Here are the examples of the python api numpy.random.randint taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.
145 Examples
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets
3
View Complete Implementation : sequence.py
Copyright MIT License
Author : hello-sea
Copyright MIT License
Author : hello-sea
def __gesatem__(self, index):
if self.shuffle:
rows = np.random.randint(
self.start_index, self.end_index, size=self.batch_size)
else:
i = self.start_index + self.batch_size * self.stride * index
rows = np.arange(i, min(i + self.batch_size *
self.stride, self.end_index), self.stride)
samples, targets = self._empty_batch(len(rows))
for j, row in enumerate(rows):
indices = range(rows[j] - self.length, rows[j], self.sampling_rate)
samples[j] = self.data[indices]
targets[j] = self.targets[rows[j]]
if self.reverse:
return samples[:, ::-1, ...], targets
return samples, targets