DAQData

Usage

Read and plot slow and fast data binary files from centrifuge experiments conducted at Center of Geotechnical Modeling at University of California Davis

Features

• Reads slow and fast data binary files.
• List downs all the sensors,channels,configuration list, sampling rate...
• Extract all data or a subset of a data within a time frame.
• Plot data directly from the binary file.
• supports reading and plotting large data files.

Installation

This package is availably via pypi:

pip install DAQData

Read meta data from the binary file

import DAQData as DQ;

# Centrifuge CGM (UC Davis) data file. Can be slow as well as fast data 
Data_File = "../Binary_Data_Files/07162019@124724@124752@999.0rpm.bin";

# By default the, 'Extract_Data' parameter is set to be True. If the files are
# very large and only meta data needs to be checked, the data extraction can be
# stooped by setting 'Extract_Data' parameter false. This would increase the
# execution speed but will not read any data 
Data_DAQ = DQ.DAQ(Data_File,Extract_Data=True);

# To print all the meta data 
print(Data_DAQ)


# Extracting meta data
FileName                      = Data_DAQ.FileName; # gets the filename
Sampling_Rate                 = Data_DAQ.Sampling_Rate; # gets Sampling_Rate
Number_of_Channels            = Data_DAQ.Number_of_Channels; # gets number of channels
Number_of_Hardware_Channels   = Data_DAQ.Number_of_Hardware_Channels; # gets number of hardware channels
Number_of_Xdcr_Serial_Numbers = Data_DAQ.Number_of_Xdcr_Serial_Numbers # gets number of Xdcr_Serial Numbers (also referred as sensors)
Channel_List                  = Data_DAQ.Channel_List; # gets the channel list
Hardware_Channel_List         = Data_DAQ.Hardware_Channel_List; # get the hardware channel list
Xdcr_Serial_Numbers_List      = Data_DAQ.Xdcr_Serial_Numbers_List; # gets the sensor list 
Number_of_Samples             = Data_DAQ.Number_of_Samples; # gets the total number of samples per sensor 
Data_Length                   = Data_DAQ.Data_Length; # gets the total data length in the binary file. Number_of_Samples*Number_of_sensors
Channel_Dictionary            = Data_DAQ.Channel_Dictionary; # returns a dictionary of channel name to the column number in data 
ExcelConfig                   = Data_DAQ.ExcelConfig; # return excel configuration file as a csv string 

Extract data on demand

import DAQData as DQ;

Data_File = "../Binary_Data_Files/07162019@124724@124752@999.0rpm.bin";
Data_DAQ  = DQ.DAQ(Data_File,Extract_Data=True);


# If the 'Extract_Data' parameter is True, the whole data is already read and extracted and can be easily retrieved as
Time_Data  = Data_DAQ.Time_Data;    # 1=D array 
Sensor_Data = Data_DAQ.Sensor_Data; # 2-D numpy array

# If the 'Extract_Data' parameter was initially set to False, the data can be extracted on demand by defining the start and end time
# ..... Time_Data, Sesnor_Data = Data_DAQ.Extract(Start_Time=0, End_Time=10)
# To extract the whole data, set the start time to be 0 and end time to be Number_of_Samples/Sampling_Rate

Data_DAQ  = DQ.DAQ(Data_File,Extract_Data=False);
Time_Data,Sensor_Data = Data_DAQ.Extract(Start_Time=0,End_Time=Number_of_Samples/Sampling_Rate);

# print(Sensor_Data.shape) # would return the same length of data as above 

Plot data

import DAQData as DQ;

Data_File = "../Binary_Data_Files/07162019@124724@124752@999.0rpm.bin";
Data_DAQ  = DQ.DAQ(Data_File,Extract_Data=True);

Channel_Index = Data_DAQ.get_Channel_Index(Channel_Name='ICP1-0');
ICP10_Data    = Sensor_Data[:,Channel_Index];
Sensor_Name   = Xdcr_Serial_Numbers_List[Channel_Index];

import matplotlib.pyplot as plt;

plt.figure(figsize=(8,3));
plt.plot(Time_Data,ICP10_Data,'k',label=Sensor_Name);
plt.legend(loc='best')
plt.grid(axis='both', which='major', ls='-')
plt.grid(axis='both', which='minor', ls='--', alpha=0.4)
plt.minorticks_on()
plt.xlabel('Time [s]')
plt.ylabel('Acc [g]')
plt.ylim([-10,10])
plt.tight_layout();
plt.show();

Send your comments, bugs, issues and features to add to Sumeet Kumar Sinha at sumeet.kumar507@gmail.com. Please feel free to create issues on https://github.com/SumeetSinha/DAQData/issues