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Computing, data-analytics and big-data solutions are proliferating today. These revolutionary technologies and the services these enable bring changes that touch the very lives of the people, especially the socially excluded and the environment. How far are we from a just society when digital platforms are operated by only few oligopolies? How we can truly ensure the fairness, transparency, openness and sustainability in our digital ecosystems?
Digital technologies enable nowadays, for example, the pursuit of completely different goals: from the provision of healthcare services or education to the reduction of energy consumption and greenhouse gas emissions. Comparing with the 20th Century conditions, we have a new “digital age” with a radically changed landscape and a renewed definition of the social and the economic order.
We want to introduce to you current and future challenges of these technologies. The society of the 21st century needs to be an intelligent society, where the individual can share his data, his voice, his view, his experiences. The individual wants to be able to take care of his life and be well coordinated with the developed and the developing world.Q:
Efficient way of updating numpy array with numpy slicing
I'm looking for an efficient way of updating an numpy array.
My problem is that I have a huge array (800 x 1048576 x 8192) and I have to slice and save only specific indices into another array.
This is what I'm doing right now:
def initialize_data(self, data):
This function is called to create a new array
data: dictioanry of shape (800, 1048576, 8192)
# Initialize with the data which is created earlier
self.data = data
# Create an empty array with the requested shape
self.data_vec = np.zeros([800, 1048576, 8192])
def update_data(self, data):
This function is called to update the data array
data: dictioanry of shape (800, 10 0b46394aab