provide populate_buy_trend. "
                              "Using populate_buy_trend from DefaultStrategy.")
  
verification_info: {"golden_diff": "diff --git a/freqtrade/optimize/hyperopt_interface.py b/freqtrade/optimize/hyperopt_interface.py\n--- a/freqtrade/optimize/hyperopt_interface.py\n+++ b/freqtrade/optimize/hyperopt_interface.py\n@@ -20,6 +20,7 @@\n         stoploss -> float: optimal stoploss designed for the strategy\n         ticker_interval -> int: value of the ticker interval to use for the strategy\n     \"\"\"\n+    ticker_interval: str\n \n     @staticmethod\n     @abstractmethod\ndiff --git a/freqtrade/resolvers/hyperopt_resolver.py b/freqtrade/resolvers/hyperopt_resolver.py\n--- a/freqtrade/resolvers/hyperopt_resolver.py\n+++ b/freqtrade/resolvers/hyperopt_resolver.py\n@@ -32,6 +32,9 @@\n         hyperopt_name = config.get('hyperopt') or DEFAULT_HYPEROPT\n         self.hyperopt = self._load_hyperopt(hyperopt_name, extra_dir=config.get('hyperopt_path'))\n \n+        # Assign ticker_interval to be used in hyperopt\n+        self.hyperopt.__class__.ticker_interval = str(config['ticker_interval'])\n+\n         if not hasattr(self.hyperopt, 'populate_buy_trend'):\n             logger.warning(\"Custom Hyperopt does not provide populate_buy_trend. \"\n                            \"Using populate_buy_trend from DefaultStrategy.\")\n", "issue": "Hyperopt Resamples\n   Python Version: 3.6.7\r\n    CCXT version: 1.18.507\r\n    Branch: Develop\r\n    Last Commit ID: 4ae743e\r\n\r\n  \r\n## Step 3: Describe the problem:\r\n\r\nself.ticker_interval is not implemented in the hyperopt interface, so you cannot resample data to higher timeframes.\r\n\r\n\n", "before_files": [{"content": "\"\"\"\nIHyperOpt interface\nThis module defines the interface to apply for hyperopts\n\"\"\"\n\nfrom abc import ABC, abstractmethod\nfrom typing import Dict, Any, Callable, List\n\nfrom pandas import DataFrame\nfrom skopt.space import Dimension\n\n\nclass IHyperOpt(ABC):\n    \"\"\"\n    Interface for freqtrade hyperopts\n    Defines the mandatory structure must follow any custom strategies\n\n    Attributes you can use:\n        minimal_roi -> Dict: Minimal ROI designed for the strategy\n        stoploss -> float: optimal stoploss designed for the strategy\n        ticker_interval -> int: value of the ticker interval to use for the strategy\n    \"\"\"\n\n    @staticmethod\n    @abstractmethod\n    def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:\n        \"\"\"\n        Populate indicators that will be used in the Buy and Sell strategy\n        :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()\n        :return: a Dataframe with all mandatory indicators for the strategies\n        \"\"\"\n\n    @staticmethod\n    @abstractmethod\n    def buy_strategy_generator(params: Dict[str, Any]) -> Callable:\n        \"\"\"\n        Create a buy strategy generator\n        \"\"\"\n\n    @staticmethod\n    @abstractmethod\n    def sell_strategy_generator(params: Dict[str, Any]) -> Callable:\n        \"\"\"\n        Create a sell strategy generator\n        \"\"\"\n\n    @staticmethod\n    @abstractmethod\n    def indicator_space() -> List[Dimension]:\n        \"\"\"\n        Create an indicator space\n        \"\"\"\n\n    @staticmethod\n    @abstractmethod\n    def sell_indicator_space() -> List[Dimension]:\n        \"\"\"\n        Create a sell indicator space\n        \"\"\"\n\n    @staticmethod\n    @abstractmethod\n    def generate_roi_table(params: Dict) -> Dict[int, float]:\n        \"\"\"\n        Create an roi table\n        \"\"\"\n\n    @staticmethod\n    @abstractmethod\n    def stoploss_space() -> List[Dimension]:\n        \"\"\"\n        Create a stoploss space\n        \"\"\"\n\n    @staticmethod\n    @abstractmethod\n    def roi_space() -> List[Dimension]:\n        \"\"\"\n        Create a roi space\n        \"\"\"\n", "path": "freqtrade/optimize/hyperopt_interface.py"}, {"content": "# pragma pylint: disable=attribute-defined-outside-init\n\n\"\"\"\nThis module load custom hyperopts\n\"\"\"\nimport logging\nfrom pathlib import Path\nfrom typing import Optional, Dict\n\nfrom freqtrade.constants import DEFAULT_HYPEROPT\nfrom freqtrade.optimize.hyperopt_interface import IHyperOpt\nfrom freqtrade.resolvers import IResolver\n\nlogger = logging.getLogger(__name__)\n\n\nclass HyperOptResolver(IResolver):\n    \"\"\"\n    This class contains all the logic to load custom hyperopt class\n    \"\"\"\n\n    __slots__ = ['hyperopt']\n\n    def __init__(self, config: Optional[Dict] = None) -> None:\n        \"\"\"\n        Load the custom class from config parameter\n        :param config: configuration dictionary or None\n        \"\"\"\n        config = config or {}\n\n        # Verify the hyperopt is in the configuration, otherwise fallback to the default hyperopt\n        hyperopt_name = config.get('hyperopt') or DEFAULT_HYPEROPT\n        self.hyperopt = self._load_hyperopt(hyperopt_name, extra_dir=config.get('hyperopt_path'))\n\n        if not hasattr(self.hyperopt, 'populate_buy_trend'):\n            logger.warning(\"Custom Hyperopt does not provide populate_buy_trend. \"\n                           \"Using populate_buy_trend from DefaultStrategy.\")\n        if not hasattr(self.hyperopt, 'populate_sell_trend'):\n            logger.warning(\"Custom Hyperopt does not provide populate_sell_trend. \"\n                           \"Using populate_sell_trend from DefaultStrategy.\")\n\n    def _load_hyperopt(\n            self, hyperopt_name: str, extra_dir: Optional[str] = None) -> IHyperOpt:\n        \"\"\"\n        Search and loads the specified hyperopt.\n        :param hyperopt_name: name of the module to import\n        :param extra_dir: additional directory to search for the given hyperopt\n        :return: HyperOpt instance or None\n        \"\"\"\n        current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()\n\n        abs_paths = [\n            current_path.parent.parent.joinpath('user_data/hyperopts'),\n            current_path,\n        ]\n\n        if extra_dir:\n            # Add extra hyperopt directory on top of search paths\n            abs_paths.insert(0, Path(extra_dir))\n\n        for _path in abs_paths:\n            try:\n                hyperopt = self._search_object(directory=_path, object_type=IHyperOpt,\n                                               object_name=hyperopt_name)\n                if hyperopt:\n                    logger.info(\"Using resolved hyperopt %s from '%s'\", hyperopt_name, _path)\n                    return hyperopt\n            except FileNotFoundError:\n                logger.warning('Path \"%s\" does not exist', _path.relative_to(Path.cwd()))\n\n        raise ImportError(\n            \"Impossible to load Hyperopt '{}'. This class does not exist\"\n            \" or contains Python code errors\".format(hyperopt_name)\n        )\n", "path": "freqtrade/resolvers/hyperopt_resolver.py"}]}