some not important changes and an organization md file

MCDAQcontrolsignals.py

@@ -4,7 +4,11 @@ Here the class of control signals are created. There are two types: analog and d
 """
 import sys
 if sys.platform == 'linux':
-    from drivers.ADoutputs_linux import daq_AO, daq_DO
+    try:
+        from drivers.ADoutputs_linux import daq_AO, daq_DO
+    except Exception:
+        print('No MCCDAQ found')
+        from drivers.ADoutputs import daq_AO, daq_DO    
 else:
     from drivers.ADoutputs import daq_AO, daq_DO
 from PyQt5 import QtCore

controlGui.py

@@ -8,7 +8,7 @@ controlled from this Gui. It is more for searching and exploring the paremeters.
 """
 import sys
 from PyQt5 import QtGui, QtCore
-import qdarkstyle
+#import qdarkstyle
 import os
 from PyQt5.QtWidgets import QLabel
 

main.py

     
 from PyQt5 import QtGui, QtCore
-from drivers.andorzyla import AndorZyla
-#from drivers.dummyAndor import AndorZyla
+#from drivers.andorzyla import AndorZyla
+from drivers.dummyAndor import AndorZyla
 
 from cameraGui import CameraGuiMainWindow
 from zylaCameraWorker import CameraWorker
@@ -52,13 +52,13 @@ if __name__ == "__main__":
         do.moveToThread(mcDAQthread)
 
 
-    myGuiMainWindow = CameraGuiMainWindow()
+    cameraMainWindow = CameraGuiMainWindow()
     cameraWorker = CameraWorker(camera)
 
     cameraThread = QtCore.QThread()
     cameraWorker.moveToThread(cameraThread)
 
-    cameraWorker.make_connections(myGuiMainWindow)
+    cameraWorker.make_connections(cameraMainWindow)
     myGuiMainWindow.make_connections(cameraWorker)
 
     cameraThread.start()

organization.md

+# Architecture
+
+The code is organized in three layers:
+- Drivers: talk to the instruments and handle all the specifics exposing a, hopefully, user friendly API. 
+- Backend: Organize more complex actions, that might or might not involve instruments.
+- Frontend: Provide a user interface. It should not be required to work.
+
+
+**Basic blocks**
+
+The basic blocks are the following:
+
+ - Camera frontend and backend: cameraGUi and zylaCameraWorker
+ - MCCDAQ frontend and backend: controlGui and MCDAQcontrolsignals
+
+ There is and aditional block, which is the measurement block. Its frontend lies in the camera frontend, and its backend lies in the camera backend. From there, it also controls the daq control signals. 
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readme.md

 # Control App
 
 
-## Getting Started
+## ¿What is my purpose?
 
-These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
+This application should enable to control, for now, a measurement computing daq and a zyla camera. 
 
 ## Requisites
 
+These requisites are recommended to be installed after creating the anaconda environment described below. 
+
 In windows, the mcculw package is needed. You can install it from https://pypi.org/project/mcculw/, where you need to follow some simple instrucions. After following those, open the installed 
 program Instalcal at least once for getting some neccesary updates.  
 
 In Linux, you will need the mccdaq package. You can install it from https://pypi.org/project/uldaq/. There you should go to the github repository and follow the build instructions. 
-Also, check requisites.txt, and install the python packages listed there. This can be usually done via PIP. 
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+Also, check requisites.txt, and install the python packages listed there. This can be usually done via PIP. 
+
+## Getting started
+
+
+You can run the Software directly from the repo. First install all
+the dependencies in a conda environment:
+
+    $ conda create -n controlApp python=3.6 
+    $ conda activate controlApp
+    $ conda install numpy pyqt pyqtgraph matplotlib
+    
+Then run it simply by calling main in that environment:
+
+    $ python main.py  
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