elaOnMars · April 4, 2021 20:42 · Mar 30, 2019
diff --git a/load_multiple_files_in_numpy.md b/load_multiple_files_in_numpy.md
@@ -0,0 +1,96 @@
+# Load multiple files using numpy.loadtxt
+
+## A functional approach
+```python
+#!/usr/bin/env python
+"""
+The examples below show how to load multiple files via numpy loadtext.
+
+Sorting the files may or may not be necessary depending on your problem.
+
+Given that loading multiple files for a single calculation seems to be a common
+task, numpy should have a better approach somewhere in its library. 
+
+This is the best I could do with a little research.
+"""
+import fileinput
+import glob
+import numpy as np
+
+
+def oneliner(filename_glob_pattern):
+    array = np.loadtxt(fileinput.input(sorted(glob.glob(filename_glob_pattern))))
+
+
+def broken_out_for_pedagogical_purposes(filename_glob_pattern):
+    list_all_matching_files = glob.glob(filename_glob_pattern)
+    sorted_list_of_filenames = sorted(list_all_matching_files)
+    concatenate_files_into_single_input = fileinput.input(sorted_list_of_filenames)
+    single_array_of_all_files = np.loadtxt(concatenate_files_into_single_input)
+    return single_array_of_all_files
+
+
+if __name__ == "__main__":
+    array = oneliner("flinakT940n100UF4-Charges.dat*")
+    print("The whole array has {} rows".format(len(array)))
+```
+References and further reading:
+- [glob](https://docs.python.org/2/library/glob.html?highlight=glob#glob.glob) selects files by unix patterns. Asterisks are patterns for zero or more characters, question marks and square brackets also have special meanings.
+- [sorted](https://docs.python.org/2/library/functions.html#sorted) is a builtin function. You do not need to import it: it's always available.
+- [fileinput](https://docs.python.org/2/library/fileinput.html?highlight=fileinput#module-fileinput) concatenates multiple files together into a single iterator
+- [numpy.loadtxt](https://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html) It's always worth checking the documentation to see whether something is already built in. 
+## Some other approaches
+
+```python
+
+"""
+You have to know the number of files for this approach.
+This may be more comfortable for those more familiar with C.
+"""
+import numpy as np
+
+
+def iterative_approach(filename_pattern, number_of_files):
+    """
+    This approach may be more comfortable to those coming from a language like C.
+    """
+    list_of_filenames = []
+    for number in range(1, number_of_files + 1):
+        list_of_filenames.append(filename_pattern % number)
+    list_of_arrays = []
+    for filename in list_of_filenames:
+        list_of_arrays.append(np.loadtxt(filename))
+    final_array = np.concatenate(arrays)
+    return final_array
+
+
+def using_string_formatting(filename_pattern, number_of_files):
+    """
+    String formatting & list comprehensions both can help condense the code in iterative_approach.
+    
+    String formatting replaces a {} with the format arguments.
+    List comprehensions create a list by [something for varfoo in iterator]; 
+    all the resulting somethings are elements of the list.
+    """
+    filename_list = ["{}{}".format(filename_pattern, number) 
+                     for number in range(1, number_of_files + 1)]
+    return [np.loadtxt(filename) for filename in filename_list]
+
+
+def test_iterative_approach():
+    array = iterative_approach("flinakT940n100UF4-Charges.dat%s", 23)
+    print("The whole array has %d rows" % len(array))
+
+
+def test_using_string_formating():
+    array = using_string_formatting("flinakT940n100UF4-Charges.dat", 23)
+    print("The whole array has {} rows".format(len(array)))
+
+```
+
+References and further reading:
+- [PEP 3101](https://www.python.org/dev/peps/pep-3101/) is a gentle introduction to the string formatting "mini language."
+- [The library format specification](https://docs.python.org/2/library/string.html#format-specification-mini-language) is a a quick reference.
+- [The range](https://docs.python.org/2/library/functions.html#range) function is a built in (no need to import.) There are about forty such functions.
+- [Numpy examples](https://swcarpentry.github.io/python-novice-inflammation/04-files/) illustrating some real world uses.
+- [sorted](https://stackoverflow.com/a/6774404) is another built in function that is worth learning how to use.