def make_non_virtual_temp_plots():
input_dir = path_util.get_project_root(
) / "calculations" / "calc_from_intermediate"
levels = [2]
data = dict()
print("Loading data")
for level in levels:
level_input_dir = input_dir / str(level)
data[level] = pd.read_csv(level_input_dir / "results-temp.csv",
sep="\t",
parse_dates=["time"])
output_dir = input_dir / "plots"
output_dir.mkdir(parents=True, exist_ok=True)
#kinematic_temp_flux
print("Kinematic temp flux")
args = PlotVariables(column="kinematic_temp_flux",
plot_title="Kinematic Temperature Flux (cov T, w)",
y_label="Flux (K*m/s)",
output_path=output_dir / "temp_flux.png")
plot_variable(data, args, only_surface=True)
# H_s
print("H_s")
args = PlotVariables(column="H_s",
plot_title="Sensible Heat Flux (H_s)",
y_label="Flux (W/m^2)",
output_path=output_dir / "sensible_heat_flux.png")
plot_variable(data, args, only_surface=True)
def load_processed_sonic_data(level, directory_override=None):
"""
Loads the sonic anemometer data (from an intermediate dataset you need to download!)
Column names are:
"time", "pressure", "rho_v", "u", "v", "w", "virtual_temp", "temp", "potential_temp"
:param level: 2, 5, or 10 - the height (in meters) of the dataset
:param directory_override: path to test data/nondefault data path if applicable
:return: pandas.DataFrame
"""
if type(directory_override) == bool and directory_override:
directory_override = get_project_root(
) / "data/2021 Final Project Data/SonicData/select_fields/1hr"
directory = _get_data_root_dir() / directory_override if directory_override \
else _get_sonic_data_dir() / "select_fields"
file = directory / ("sonic_data_" + str(level))
try:
df = pd.read_csv(file, sep="\t", parse_dates=["time"], index_col=0)
df["time"] = df["time"] - datetime.timedelta(days=366)
# df = df[(df["time"] >= pd.Timestamp('2018-09-13 21:00:00')) & (df["time"] <=
# pd.Timestamp('2018-09-14 06:00:00'))]
return df
except FileNotFoundError as e:
_handle_file_not_found(e, "select_fields")
def __init__(self):
with open(get_project_root() / "calculations" /
"calculations_config.yaml") as config_file:
config = yaml.load(config_file, Loader=yaml.FullLoader)
self.config = config
dirs = [self.get_figure_output_dir(), self.get_data_output_dir()]
for directory in dirs:
directory.mkdir(parents=True, exist_ok=True)
class TestTimeFormatter(unittest.TestCase):
test_dir = get_project_root() / "test" / "test_data"
def test_get_time_parsing_args_for_visibility_data(self):
kwargs = time_format.get_time_parsing_args_for_visibility_data()
test_file = self.test_dir / "mock_vis_time_data.csv"
df = pd.read_csv(test_file, sep="\t", **kwargs)
expected = datetime.datetime(2018, 9, 13, second=9)
self.assertEquals(expected, df.iloc[0]["time"])
def main(test=True):
intermediate_dir = path_util.get_project_root() / "data" / "intermediate"
output_dir = path_util.get_project_root(
) / "calculations" / "calc_from_intermediate" / "dissipation"
if test:
intermediate_dir = intermediate_dir / "test"
output_dir = output_dir / "test"
levels = [2, 5, 10]
datasets = dict()
for level in levels:
input_dir = intermediate_dir / str(level)
datasets[level] = load_datasets(input_dir)
dissipation_rates = dict()
etas = dict()
for level in levels:
dissipation_rates[level] = calculate_dissipation_rate(datasets, level)
etas[level] = calculate_kolmogorov_length(dissipation_rates[level])
output_dir.mkdir(parents=True, exist_ok=True)
plot_dissipation_rate(dissipation_rates, output_dir)
plot_eta(etas, output_dir)
def main(test=True):
intermediate_dir = path_util.get_project_root() / "data" / "intermediate"
output_dir = path_util.get_project_root(
) / "calculations" / "calc_from_intermediate"
if test:
intermediate_dir = intermediate_dir / "test"
output_dir = output_dir / "test"
tke_output_dir = output_dir / "tke_10"
levels = [2, 5, 10]
tke_10_min_sets = dict()
for level in levels:
input_dir = intermediate_dir / str(level)
datasets = load_datasets(input_dir)
if level == 2:
surface_data = datasets
# run_calculations(level, datasets, surface_data, output_dir / str(level), test)
tke_10_min_sets[level] = calculate_tke_10_min(
datasets, tke_output_dir / str(level))
plot_tke_10_min(tke_10_min_sets, tke_output_dir)
def get_sonic_data(level, test):
if level in sonic_data_cached:
return sonic_data_cached[level]
test_dir = None
if test:
test_dir = path_util.get_project_root(
) / "data/2021 Final Project Data/SonicData/select_fields/1hr"
print("Loading sonic data")
sonic_data = data_loader.load_processed_sonic_data(
level, directory_override=test_dir)
print("... Loaded")
sonic_data_cached[level] = sonic_data
return sonic_data
def main(test=True):
root_output_dir = path_util.get_project_root() / "data" / "intermediate"
override = None
if test:
root_output_dir = root_output_dir / "test"
override = _get_data_root_dir() / "SonicData/select_fields/1hr"
levels = [2, 5, 10]
for level in levels:
output_dir = root_output_dir / str(level)
output_dir.mkdir(parents=True, exist_ok=True)
sonic_data = load_processed_sonic_data(level, override)
## Change which methods to call
calculate_w_prime(sonic_data, output_dir / "w_prime.csv")
calculate_u_prime(sonic_data, output_dir / "u_prime.csv")
calculate_T_prime(sonic_data, output_dir / "T_prime.csv")
calculate_v_prime(sonic_data, output_dir / "v_prime.csv")
calculate_T_s_prime(sonic_data, output_dir / "T_s_prime.csv")
def plot_autocorrelation(T, U, V, W):
print("starting autocorrelations")
auto_corr_lag_U = calculate_autocorrelation(U)
print("finished u")
auto_corr_lag_V = calculate_autocorrelation(V)
print("finished v")
auto_corr_lag_W = calculate_autocorrelation(W)
print("finished w")
auto_corr_lag_T = calculate_autocorrelation(T)
print("finished T")
dt = 1 / 20 # 20 Hz
time = np.arange(1, int(len(U)*dt))
plt.plot(time, auto_corr_lag_U, label="U velocity")
plt.plot(time, auto_corr_lag_V, label="V velocity")
plt.plot(time, auto_corr_lag_W, label="W velocity")
plt.plot(time, auto_corr_lag_T, label="Virtual Temperature")
plt.ylabel('Autocorrelation')
plt.xlabel("Lag (seconds)")
plt.legend()
plt.grid()
plt.title("Autocorrelation vs. Lag")
plt.savefig(path_util.get_project_root() /
"AutocorrelationLag-{}.png".format(datetime.datetime.now()))
def _get_data_root_dir():
return get_project_root() / "data" / "2021 Final Project Data"
def get_output_root_dir(self):
return get_project_root() / self.config["output_dirs"]["root"]
def main(test=True):
input_dir = path_util.get_project_root(
) / "calculations" / "calc_from_intermediate"
if test:
input_dir = input_dir / "test"
levels = [2, 5, 10]
data = dict()
print("Loading data")
for level in levels:
level_input_dir = input_dir / str(level)
data[level] = pd.read_csv(level_input_dir / "results.csv",
sep="\t",
parse_dates=["time"])
output_dir = input_dir / "plots"
output_dir.mkdir(parents=True, exist_ok=True)
print("Making plots")
#kinematic_temp_flux
print("Kinematic temp flux")
args = PlotVariables(column="kinematic_temp_flux",
plot_title="Kinematic Temperature Flux (cov T_S, w)",
y_label="Flux (K*m/s)",
output_path=output_dir / "temp_flux.png")
plot_variable(data, args, only_surface=True)
# friction_velocity
print("Friction velocity")
args = PlotVariables(column="friction_velocity",
plot_title="Friction Velocity (u*)",
y_label="Friction Velocity (m/s)",
output_path=output_dir / "friction_velocity.png")
plot_variable(data, args)
# H_s
print("H_s")
args = PlotVariables(column="H_s",
plot_title="Sensible Heat Flux (H_s)",
y_label="Flux (W/m^2)",
output_path=output_dir / "sensible_heat_flux.png")
plot_variable(data, args, only_surface=True)
# tke
print("tke")
args = PlotVariables(column="tke",
plot_title="Turbulent Kinetic Energy (tke)",
y_label="tke (m^2/s^2)",
output_path=output_dir / "tke.png")
plot_variable(data, args)
# w*
print("w*")
args = PlotVariables(column="w_star",
plot_title="Deardorff/Convective Velocity (w*)",
y_label="w* (m/s)",
output_path=output_dir / "w_star.png")
plot_variable(data, args)
# L
print("L")
args = PlotVariables(column="L",
plot_title="Monin-Obukhov Length (L)",
y_label="L (m)",
output_path=output_dir / "obukhov_length.png")
plot_variable(data, args)
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import datetime
from utils import path_util
# file1 = r'C:\Users\makom\source\repos\EFD_Final_Project\EFD_Final_Project\select_fields\sonic_data_2'
# file2 = r'C:\Users\makom\source\repos\EFD_Final_Project\EFD_Final_Project\select_fields\sonic_data_5'
# file3 = r'C:\Users\makom\source\repos\EFD_Final_Project\EFD_Final_Project\select_fields\sonic_data_10'
file_dir = path_util.get_project_root(
) / "data" / "2021 Final Project Data" / "SonicData" / "select_fields"
file1 = file_dir / "sonic_data_2"
file2 = file_dir / "sonic_data_5"
file3 = file_dir / "sonic_data_10"
def load_data(file):
return pd.read_csv(file, sep="\t", index_col=0, parse_dates=["time"])
sonic2 = load_data(file1)
sonic5 = load_data(file2)
sonic10 = load_data(file3)
def correct_time(data):
data["time"] = data["time"] - datetime.timedelta(days=366)
# data = data[(data["time"] >= pd.Timestamp('2018-09-13 21:00:00')) &
# (data["time"] <= pd.Timestamp('2018-09-14 06:00:00'))]
return data
