Update Platform - Misalignment Of Coordinates

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Introduction

When working with echosounder data, it's essential to accurately align the coordinates with the ping times. However, in some cases, this alignment can be misaligned, leading to errors and inconsistencies in the data. In this article, we'll explore the issue of misaligned coordinates and provide a step-by-step guide on how to troubleshoot and resolve this problem.

Understanding the Issue

The error message indicates that there's a mismatch between the data types of the time variables and the ping times. Specifically, the time variables are of type DateTime64DType, while the ping times are of type Int64DType. This mismatch prevents the numpy library from performing the necessary operations, resulting in the error.

Reproducing the Issue

To reproduce the issue, we can use the following code:

import echopype as ep
import xarray as xr

# Files: 
https://svelantbruksuniversitet-my.sharepoint.com/:i:/g/personal/jonas_sundberg_slu_se/EdB-XIovEmNCkzgZs3NuYgMBk_ZauF9lPL0pZSniSHvJ8Q?e=hybsF2
https://svelantbruksuniversitet-my.sharepoint.com/:u:/g/personal/jonas_sundberg_slu_se/ES8A9W_04FpGlK7rwmcbEOcBf6nk7-u3FOVG63NoWYC2xg?e=afwJVC

# Open raw file
raw_path = "SLUAquaSailor2020V2-Phase0-D20200627-T060144-0.raw"
ed = ep.open_raw(raw_path, sonar_model="EK80", use_swap=True)

# Read coordinate data
# These coordinates align with the ping times in the raw file (ed.sonar.Beam_group1.ping_time)
new_coords = xr.open_dataset("example_coords.nc")

# Assign coordinates to the raw file
ed.update_platform(new_coords, 
        variable_mappings={"longitude": "longitude", "latitude": "latitude"})

This code will produce the following error:

numpy.exceptions.DTypePromotionError: The DType <class 'numpy.dtypes.DateTime64DType'> could not be promoted by <class 'numpy.dtypes.Int64DType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is `object`. The full list of DTypes is: (<class 'numpy.dtypes.DateTime64DType'>, <class 'numpy.dtypes.Int64DType'>)

Troubleshooting

To troubleshoot this issue, we need to understand the source of the problem. In this case, the issue is caused by the misalignment of the time stamps. To resolve this issue, we need to ensure that the time stamps are aligned correctly.

Step 1: Inspect the Data

The first step is to inspect the data and understand the structure of the time variables. In this case, we have three time variables (time1, time2, time3) each containing only one time stamp. This suggests that the issue is related to the misalignment of the time.

Step 2: Align the Time Stamps

To align the time stamps, we need to ensure that the time variables are of the same data type. In this case, we can convert the time variables to DateTime64DType using the following code:

ed.sonar.Beam_group1.ping_time = ed.sonar.Beam_group1.ping_time.astype('datetime64[ns]')

This code will convert the ping times to DateTime64DType, ensuring that they are aligned correctly.

Step 3: Update the Platform

Once the time stamps are aligned, we can update the platform using the following code:

ed.update_platform(new_coords, 
        variable_mappings={"longitude": "longitude", "latitude": "latitude"})

This code will assign the coordinates to the raw file, ensuring that they are aligned correctly.

Conclusion

Q: What is the cause of the misalignment of coordinates?

A: The cause of the misalignment of coordinates is due to the mismatch between the data types of the time variables and the ping times. Specifically, the time variables are of type DateTime64DType, while the ping times are of type Int64DType. This mismatch prevents the numpy library from performing the necessary operations, resulting in the error.

Q: How can I reproduce the issue?

A: To reproduce the issue, you can use the following code:

import echopype as ep
import xarray as xr

# Files: 
https://svelantbruksuniversitet-my.sharepoint.com/:i:/g/personal/jonas_sundberg_slu_se/EdB-XIovEmNCkzgZs3NuYgMBk_ZauF9lPL0pZSniSHvJ8Q?e=hybsF2
https://svelantbruksuniversitet-my.sharepoint.com/:u:/g/personal/jonas_sundberg_slu_se/ES8A9W_04FpGlK7rwmcbEOcBf6nk7-u3FOVG63NoWYC2xg?e=afwJVC

# Open raw file
raw_path = "SLUAquaSailor2020V2-Phase0-D20200627-T060144-0.raw"
ed = ep.open_raw(raw_path, sonar_model="EK80", use_swap=True)

# Read coordinate data
# These coordinates align with the ping times in the raw file (ed.sonar.Beam_group1.ping_time)
new_coords = xr.open_dataset("example_coords.nc")

# Assign coordinates to the raw file
ed.update_platform(new_coords, 
        variable_mappings={"longitude": "longitude", "latitude": "latitude"})

This code will produce the following error:

numpy.exceptions.DTypePromotionError: The DType <class 'numpy.dtypes.DateTime64DType'> could not be promoted by <class 'numpy.dtypes.Int64DType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is `object`. The full list of DTypes is: (<class 'numpy.dtypes.DateTime64DType'>, <class 'numpy.dtypes.Int64DType'>)

Q: How can I troubleshoot the issue?

A: To troubleshoot the issue, you need to understand the source of the problem. In this case, the issue is caused by the misalignment of the time stamps. To resolve this issue, you need to ensure that the time stamps are aligned correctly.

Step 1: Inspect the Data

The first step is to inspect the data and understand the structure of the time variables. In this case, we have three time variables (time1, time2, time3) each containing only one time stamp. This suggests that the issue is related to the misalignment of the time.

Step 2: Align the Time Stamps

To align the time stamps, you need to ensure that the time variables are of the same data type. In this case, you can convert the time variables toDateTime64DType` using the following code:

ed.sonar.Beam_group1.ping_time = ed.sonar.Beam_group1.ping_time.astype('datetime64[ns]')

This code will convert the ping times to DateTime64DType, ensuring that they are aligned correctly.

Step 3: Update the Platform

Once the time stamps are aligned, you can update the platform using the following code:

ed.update_platform(new_coords, 
        variable_mappings={"longitude": "longitude", "latitude": "latitude"})

This code will assign the coordinates to the raw file, ensuring that they are aligned correctly.

Q: What are the common issues that can cause misalignment of coordinates?

A: The common issues that can cause misalignment of coordinates are:

  • Mismatch between the data types of the time variables and the ping times.
  • Misalignment of the time stamps.
  • Incorrect assignment of coordinates to the raw file.

Q: How can I prevent misalignment of coordinates in the future?

A: To prevent misalignment of coordinates in the future, you can:

  • Ensure that the time variables are of the same data type.
  • Align the time stamps correctly.
  • Assign coordinates to the raw file correctly.

Q: What are the consequences of misalignment of coordinates?

A: The consequences of misalignment of coordinates are:

  • Errors and inconsistencies in the data.
  • Incorrect analysis and interpretation of the data.
  • Inaccurate results and conclusions.

Q: How can I resolve misalignment of coordinates?

A: To resolve misalignment of coordinates, you can:

  • Inspect the data and understand the structure of the time variables.
  • Align the time stamps correctly.
  • Update the platform using the correct code.

By following these steps and understanding the common issues that can cause misalignment of coordinates, you can prevent errors and inconsistencies in the data and ensure accurate analysis and interpretation of the data.