Python 3.7.3 : Testing firebase with Python 3.7.3 .

The tutorial for today consists of using the Firebase service with python version 3.7.3 .
As you know Firebase offers multiple free and paid services.
In order to use the Python programming language, we need to use the pip utility to enter the required modules.
If your installation requires other python modules then you will need to install them in the same way.

C:\Python373>pip install firebase-admin
C:\Python373\Scripts>pip install google-cloud-firestore

The next step is to log in with a firebase account and create or use a project with a database.
You must use this link to see your project data and create your JSON configuration file for access.
Here's a screenshot of an old project in another programming language that I used for this tutorial.

At point 1, you will find Project Settings - Service accounts and you will need to use the Generate new private key button.
This will generate a JSON file that we will use in the python script.
Be careful to define the path to the python script file.
At point 2, you will find the database or you will need to create it to use it.
The script I'm going to present has commented on the lines for a better understanding of how to use it.

import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore

# the go-test.json from my project settings 
cred = credentials.Certificate("go-test.json")

# start using firebase python modules 
firebase_admin.initialize_app(cred)

# access the database
database = firestore.client()

# access the collection with limit 
my_ref = database.collection("test").limit(2)

# show the values from database
try:
    docs = my_ref.stream()
    for doc in docs:
         print(u'Doc Data:{}'.format(doc.to_dict()))
except:
    print(u'Missing data')

# result running
#Doc Data:{'nrcrt': 1, 'string_value': 'this is a text'}
#Doc Data:{'name': 'test', 'added': 'just now'}

# add data to database
my_ref_add = database.collection("test")
my_ref_add.add({u'nickname': u'catafest', u'friend': u'Last Ocelot'})

# show the new database values
try:
    docs = my_ref_add.stream()
    for doc in docs:
         print(u'Doc Data:{}'.format(doc.to_dict()))
except:
    print(u'Missing data')

# result running
#Doc Data:{'nrcrt': 1, 'string_value': 'this is a text'}
#Doc Data:{'friend': 'Last Ocelot', 'nickname': 'catafest'}
#Doc Data:{'name': 'test', 'added': 'just now'}

# get just one 
doc = database.collection('test').document('doc_id').get()

# show create time 
print(doc.create_time)

# result running
#seconds: 1556014478
#nanos: 460439000

About psychopy tool.

A good definition for this tool can be found at the Wikipedia website:
2002: PsychoPy was originally written by Peirce as a proof of concept - that a high-level scripting language could generate experimental stimuli in real time (existing solutions, such as Psychtoolbox, had to pre-generate movies or use CLUT animation techniques).
The install of this python module is very simple:

C:\Python373\Scripts>pip install psychopy

Using this command to start this tool:

C:\Python373>psychopy

The tool starts with two graphical interfaces:

• one for Coder area;
• one for the project with an untitled.psyexp;

Let's see one screenshot with this tool:

This open source tool, written in the Python programming language, help you to run a wide range of neuroscience, psychology and psychophysics experiments.
I searched the internet for the capabilities of this tool and the obvious conclusion is a utility for building experiments with a wide range of applicability.
This tool lets you use the pavlovia website, see more:
Pavlovia is a place for the wide community of researchers in the behavioural sciences to run, share, and explore experiments online.
This tool used commonly-used components for linguistic experiments:

1. Text Component (display text on the screen);
2. Sound Component (play sounds);
3. Keyboard Component (receive input from the keyboard);
4. RatingScale Component (collect a numeric rating or a choice from a few alternatives, via the mouse, the keyboard or both);
5. Code Component (insert short pieces of python code into your experiments (e.g. time stamp for the production task);

The easy way is to use the Builder tool to generate a wide range of experiments easily from the Builder using its intuitive, graphical user interface (GUI).
Today I will use the Coder with programming a simple example.
To access demos, you need to create a python script in the Coder area (use File menu - New) then use the Demos from the application menu.
Everything in a PsychoPy experiment needs a unique name.
The name must contain only letters, numbers and underscores and not contain spaces, punctuation or mathematical symbols.
This tool saves several data files: a Microsoft Excel (spreadsheet) file, a psydat file, and a log file.
The example I used today for this tutorial is how to import from a CSV file named colors_001.csv and used with psychopy python module to create stimuli:

3.3;"red"
1.1;"green"
4.4;"red"
2.2;"green"

This python script named colors.py I used to import the CSV file and use it:

from psychopy import core, visual, event
import csv
  
## Setup section, read experiment variables from file
win = visual.Window([400,300], monitor="testMonitor", units="cm", fullscr=False)
stimuli = []
datafile = open("colors_001.csv", "r",encoding="utf8")
reader = csv.reader(datafile, delimiter=";")
for row in reader:
    if len(row)==2:         # ignore empty and incomplete lines
        size = float(row[0])  # the first element in the row converted to a floating point number
        color = row[1]        # the second element in the row
        stimulus = visual.Rect(win, width=size, height=size)
        stimulus.fillColor = color
        stimuli.append(stimulus)
datafile.close()
  
## Experiment Section, use experiment variables here
for stimulus in stimuli:
    stimulus.draw()
    win.flip()
    core.wait(1.000)

## Closing Section
win.close()
core.quit()

The result of this script will show you four squares colored by the CSV file.
If you don't like to use the Builder or Coder areas, then you can simply use the python:

C:\Python373>python.exe
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD64)]
 on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> from psychopy import visual, core
pygame 1.9.5
Hello from the pygame community. https://www.pygame.org/contribute.html
>>> win = visual.Window()
>>> msg = visual.TextStim(win, text=u"Hello python users!")
>>> msg.draw()
>>> win.flip()
47.541564770566765

The output will be a window with a text message.

Update python modules of 3.73 version.

Today we tested an older tool with the new version of python 3.7.3.
This is a tool that will help you update your python modules.
Here's how to install:

C:\Python373\Scripts>pip install pip-review
Collecting pip-review
...
Requirement already satisfied: pyparsing>=2.0.2 in c:\python373\lib\site-package
s (from packaging->pip-review) (2.4.0)
Installing collected packages: packaging, pip-review
Successfully installed packaging-19.0 pip-review-1.0

Here is the complete overview of the options.

C:\Python373\Scripts>pip-review -h
usage: pip-review [-h] [--verbose] [--raw] [--interactive] [--auto]

Keeps your Python packages fresh.

optional arguments:
  -h, --help         show this help message and exit
  --verbose, -v      Show more output
  --raw, -r          Print raw lines (suitable for passing to pip install)
  --interactive, -i  Ask interactively to install updates
  --auto, -a         Automatically install every update found

Unrecognised arguments will be forwarded to pip list --outdated, so you can
pass things such as --user, --pre and --timeout and they will do exactly what
you expect. See pip list -h for a full overview of the options.

To update all python modules you can use:

C:\Python373\Scripts>pip-review --auto

To run interactively, you can ask to upgrade for each package:

C:\Python373\Scripts>pip-review --interactive

Using the ORB feature from OpenCV python module.

Today I will show you a simple script using the ORB (oriented BRIEF), see C++ documentation / OpenCV.
The algorithm uses FAST in pyramids to detect stable keypoints, selects the strongest features using FAST or Harris response, finds their orientation using first-order moments and computes the descriptors using BRIEF (where the coordinates of random point pairs (or k-tuples) are rotated according to the measured orientation).
One good feature of ORB is the is rotation invariant and resistant to noise.
The ORB descriptor use the Center of the mass of the patch of the Moment (sum of x,y), Centroid (the result of the matrix of all moment) and Orientation ( the atan2 of moment one and two).
One good article about ORB can be found here.
Let's see the script code of this python example:

import cv2
import numpy as np 

image_1 = cv2.imread("1.png", cv2.IMREAD_GRAYSCALE)
image_2 = cv2.imread("2.png", cv2.IMREAD_GRAYSCALE)

orb = cv2.ORB_create()
kp1, des1 = orb.detectAndCompute(image_1,None)
kp2, des2 = orb.detectAndCompute(image_2,None)

bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
matches = bf.match(des1, des2)
matches = sorted(matches, key = lambda x:x.distance)

matching_result = cv2.drawMatches(image_1, kp1, image_2, kp2, matches[:150], None, flags=2)

cv2.imshow("Image 1", image_1)
cv2.imshow("Image 2", image_2)
cv2.imshow("Matching result", matching_result)
cv2.waitKey(0)
cv2.destroyAllWindows()

The script use two file images 1.png and 2.png.
The result is an image composed of the two on which the areas of similitude are traced as detected by the mathematical algorithm.

Using the python module music21.

What is music21?
Music21 is a set of tools for helping scholars and other active listeners answer questions about music quickly and simply. If you’ve ever asked yourself a question like, “I wonder how often Bach does that” or “I wish I knew which band was the first to use these chords in this order,” or “I’ll bet we’d know more about Renaissance counterpoint (or Indian ragas or post-tonal pitch structures or the form of minuets) if I could write a program to automatically write more of them,” then music21 can help you with your work.
This toolkit for Computer-Aided Musical Analysis was developed at MIT by cuthbertLab. Michael Scott Cuthbert, Principal Investigator.
The development of music21 is supported by the generosity of the Seaver Institute and the NEH.
The tutorial today is about the python music21 module.
Let's start with the default pip tool to install this python module:

C:\Python364\Scripts>pip install --upgrade music21
Collecting music21
...
  Running setup.py install for music21 ... done
Successfully installed music21-5.5.0

The next step tells us to install some additional python modules:

C:\Python373>python.exe
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD64)]
 on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> from music21 import * 
music21: Certain music21 functions might need these optional packages: matplotlib,
 scipy;
if you run into errors, install them by following the instructions at
http://mit.edu/music21/doc/installing/installAdditional.html

Let's install these python modules:

C:\Python373\Scripts>pip install matplotlib
C:\Python373\Scripts>pip install scipy

Let's test and play a simple example (Bach’s BWV 66.6):

>>> from music21 import *
>>> s = corpus.parse('bwv66.6')
>>> sChords = s.chordify()
>>> sChords
...
>>> sChords.show('midi')

If you want to save it, use:

>>> sChords.write("midi", "bach6.mid")
'bach6.mid'

Another example is to play a note on guitar (C#):

from music21 import stream, instrument
from music21.note import Note
cd = Note("C#", type='quarter')
test = stream.Part()
test.insert(0, instrument.AcousticGuitar())
test_measure = stream.Measure()
test_measure.append(cd)
test.append(test_measure)
test.show('midi')

You can see all the instruments here.
This python module is very complex and can be used with additional software, see here.
More details can be found in the documentation.