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Merge pull request #724 from PowerGridModel/fix/quick-start
fix quick start
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docs/quickstart.md

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@@ -34,7 +34,6 @@ and there are no build errors, segmentation violations, undefined symbols, etc.
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The function should be imported and called by a user by running following commands:
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```python
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from power_grid_model.utils import self_test
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self_test()
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```
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@@ -152,18 +151,7 @@ To validate the `input_data` and `update_data` for valid values, use {py:class}`
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## Batch Data
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Optionally, we can add batch scenarios using the `update_data` argument.
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The code below initializes a symmetric load update array with a shape of `(5, 4)`. This is in the form of $\text{number of batches} \times \text{number of components}$.
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The `update_data` is an optional argument to the {py:class}`power_grid_model.PowerGridModel` object or the calculation functions.
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```python
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from power_grid_model import initialize_array
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sym_load_update = initialize_array('update', 'sym_load', (5, 4))
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# --- Add other sym_load attributes ---
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update_data = {
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"sym_load": sym_load_update
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}
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model.calculate_power_flow(update_data=update_data)
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```
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You can calculate a (large) number of scenarios using one command and even in parallel threading.
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This is what makes Power Grid Model a powerful calculation engine.
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You need to create a batch update dataset and put it in the `update_data` argument of `calculate_power_flow`.
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Please refer to [Power Flow Example](examples/Power%20Flow%20Example.ipynb) for a detailed tutorial about how to execute batch calculations.

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