Quickstart#
Welcome to PyDARTdiags! This guide will help you get started with the library, showing you how to import the modules, read observation sequence files, and perform basic operations. For more detailed information, refer to the User Guide.
import pydartdiags.obs_sequence.obs_sequence as obsq
from pydartdiags.stats import stats
from pydartdiags.matplots import matplots as mp
Specify an obs_sequence file to work with#
Note this example uses a small observation sequence file included with pyDARTdiags and uses the get_example_data function to retrieve it.
To use your own obs sequence file, simply remove the call to get_example_data and replace the value of datafile with the path to the file.
from pydartdiags.data import get_example_data
datafile = get_example_data("obs_seq.final.1000")
#### With your own obs seq:
# datafile = "my_obs_seq.final"
Read an obs_sequence file#
Read an observation sequence file into a DataFrame
obs_seq = obsq.ObsSequence(datafile)
Examine the DataFrame#
The ObsSequence object contains a Pandas DataFrame with all the observations and their associated metadata. You can access the DataFrame using the df attribute of the ObsSequence object. You can then use Pandas methods to explore the data, such as head() to view the first few rows.
obs_seq.df.head()
| obs_num | observation | prior_ensemble_mean | prior_ensemble_spread | prior_ensemble_member_1 | prior_ensemble_member_2 | prior_ensemble_member_3 | prior_ensemble_member_4 | prior_ensemble_member_5 | prior_ensemble_member_6 | ... | latitude | vertical | vert_unit | type | seconds | days | time | obs_err_var | bias | sq_err | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 230.16 | 231.310652 | 0.405191 | 231.304725 | 231.562874 | 231.333915 | 231.297690 | 232.081416 | 231.051063 | ... | 0.012188 | 23950.0 | pressure (Pa) | ACARS_TEMPERATURE | 75603 | 153005 | 2019-12-01 21:00:03 | 1.00 | 1.150652 | 1.324001 |
| 1 | 2 | 18.40 | 15.720527 | 0.630827 | 14.217207 | 15.558196 | 15.805599 | 16.594644 | 14.877743 | 16.334438 | ... | 0.012188 | 23950.0 | pressure (Pa) | ACARS_U_WIND_COMPONENT | 75603 | 153005 | 2019-12-01 21:00:03 | 6.25 | -2.679473 | 7.179578 |
| 2 | 3 | 1.60 | -4.932073 | 0.825899 | -5.270562 | -5.955998 | -4.209766 | -5.105016 | -4.669405 | -4.365305 | ... | 0.012188 | 23950.0 | pressure (Pa) | ACARS_V_WIND_COMPONENT | 75603 | 153005 | 2019-12-01 21:00:03 | 6.25 | -6.532073 | 42.667980 |
| 3 | 4 | 264.16 | 264.060532 | 0.035584 | 264.107192 | 264.097270 | 264.073212 | 264.047718 | 264.074140 | 264.019895 | ... | 0.010389 | 56260.0 | pressure (Pa) | ACARS_TEMPERATURE | 75603 | 153005 | 2019-12-01 21:00:03 | 1.00 | -0.099468 | 0.009894 |
| 4 | 5 | 11.60 | 10.134115 | 0.063183 | 10.067956 | 10.078798 | 10.120263 | 10.084885 | 10.135112 | 10.140610 | ... | 0.010389 | 56260.0 | pressure (Pa) | ACARS_U_WIND_COMPONENT | 75603 | 153005 | 2019-12-01 21:00:03 | 6.25 | -1.465885 | 2.148818 |
5 rows × 180 columns
Find the number of assimilated (used) observations vs. possible observations by type
obs_seq.possible_vs_used()
| type | possible | used | |
|---|---|---|---|
| 0 | ACARS_TEMPERATURE | 314 | 233 |
| 1 | ACARS_U_WIND_COMPONENT | 313 | 227 |
| 2 | ACARS_V_WIND_COMPONENT | 313 | 228 |
| 3 | AIRCRAFT_TEMPERATURE | 20 | 14 |
| 4 | AIRCRAFT_U_WIND_COMPONENT | 20 | 14 |
| 5 | AIRCRAFT_V_WIND_COMPONENT | 20 | 13 |
Examples#
The pyDARTdiags source comes with a set of examples in the examples directory.
The examples are also available as notebooks in the Examples Gallery.
The examples cover, Manipulating Observation Sequences, Visualizing Observation Sequences, and Diagnostics.