GBARpy 1.0.15

Libraries and software to analyse data (the MCP's picture and CsI signals) in the framework of the GBAR experiment

GBARpy manual

This library is made to work with python 3.

Table of Contents

• Installation
  • Procedure for Unix and MacOS
  • Procedure for Windows
• Graphical User Interface
  • How to do an analysis
  • Set the MCP parameters
• MCPpicture library
  • Basic code for an analysis
  • More examples
  • BeamSpot class
    • Attributes
    • Methods

Installation

Procedure for Unix and MacOS

1. Install python 3
2. Check if pip is installed by entrering in the terminal

   python3 -m pip -V
   

   This command will give you the version of pip already installed. If not, install it
3. Install GBARpy

   python3 -m pip install GBARpy
   

4. Lauch GBARpy

   python3 -m GBARpy
   

If in the future, you need to update the version of GBARpy

python3 -m pip install --upgrade GBARpy

or to remove GBARpy

python3 -m pip uninstall GBARpy

Procedure for Windows

1. Install python 3
2. Check if pip is installed by entrering in the command prompt

   py -m pip -V
   

   This command will give you the version of pip already installed. If not, install it
3. Install GBARpy

   py -m pip install GBARpy
   

4. Lauch GBARpy

   py -m GBARpy
   

If in the future, you need to update the version of GBARpy

py -m pip install --upgrade GBARpy

or to remove GBARpy

py -m pip uninstall GBARpy

Graphical User Interface

How to do an analysis

GUI_1

1. Button to open an MCP picture.
2. Button to analyse the opened picture. If no picture has been opened, a dialog window will appears to invite you to open one.
3. To save as an image the result of the analysis. If no picture has been opened, a dialog window will appears to invite you to open one.
4. Button to open the window to set the MCP parameters
5. The MCP parameters one they have been set
6. The opened picture.
7. The result of the analysis.

GUI_2

GUI_3

GUI_4

Set the MCP parameters

The different parameters are

• Name: the name of your MCP
• R: the radius of the phosphore screen in mm (to define in the end the ratio mm/pixels)
• x0: the x position of the center of the phosphore screen (in pixels)
• y0: the y position of the center of the phosphore screen (in pixels)
• R0: the radius of the phosphore screen in pixels (to define in the end the ratio mm/pixels)
• ratio: the mm/pixels ratio; if R and R0 are defined, the ratio is automatically defined (ratio = R/R0)

To try the setting of the parameters, you can use the picture lumosmax.tif and the parameter file BGT_in.mcp. It is obviously better to have a picture where the border of your MCP are clearly visible to be able to set the parameters. In the future, a tool will be developped the find more easily these parameters.

GUI_5

The window posses 4 buttons:

• Set: to set the parameters and use them in the future analysis
• Save: to save the parameters as a binary file (.mcp) to be able to use the parameters during a future session
• Load: to import the parameters from a binary file previously created (.mcp file)
• Remove: to empty the form

Be careful: if you do not press the "set" buttons and close the MCP parameter windows, what you filled in the form is lost. On the contrary, pressing "remove" by accident is not a problem if you didn't press "set", in that case, close and re-open the window.

GUI_6

One ce parameters has been set, press "Analyse the picture". If "ratio" has been set, then the pixels are converted in mm. If all the parameters are set, then the border of your phosphore screen will be draw. In the future, these parameters will be used to improve the fitting of the pictures.

MCPpicture library

Basic code for an analysis

The examples corresponds to the python scripts MCP_example_basic.py and MCP_example_small_functions.py.

# Import the library
import GBARpy.MCPPicture as mcp
import matplotlib.pyplot as plt

Let's see how to import a beam spot picture (you can try with the file IMG0008.bmp):

# reshape analyse the beam spot
pic = mcp.BeamSpot("IMG0008.bmp",reshape=[1250,1000,600])
# the reshape array is a made of 3 elements: positionX, positionY, length (in pixel)
# if you don't want to reshape
pic = mcp.BeamSpot("IMG0008.bmp")

With this minimal code, the picture is analysed and the parameters of the fit can be obtained usign print(img). If it then possible to see and save the pictures as in the following example:

#plot the image
fig1 = plt.figure(figsize=(5,5))
plt.imshow(pic.img)
fig1.savefig("fig_example_1.pdf")

Example_1

Even if it can be written manually, there are line codes to plot the intgrals along the x-axis and the y-axis:

#plot the fit
fig2 = plt.figure(figsize=(5,5))
pic.plot_X_int()
pic.plot_Y_int()
fig2.savefig("fig_example_2.pdf")

Example_2

or to plot a summary of the fit:

#plot all
pic.plot("fig_example_3.pdf")

Example_3

More examples

To import the required librairies for the following examples:

# Import the library
import GBARpy.MCPPicture as mcp
import matplotlib.pyplot as plt

For some reasons, you might desire to import the picture without analysing it:

### Import the Picture
img = mcp.import_image("IMG0008.bmp")
fig4 = plt.figure(figsize=(5,5))
plt.imshow(img)
fig4.savefig("fig_example_4.png")

Example_4

### Import the Picture and reshape
img = mcp.import_image("IMG0008.bmp",reshape=[1250,1000,600])
fig5 = plt.figure(figsize=(5,5))
plt.imshow(img)
fig5.savefig("fig_example_5.png")

Example_5

Once the pictures imported as a 2D array, it it possible to get the integrals along the x or y axis

### Integrals along the X and Y axis
Px,Ix = mcp.integrate_picture_along_X(img)
Py,Iy = mcp.integrate_picture_along_Y(img)
fig6 = plt.figure(figsize=(10,5))
plt.subplot(121)
plt.imshow(img)
plt.subplot(122)
plt.plot(Px,Ix)
plt.plot(Py,Iy)
fig6.savefig("fig_example_6.png")

Example_6

and then, using the fit function defined in the library

### Fit of the integrals
poptX,perrX=mcp.fit_gaussian_offset_filtered(Px,Ix)
poptY,perrY=mcp.fit_gaussian_offset_filtered(Py,Iy)
fig7 = plt.figure(figsize=(5,5))
plt.plot(Px,Ix,'.',color='tab:red',ms=1)
plt.plot(Px,mcp.gaussian_offset(Px,*poptX),color='tab:red')
plt.plot(Py,Iy,'.',color='tab:blue',ms=1)
plt.plot(Py,mcp.gaussian_offset(Py,*poptY),color='tab:blue')
fig7.savefig("fig_example_7.png")

Example_7

BeamSpot class

Attributes

• BeamSpot.fname: string, file name of the picture
• BeamSpot.img: 2D array, picture as an array
• BeamSpot.pix: the pixels along the x axis
• BeamSpot.piy: the pixels along the y axis
• BeamSpot.Ix: array of floats, integral along the x axis
• BeamSpot.Iy: array of floatt, integral along the y axis
• BeamSpot.Ax: float, Amplitude, fit along the x axis
• BeamSpot.Ay: float, Amplitude, fit along the y axis
• BeamSpot.sigx: float, Sigma, fit along the x axis
• BeamSpot.sigy: float, Sigma, fit along the x axis
• BeamSpot.r0x: float, Center, fit along the x axis
• BeamSpot.r0y: float, Center, fit along the x axis
• BeamSpot.offsetx: float, offset, fit along the x axis
• BeamSpot.offsety: float, offset, fit along the x axis
• BeamSpot.poptx: array of floats, the parameters of the fit along the x-axis
• BeamSpot.perrx: array of floats, errors on the parameters of the fit along the x-axis
• BeamSpot.popty: array of floats, the parameters of the fit along the y-axis
• BeamSpot.perry: array of floats, errors on the parameters of the fit along the y-axis
• BeamSpot.reshape: array of int, the parameters to reshape, see help(import_image)

Methods

__init__(self,fname,reshape=[]): Constructor of the class

• Parameters
  • fname: string, file name of the picture, the accepted file format ["tif","jpg","jpeg","png","asc","bmp"]
  • reshape: array of 3 integers (optional), to reshape the pictures (square): x,y,length
• Example

  import GBARpy.MCPPicture as mcp
  bs = mcp.BeamSpot("name.tif")
  

__repr__(self): To represent the object as a string

• Returns
  • a string variable
• Example

  import GBARpy.MCPPicture as mcp
  bs = mcp.BeamSpot("name.tif")
  repr = bs.__repr__()
  #or to print it in the python console
  print(bs)
  

plot_Y_int(self,label=""): To plot the integral of the picture along the "y" axis

• Parameters
  • label: (optional) a string
• Example

  import GBARpy.MCPPicture as mcp
  bs = mcp.BeamSpot("name.tif")
  bs.plot_Y_int("Integral along the y-axis")
  

plot_X_int(self,label=""): To plot the integral of the picture along the "x" axis

• Parameters
  • label: (optional) a string
• Example

  import GBARpy.MCPPicture as mcp
  bs = mcp.BeamSpot("name.tif")
  bs.plot_X_int("Integral along the x-axis")
  

plot_X_int_revert(self): To plot the integral of the picture along the "x" axis and reverse the picture

• Example

  import GBARpy.MCPPicture as mcp
  bs = mcp.BeamSpot("name.tif")
  bs.plot_X_int("Integral along the x-axis")
  

plot(self,fname="",figsize=(12,10),fontsize=12,ftsizeticks=12): To plot the picture and the analysis

• Parameters
  • fname: string (optional), the name of the file to save the plot
  • figsize: tuple (size in inch X, Y) (optional), size of the figure
  • fontsize: int (optional), size of the font
  • ftsizeticks: int (optional), size of the ticks' font
• Returns
  • fig: a matplotlib.pyplot.figure
• Example

  import GBARpy.MCPPicture as mcp
  bs = mcp.BeamSpot("name.tif")
  fig = bs.plot("analysis.pdf")
  # or
  fig = bs.plot()
  fig.savefig("analysis.pdf")