Merge pull request animator#536 from Santhosh-Siddhardha/main

animator · web-flow · commit ed4b85e9a760 · 2024-05-24T21:31:19.000+05:30
Added Saving Arrays into Files section under NumPy module
diff --git a/contrib/numpy/index.md b/contrib/numpy/index.md
@@ -6,3 +6,4 @@
 - [Basic Mathematics](basic_math.md)
 - [Operations on Arrays in NumPy](operations-on-arrays.md)
 - [Loading Arrays from Files](loading_arrays_from_files.md)
+- [Saving Numpy Arrays into FIles](saving_numpy_arrays_to_files.md)
diff --git a/contrib/numpy/saving_numpy_arrays_to_files.md b/contrib/numpy/saving_numpy_arrays_to_files.md
@@ -0,0 +1,126 @@
+# Saving NumPy Arrays to Files
+
+- Saving arrays in NumPy is important due to its efficiency in storage and speed, maintaining data integrity and precision, and offering convenience and interoperability.
+- NumPy provides several methods to save arrays efficiently, either in binary or text formats.
+- The primary methods are `save`, `savez`, and `savetxt`.
+
+### 1. numpy.save():
+
+The `np.save` function saves a single NumPy array to a binary file with a `.npy` extension. This format is efficient and preserves the array's data type and shape.
+
+#### Syntax :
+
+  ```python
+  numpy.save(file, arr, allow_pickle=True, fix_imports=True)
+  ```
+- **file** : Name of the file.
+- **arr** : Array to be saved.
+- **allow_pickle** : This is an Optional parameter, Allows saving object arrays using Python pickles.(By Default True)
+- **fix_imports** : This is an Optional parameter, Fixes issues for Python 2 to Python 3 compatibility.(By Default True)
+
+#### Example :
+
+```python
+import numpy as np
+
+arr = np.array([1,2,3,4,5])
+np.save("example.npy",arr) #saves arr into example.npy file in binary format
+```
+
+Inorder to load the array from example.npy
+
+```python
+arr1 = np.load("example.npy")
+print(arr1)
+```
+**Output** :
+  
+```python
+[1,2,3,4,5]
+```
+### 2. numpy.savez():
+
+The `np.savez` function saves multiple NumPy arrays into a single file with a `.npz` extension. Each array is stored with a unique name.
+
+#### Syntax :
+
+  ```python
+numpy.savez(file, *args, **kwds)
+  ```
+- **file** : Name of the file.
+- **args** : Arrays to be saved.( If arrays are unnamed, they are stored with default names like arr_0, arr_1, etc.)
+- **kwds** : Named arrays to be saved.
+
+#### Example :
+
+```python
+import numpy as np
+
+arr1 = np.array([1,2,3,4,5])
+arr2 = np.array(['a','b','c','d'])
+arr3 = np.array([1.2,3.4,5])
+np.savez('example.npz', a1=arr1, a2=arr2, a3 = arr3) #saves arrays in npz format
+
+```
+
+Inorder to load the array from example.npz
+
+```python
+
+arr = np.load('example.npz')
+print(arr['a1'])
+print(arr['a2'])
+print(arr['a3'])
+
+```
+**Output** :
+```python
+[1 2 3 4 5]
+['a' 'b' 'c' 'd']
+[1.2 3.4 5. ]
+```
+
+### 3. np.savetxt()
+
+The `np.savetxt` function saves a NumPy array to a text file, such as `.txt` or `.csv`. This format is human-readable and can be used for interoperability with other tools.
+
+#### Syntax :
+
+  ```python
+numpy.savetxt(fname, X, delimiter=' ', newline='\n', header='', footer='', encoding=None)
+  ```
+- **fname** : Name of the file.
+- **X** : Array to be saved.
+- **delimiter** : It is a Optional parameter,This is a character or string that is used to separate columns.(By Default it is " ")
+- **newline** : It is a Optional parameter, Character for seperating lines.(By Default it is "\n")
+- **header** : It is a Optional parameter, String that is written at beginning of the file.
+- **footer** : It is a Optional parameter, String that is written at ending of the file.
+- **encoding** : It is a Optional parameter, Encoding of the output file. (By Default it is None)
+
+#### Example :
+
+```python
+import numpy as np
+
+arr = np.array([1.1,2.2,3,4.4,5])
+np.savetxt("example.txt",arr) #saves the array in example.txt
+
+```
+
+Inorder to load the array from example.txt
+
+```python
+
+arr1 = np.loadtxt("example.txt")
+print(arr1)
+
+```
+**Output** :
+```python
+[1.1 2.2 3. 4.4 5. ]
+```
+
+
+By using these methods, you can efficiently save and load NumPy arrays in various formats suitable for your needs.
+
+
