Move CF scripts to repo

src/Basic_Path/main.py

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+# author: Axel Fischer
+# created at: 07.05.2019
+# company/institute: sweep-me.net
+
+import os
+
+class Main():
+
+    # please define variables and units as returned by the function 'main'
+    variables = ["Folder", "File name", "File extension", "File exists"]
+    units = ["", "", "", ""]
+
+    # the function 'main' will be loaded as the function that can be seen inside the module
+    # the arguments of the function tell SweepMe! which kind of data you expect and what are the default values
+    # SweepMe! will generate the input of the graphical user interface accordingly
+    def main(   
+            self,           
+            # must the first argument and should not be removed
+
+            Path_to_evaluate = (), 
+            # a tuple let you choose from all available SweepMe! values from a ComboBox
+
+
+            ): # angry? If you find a bug or need support, please write to [email protected]
+
+
+        ''' 
+        <h2>Path evaluation</h2>
+        returns folder, file name, file extension and whether files exists<br>
+        ''' 
+
+        existing = os.path.exists(Path_to_evaluate[0])        
+
+        if existing:
+
+            file_name, ext =  os.path.splitext(Path_to_evaluate[0])
+
+            file_name = os.path.basename(file_name)
+
+            folder = os.path.dirname(Path_to_evaluate[0])
+
+
+        else:
+
+            folder, file_name, ext = False, False, False
+
+
+        # ... and return your result according to 'variables' and 'units' defined at the beginning of this file
+        return folder, file_name, ext, existing
+

src/Basic_Print/main.py

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+# author: Axel Fischer
+# created at: 27.04.2019
+# company/institute: sweep-me.net
+
+
+class Main():
+
+    def main(self, Data = ()): 
+
+        ''' 
+        <h2>Print</h2>
+        print the selected data to the Debug console (F2)<br>
+        '''
+
+        print("Print:", Data[0])

src/Basic_RegEx/main.py

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+# author: Axel Fischer
+# created at: 27.04.2019
+# company/institute: sweep-me.net
+
+import re
+
+class Main():
+
+    # please define variables and units as returned by the function 'main'
+    variables = ["Match"]
+    units = [""]
+
+    # the function 'main' will be loaded as the function that can be seen inside the module
+    # the arguments of the function tell SweepMe! which kind of data you expect and what are the default values
+    # SweepMe! will generate the input of the graphical user interface accordingly
+    def main(   
+            self,           
+            # must the first argument and should not be removed
+
+            String_to_evaluate = (), 
+            # a tuple let you choose from all available SweepMe! values from a ComboBox
+
+            Search_pattern = "", 
+            # an integer let you insert an integer
+
+            #Return_type = ["String", "Integer", "Float"], 
+            # A list of strings let you choose one of the items in a ComboBox
+
+            ): # angry? If you find a bug or need support, please write to [email protected]
+
+
+        ''' 
+        <h2>Regular expression</h2>
+        Search for a sequence of characters in a string using regular expressions<br>
+
+        <h4>Usage:</h4>
+        Use as 'String_to_evaluate' a variable that contains a string.<br>
+        Use as 'Search_pattern' a regular expression pattern.<br>
+        The function returns the first match, otherwise not-a-number (nan).<br>
+        If possible the result is automatically converted to an integer or a float.<br>
+        The function is based on the re module of python.
+        <br>
+        <h4>Examples:</h4>
+        The pattern 'W=([-+]?\d+.d+)nm_' finds a positive or negative float in the string "...W=340.12nm_..." and will return '340.0' as float.<br>
+        The pattern 'W=([-+]?\[0-9]+.[0-9]+)nm_' does the same than the previous example.<br>
+        The pattern 'W=(\d+)nm_' finds a positive integer in the string "...W=340nm_..." and will return '340' as int.<br>
+        The pattern '([A-Z])=' finds a capital letter in the string "...W=340nm_..." and will return 'W' as string.<br>
+        <br>
+        Further help about regular expressions can be found here:<br>
+        <a href="https://docs.python.org/3.6/library/re.html">https://docs.python.org/3.6/library/re.html</a>
+        '''       
+
+        match = re.search(Search_pattern, str(String_to_evaluate[0]))
+
+        try:
+            result = match.group(1)
+
+            try:
+                result = int(result)
+            except:
+                try:
+                    result = float(result)
+                except:
+                    pass
+
+        except:
+            result = float('nan')
+
+
+        # ... and return your result according to 'variables' and 'units' defined at the beginning of this file
+        return result
+

src/CreateAnimation/libs/LICENSE.txt

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+Copyright (c) 2014-2018, imageio developers
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+
+* Redistributions in binary form must reproduce the above copyright notice,
+  this list of conditions and the following disclaimer in the documentation
+  and/or other materials provided with the distribution.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+

src/CreateAnimation/main.py

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+# author: Axel Fischer (sweep-me.net)
+# started: 23.01.19
+
+import numpy as np
+import os
+import pathlib
+
+import FolderManager
+FoMa = FolderManager.FolderManager()
+FolderManager.addFolderToPATH()
+
+import imageio
+
+
+# please defines variables and units as returned by the function 'main'
+variables = ["Path animation"]
+units = [""]
+
+# the function 'main' will be loaded as function
+def main(
+            Pictures = (), # a tuple let you choose SweepMe! values from a ComboBox
+            Duration = 0.1,
+            #Format = ["gif", "avi"],
+
+        ): 
+
+    # just right at the start of the function, you set the help text which will be displayed as description in the GUI
+    ''' 
+        <h2>Animation</h2>
+        <br>
+        create an animation based on a list of files<br>
+        select a variable that stores paths to image files<br>
+    '''
+
+    tempfolder = FoMa.get_path("TEMP")
+
+    images = []
+    for filename in Pictures:
+        images.append(imageio.imread(filename))
+
+    animation_path = tempfolder + os.sep + "temp_Animation.gif"
+
+    imageio.mimsave(animation_path, images, duration = Duration)
+
+    return [animation_path]
+

src/Evaluation_Rectification/main.py

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+# author: Axel Fischer (sweep-me.net)
+# started: 29.08.18
+
+import numpy as np
+import os
+import pathlib
+import math
+
+# please defines variables and units as returned by the function 'main'
+variables = ["Rectification", ""]
+units = ["", ""]
+
+# the function 'main' will be loaded as function
+def main(
+            current = (), # a tuple let you choose SweepMe! values from a ComboBox
+            voltage = (),
+        ): # angry? If you find a bug or need support for another type, please contact us
+
+    # just right at the start of the function, you set the help text which will be displayed as description in the GUI
+    ''' 
+        <h2>Rectification</h2>
+    '''
+
+    # do whatever you want 
+    print("Output of Evaluation example function:")
+    print("data:", current)
+
+    # return values according to 'variables' and 'units' defined at the beginning of this file
+    return [abs(current.max()/current.min()), ""]
+

src/Evaluation_Statistics/main.py

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+# author: Axel Fischer ([email protected])
+# company/institution: SweepMe! GmbH
+# started: 04.10.18
+# revised: 25.01.23
+
+import numpy as np
+
+
+class Main():
+
+    """ 
+    <h2>Simple statistics</h2>
+
+    calculates
+    <ul>
+    <li>mean</li>
+    <li>standard deviation</li>
+    <li>median</li>
+    <li>minimum</li>
+    <li>maximum</li>
+    </ul>
+
+    of a list of values.
+
+    </h3>Parameters</h3>
+    <ul>
+    <li>Data: a list or array of values, or single values, e.g int or float
+    <li>Append: concatenate new values to previous values.</li>
+    <li>Last points: Only keep the given number of points. If empty, all points are used.</li>
+    </ul>
+    """
+
+    variables = ["Mean", "Standard deviation", "Median", "Min", "Max"]
+    units = ["", "", "", "", ""]
+    arguments = {
+        "Data": (),
+        "Append": False,
+        "Last points": "",
+        }
+
+    def configure(self):
+        self.data_all = np.array([])
+
+    def main(self, **kwargs):
+
+        # Handing over arguments
+        new_data = kwargs["Data"]
+        new_data = new_data[np.isfinite(np.array(new_data).flatten())]
+        use_append = kwargs["Append"]
+        last_points = kwargs["Last points"].strip()
+
+        # Preprocessing data
+        if last_points == "":
+            last_points_index = 0  # all points
+        else:
+            last_points_index = -int(last_points)
+
+        if use_append:    
+            self.data_all = np.concatenate((self.data_all, new_data))
+            data = self.data_all[last_points_index:]
+        else:
+            data = new_data[last_points_index:]
+
+        # Statistical evaluation
+        average = np.mean(data)
+        std = np.std(data)
+        median = np.median(data)
+        minimum = min(data)
+        maximum = max(data)
+
+        return [average, std, median, minimum, maximum]
+