This repository contains the code for a package that converts TDMS files into pandas data frame for easy usage.
You can always get the up-to-date documentation with
from TDMSUtils import TDMSConverter as tdmsc
help(tdmsc)
The package can be easily used. An example of usage is
from TDMSUtils import TDMSConverter as tdmsc
tc = tdmsc.TDMSConverter('./ExampleData/')
df , total_number_of_channels = tc.convert_to_df(debug = False)
df_avg = tc.average_files(df, debug = False)
In the df pandas dataframe you will find all the measurements. An example of how it looks like is
data groupName channelName filename
0 x y 0 0.970000 -2.358... PD_Signal_0 Avg_Data_20190405 09:28:53.72 ./ExampleData/0_cold_next_day.tdms
0 x y 0 0.970000 -2.359... PD_Signal_0 Avg_Data_20190405 09:29:08.93 ./ExampleData/0_cold_next_day.tdms
0 x y 0 0.970000 -2.359... PD_Signal_0 Avg_Data_20190405 09:29:24.14 ./ExampleData/0_cold_next_day.tdms
0 x y 0 0.970000 -2.358... PD_Signal_0 Avg_Data_20190405 09:29:39.35 ./ExampleData/0_cold_next_day.tdms
0 x y 0 0.970000 -2.358... PD_Signal_0 Avg_Data_20190405 09:29:54.56 ./ExampleData/0_cold_next_day.tdms
For example to extract the x and y from the first channel (record in the dataframe) you could do something like this
x = df.iloc[0]['data']['x']
y = df.iloc[0]['data']['y']
or if you want to plot the average of all channels for each file you can do the following
for i in range(0, df_avg.shape[1]):
plt.plot(df_avg.iloc[i]['average']['x'], df_avg.iloc[i]['average']['y'],
label = df_avg.iloc[i]['filename'])
plt.legend()
plt.show()
Help on module TDMSUtils.TDMSConverter in TDMSUtils:
NAME TDMSUtils.TDMSConverter
CLASSES builtins.object TDMSConverter
class TDMSConverter(builtins.object)
| TDMSConverter(path)
|
| Methods defined here:
|
| __init__(self, path)
| Constructor for the converter
|
| average_files(self, df, debug=False)
| This function evaluate the average of all channels for all files.
|
| Input parameters:
| df: dataframe with all the files as obtained by the function
| convert_to_df() in this package.
|
| Return Values:
| A DataFrame that contains as many records as number of files. The
| Dataframe contains two columns: 'filemname' that contains the name
| of the file with the path, and 'average' that contains a pandas
| dataframe with two columns 'x' and 'y'.
|
| convert_to_df(self, debug=False)
| This function convert the content of the Files
| into a list. Each element of the list is a pandas
| dataframe with two columns: x,y.
|
| Input parameters:
| debug: a boolean. If False no debug text is printed. If
| True then debug informations are printed.
| data_files: a list with the list of the file names.
| Typically this is the value returned by the function
| generate_file_list().
|
| Return Value:
| 1. A pandas dataframe with 3 columns:
| 'data', 'groupName', and 'channelName'.
| 2. the number of channels as integer.
|
| generate_file_list(self, debug=False)
| Returns the list of file in the folder given as input
| as a list.
|
| Input parameters:
| path: a string with the folder name. If the data is in the same folder
| as the file, you can use "./"
| debug: a boolean variable (can be True or False). If False then
| no output is printed. If True then the list of files is printed.$
|
| get_channel_name(self, channelName)
| This is a helper function that from the output of the
| tdms package for the channel name like
|
| <TdmsObject with path /'PD_Signal_0'/'Avg_Data_20190404 15:30:45.93'>
|
| extract the actual channel name. In this case
|
| Avg_Data_20190404 15:30:45.93
|
| Input Parameters:
| channelName: a channelName as returned, for example, from a loop
| like This
|
| for channel in tdms_file.group_channels(group):
| ......
|
| Return Value:
| a string with the channel name, that can be used in the function
|
| tdms_file.object(str(group), channelName).data