change sample_

langflow-ai · Jul 1, 2022 · d8e2c3c · d8e2c3c
1 parent 7058b18
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diff --git a/data/cnn_dataset/Processed_DJI.csv b/data/cnn_dataset/Processed_DJI.csv
diff --git a/data/cnn_dataset/Processed_NASDAQ.csv b/data/cnn_dataset/Processed_NASDAQ.csv
diff --git a/data/cnn_dataset/Processed_NYSE.csv b/data/cnn_dataset/Processed_NYSE.csv
diff --git a/data/cnn_dataset/Processed_RUSSELL.csv b/data/cnn_dataset/Processed_RUSSELL.csv
diff --git a/data/cnn_dataset/Processed_SP.csv b/data/cnn_dataset/Processed_SP.csv
diff --git a/notebooks/msft_analysis.1.ipynb b/notebooks/msft_analysis.1.ipynb
diff --git a/notebooks/tf_processed_data.csv b/notebooks/tf_processed_data.csv
diff --git a/notebooks/tf_time_series.ipynb b/notebooks/tf_time_series.ipynb
diff --git a/notebooks/tf_tutorial.ipynb b/notebooks/tf_tutorial.ipynb
diff --git a/src/wavy/panel.py b/src/wavy/panel.py
@@ -886,31 +886,32 @@ def tail(self, n: int = 5):
  """
  return self[-n:]
 
- def sample(self, samples: int = 5, how: str = "first"):
+ def sample_(self, samples: int = 5, how: str = "random"):
  """
  Sample panel returning a subset of frames.
 
  Args:
  samples (int): Number of samples to keep
- how (str): Resempling how, 'first', 'last', 'spaced' or 'random'
+ how (str): Sampling method, 'spaced' or 'random'
 
  Returns:
  ``Panel``: Result of sample function.
  """
-
- if how == "first":
- return self[:samples]
- elif how == "last":
- return self[-samples:]
- elif how == "random":
- indexes = np.random.choice(len(self.frames), samples, replace=False)
- indexes = sorted(indexes)
- return self[indexes]
- elif how == "spaced":
- indexes = np.linspace(
- 0, len(self.frames), samples, dtype=int, endpoint=False
- )
- return self[indexes]
+ # ! Needs to check if panel has train, test and val split first
+ # if panel.is_split():
+ # do something else
+ # ! Should sample train, val and test separately
+
+ # ! Better not to use below and focus on ids
+ # if how == "random":
+ # indexes = np.random.choice(len(self.frames), samples, replace=False)
+ # indexes = sorted(indexes)
+ # return self[indexes]
+ # elif how == "spaced":
+ # indexes = np.linspace(
+ # 0, len(self.frames), samples, dtype=int, endpoint=False
+ # )
+ # return self[indexes]
 
  @property
  def train(self):

diff --git a/tutorials/mlm_cnn.ipynb b/tutorials/mlm_cnn.ipynb