import os
import numpy as np
import crepe


def test_sweep():
    # this data contains a sine sweep
    file = os.path.join(os.path.dirname(__file__), 'sweep.wav')

    model = crepe.build_and_load_model()
    crepe.process_file(model, file)
    f0_file = os.path.join(os.path.dirname(__file__), 'sweep.f0.csv')

    result = np.loadtxt(f0_file, delimiter=',')

    # the result should be confident enough about the presence of pitch in every
    # frame
    assert np.mean(result[:, 2] > 0.5) > 0.99

    # the frequencies should be linear
    assert np.corrcoef(result[:, 1]) > 0.99

import os
import numpy as np
import crepe


def test_sweep():
    # this data contains a sine sweep
    file = os.path.join(os.path.dirname(__file__), 'sweep.wav')

    model = crepe.build_and_load_model()
    crepe.process_file(model, file)
    f0_file = os.path.join(os.path.dirname(__file__), 'sweep.f0.csv')

    result = np.loadtxt(f0_file, delimiter=',', skiprows=1)

    # the result should be confident enough about the presence of pitch in every
    # frame
    assert np.mean(result[:, 2] > 0.5) > 0.99

    # the frequencies should be linear
    assert np.corrcoef(result[:, 1]) > 0.99

Fix bug in unit test (ignore header row in output csv file)
Fix bug in unit test (ignore header row in output csv file)

  import os
  import numpy as np
  import crepe
  
  
  def test_sweep():
      # this data contains a sine sweep
      file = os.path.join(os.path.dirname(__file__), 'sweep.wav')
  
      model = crepe.build_and_load_model()
      crepe.process_file(model, file)
      f0_file = os.path.join(os.path.dirname(__file__), 'sweep.f0.csv')
  
-     result = np.loadtxt(f0_file, delimiter=',')
+     result = np.loadtxt(f0_file, delimiter=',', skiprows=1)
  
      # the result should be confident enough about the presence of pitch in every
      # frame
      assert np.mean(result[:, 2] > 0.5) > 0.99
  
      # the frequencies should be linear
      assert np.corrcoef(result[:, 1]) > 0.99
  
Fix bug in unit test (ignore header row in output csv file)
## Code Before:
import os
import numpy as np
import crepe


def test_sweep():
    # this data contains a sine sweep
    file = os.path.join(os.path.dirname(__file__), 'sweep.wav')

    model = crepe.build_and_load_model()
    crepe.process_file(model, file)
    f0_file = os.path.join(os.path.dirname(__file__), 'sweep.f0.csv')

    result = np.loadtxt(f0_file, delimiter=',')

    # the result should be confident enough about the presence of pitch in every
    # frame
    assert np.mean(result[:, 2] > 0.5) > 0.99

    # the frequencies should be linear
    assert np.corrcoef(result[:, 1]) > 0.99

## Instruction:
Fix bug in unit test (ignore header row in output csv file)
## Code After:
import os
import numpy as np
import crepe


def test_sweep():
    # this data contains a sine sweep
    file = os.path.join(os.path.dirname(__file__), 'sweep.wav')

    model = crepe.build_and_load_model()
    crepe.process_file(model, file)
    f0_file = os.path.join(os.path.dirname(__file__), 'sweep.f0.csv')

    result = np.loadtxt(f0_file, delimiter=',', skiprows=1)

    # the result should be confident enough about the presence of pitch in every
    # frame
    assert np.mean(result[:, 2] > 0.5) > 0.99

    # the frequencies should be linear
    assert np.corrcoef(result[:, 1]) > 0.99
