Cleaned up alpaca.py

Author: twhoekstra

ports/rp2/modules/alpaca.py

@@ -1,134 +1,22 @@
 """Module for using the Raspberry Pi Pico in the course NB2211 Electronic Instrumentation
     By: Thijmen de Wolf & Thijn Hoekstra
 """
-#       ___       __      .______      ___       ______     ___
-#      /   \     |  |     |   _  \    /   \     /      |   /   \
-#     /  ^  \    |  |     |  |_)  |  /  ^  \   |  ,----'  /  ^  \
-#    /  /_\  \   |  |     |   ___/  /  /_\  \  |  |      /  /_\  \
-#   /  _____  \  |  `----.|  |     /  _____  \ |  `----./  _____  \
-#  /__/     \__\ |_______|| _|    /__/     \__\ \______/__/     \__\
-version = '0.8'  # Module version so students can retrieve their version for debugging
+
+import os
+
+_VERSION = '0.8'  # Module version so students can retrieve their version
 
 
 def get_version():
     """Retrieve the version of the `nb2211` module.
     """
-    print('You are currently running version ' + version + ' of alpaca.py')
-
-def clear_disk(self):
-    import os
-    will_clear = False
+    print('You are currently running version ' + _VERSION + ' of alpaca.py')
 
-    utime.sleep(5)
 
+def clear_disk(self):
     print('Remove files...')
-    for file in os.ilistdir():
+    for file in os.listdir():
         os.remove(file[0])
         print('Removed ', file[0])
 
     print('Done.')
-
-
-def __is_2D_array(self, object):
-    result = False
-    if type(object) is list:
-        if type(object[0]) is list:
-            result = True
-    return result
-
-def __is_scalar(self, object):
-    return type(object) is float or type(object) is int
-
-def store_data(self, filename, parameters=None, samples=None):
-    """Stores samples taken during a measurement as a text file on the memory of the Raspberry Pi Pico.
-
-    The data is stored in such a way that it is relatively easy to read later on. It is possible to store
-    just the samples, but it is also possible to add information about the measurement (or parameters) to
-    the text file.
-
-    Parameters
-    ----------
-    filename : str
-        Filename of text file in which to store data. Should include the file extension, e.g. `data.txt`.
-    parameters : int or float or list, optional
-        Information about the measurement, e.g. a single measurement parameter such as frequency stored as a float
-        or multiple parameters stored as a list.
-    samples : list
-        A list of the samples taken during the measurment. Note that this can also be a nested list, e.g. a 2D array.
-
-
-    Notes
-    -----
-    Stores the file as `filename` to the root directory of the Raspberry Pi Pico. Importing the data is best done using the `numpy` package. For example:
-
-
-    Examples
-    --------
-    >>> pico = nb2211.Pico()
-    >>> pico.store_data('data.txt', samples = [1,2,3]) # Store only three samples
-    >>> pico.store_data('data.txt', 24.0, [600, 601, 602]) # Store three samples taken at a frequency of 24.0 Hertz.
-    >>> pico.store_data('temperatures.txt', [3600, 12], samples = temperature_list) # Store list 'temperature_list' along with parameters, e.g. 3600 samples taken over the course of 12 days.
-    >>> pico.store_data('data.txt', parameters = 10, samples = 3) # Store single parameter and single sample.
-    >>> # Storing data and saving data using `numpy`.
-    >>> # Saving data
-    >>> from nb2211 import Pico
-    >>> pico = Pico()
-    >>> frequencies = [10, 11, 12]
-    >>> data_2D = [[1, 2, 3, 4, 5, 6],
-    >>>            [7, 8, 9, 10, 11, 12]]
-    >>> pico.store_data('data.txt', parameters=frequencies, samples=data_2D) # With parameters
-    >>> #
-    >>> # Retrieving data
-    >>> import numpy as np
-    >>> parameters_stored = True
-    >>> data_2D = np.loadtxt('data.txt', skiprows = parameters_stored)
-    >>> frequencies = np.loadtxt('data.txt', max_rows = parameters_stored)
-
-    """
-    file = open(filename, 'w')
-
-    if parameters is not None:
-        # Write parameters
-        if self.__is_scalar(parameters):
-            file.write(str(parameters) + '\n')
-
-        elif self.__is_2D_array(parameters):
-            raise TypeError('Error exporting parameters. Can only export 1D arrays')
-
-        elif type(parameters) is list:
-            for item in parameters:
-                file.write(str(item) + ' ')
-            file.write('\n')
-
-        else:
-            file.close()
-            raise TypeError('Please input parameters as either a scalar value or a list.')
-
-    if isinstance(samples, (list, tuple, np.ndarray)):
-        for ii, item in enumerate(samples):
-            if isinstance(item, (list, tuple, np.ndarray)):
-                samples[ii] = list(np.array(item).flatten())
-
-        samples = list(samples)
-
-    # ~~~~~~~~~~~~~~~~~~~ Write samples
-    if self.__is_scalar(samples):
-        file.write(str(samples) + '\n')
-
-    elif self.__is_2D_array(samples):
-        for row in samples:
-            for column in row:
-                file.write(str(column) + ' ')
-            file.write('\n')
-
-    elif type(samples) is list:
-        for item in samples:
-            file.write(str(item) + ' ')
-        file.write('\n')
-
-    else:
-        file.close()
-        raise TypeError('Please input parameters as either a scalar value or a (nested) list.')
-
-    file.flush()
-    file.close()