def w_1():
wind_files = sorted(glob.glob("../data/csv_iw/*.csv"))
lon = latlon_ex.Lon
lat = latlon_ex.Lat
lon = np.array(lon)
lat = np.array(lat)
dirs = "../result/test_ice_wind/"
try:
os.makedirs(dirs)
except:
print('directory {} already exists'.format(dirs))
for item in wind_files:
data = calc_data.get_1day_iw_data(item)
save_name = dirs + item[15:21] + ".png"
print(save_name)
visualize.plot_map_once(
data.loc[:, ["iw_u", "iw_v"]],
data_type="type_wind",
show=False,
save_name=save_name,
vmax=None,
vmin=None,
cmap=None)
def main_data(start, end, **kwargs):
span = kwargs["span"]
region = kwargs["region"]
get_columns = kwargs["get_columns"]
accumulate = kwargs["accumulate"]
date_ax, date_ax_str = get_date_ax(start, end)
N = len(date_ax_str)
skipping_date_str = []
accumulate_data = []
data = []
for i, day in enumerate(date_ax_str):
print("{}/{}: {}".format(i + 1, N, day))
print("start: {}, end: {}".format(start, end))
year = day[2:4]
month = day[4:6]
#ファイル名の生成
wind_file_name = "../data/csv_w/ecm" + day[2:] + ".csv"
ice_file_name = "../data/csv_iw/" + day[2:] + ".csv"
ic0_145_file_name = "../data/csv_ic0/IC0_" + day + ".csv"
sit_145_file_name = "../data/csv_sit/SIT_" + day + ".csv"
coeff_file_name = "../data/csv_A_30/ssc_amsr_ads" + str(year) + str(
month) + "_" + str(span) + "_fin.csv"
hermert_file_name = "../data/csv_Helmert_30/Helmert_30_" + str(
day)[:6] + ".csv"
# wind10m_file_name = "../data/netcdf4/" + day[2:] + ".csv"
# t2m_file_name = "../data/netcdf4/" + day[2:] + ".csv"
skipping_boolean = ("coeff" not in get_columns) and (not all([
os.path.isfile(wind_file_name),
os.path.isfile(ice_file_name),
os.path.isfile(coeff_file_name)
]))
if ("ic0_145" in get_columns):
skipping_boolean = ("coeff" not in get_columns) and (not all([
os.path.isfile(wind_file_name),
os.path.isfile(ice_file_name),
os.path.isfile(coeff_file_name),
os.path.isfile(ic0_145_file_name)
]))
if ("sit_145" in get_columns):
skipping_boolean = ("coeff" not in get_columns) and (not all([
os.path.isfile(wind_file_name),
os.path.isfile(ice_file_name),
os.path.isfile(coeff_file_name),
os.path.isfile(sit_145_file_name)
]))
if skipping_boolean == True:
print("\tSkipping " + day + " file...")
date_ax_str.remove(day)
bb = date(int(day[:4]), int(day[4:6]), int(day[6:]))
date_ax.remove(bb)
skipping_date_str.append(day)
continue
data = pd.DataFrame({"data_idx": np.array(ocean_grid_145).ravel()})
if "ex_1" in get_columns:
print("\t{}\n\t{}\n\t{}\n\t{}".format(wind_file_name,
ice_file_name,
coeff_file_name))
tmp = calc_data.get_w_regression_data(wind_file_name,
ice_file_name,
coeff_file_name)
data = pd.concat([data, tmp], axis=1)
if "ex_2" in get_columns:
print("\t{}\n\t{}\n\t{}\n\t{}".format(wind_file_name,
ice_file_name,
hermert_file_name))
tmp = calc_data.get_w_hermert_data(wind_file_name, ice_file_name,
hermert_file_name)
data = pd.concat([data, tmp], axis=1)
if "w" in get_columns:
print("\t{}".format(wind_file_name))
tmp = calc_data.get_1day_w_data(wind_file_name)
data = pd.concat([data, tmp], axis=1)
if "iw" in get_columns:
print("\t{}".format(ice_file_name))
tmp = calc_data.get_1day_iw_data(ice_file_name)
data = pd.concat([data, tmp], axis=1)
if "ic0_145" in get_columns:
print("\t{}".format(ic0_145_file_name))
tmp = calc_data.get_1day_ic0_data(ic0_145_file_name)
data = pd.concat([data, tmp], axis=1)
if "sit_145" in get_columns:
print("\t{}".format(sit_145_file_name))
tmp = calc_data.get_1day_sit_data(sit_145_file_name)
data = pd.concat([data, tmp], axis=1)
if "coeff" in get_columns:
print("\t{}".format(coeff_file_name))
tmp = calc_data.get_1month_coeff_data(coeff_file_name)
data = pd.concat([data, tmp], axis=1)
if "hermert" in get_columns:
print("\t{}".format(hermert_file_name))
tmp = calc_data.get_1month_hermert_data(hermert_file_name)
data = pd.concat([data, tmp], axis=1)
"""
if "w10m" in get_columns:
tmp = calc_data.get_1day_w10m_data(wind10m_file_name)
data = pd.concat([data, tmp], axis=1)
if "t2m" in get_columns:
tmp = calc_data.get_1day_t2m_data(t2m_file_name)
data = pd.concat([data, tmp], axis=1)
"""
data = calc_data.get_masked_region_data(data, region)
if ("coeff" in get_columns):
print("\tSelected only coeff data. Getting out of the loop...")
continue
if accumulate == True:
data_1 = data.drop("data_idx", axis=1)
print("\t{}".format(data_1.columns))
accumulate_data.append(np.array(data_1))
if accumulate == True:
print("accumulate: True\tdata type: array")
return date_ax, date_ax_str, skipping_date_str, accumulate_data
else:
print("accumulate: False\tdata type: DataFrame")
return date_ax, date_ax_str, skipping_date_str, data
def test_w_iw_by_year():
dirs_1 = "../result_h/test/w_iw_by_year/"
dirs_2 = "../result_h/test/w_iw_by_year_without_ocean/"
if not os.path.exists(dirs_1):
os.makedirs(dirs_1)
if not os.path.exists(dirs_2):
os.makedirs(dirs_2)
y_list = [
"03", "04", "05", "06", "07", "08", "09", "10", "13", "14", "15", "16"
]
month_list = [
"01", "02", "03", "04", "05", "06", "07", "08", "09", "10", "11", "12"
]
for month in month_list:
print("************" + month + "************")
helmert_30_30_fname = "../data/csv_Helmert_both_30/Helmert_both_30_2003" + month + ".csv"
data_30 = pd.read_csv(helmert_30_30_fname)
#area_16_index = np.array(data_30.loc[data_30.area_label==16, :].index)
area_16_index = np.array(data_30[(data_30.area_label.isin(
list(range(17))))].dropna().index).tolist()
plot_grids = random.sample(area_16_index, 15)
print(plot_grids)
gw_list = []
iw_list = []
iw_ocean_list = []
for year in y_list:
helmert_file_name = "../data/csv_Helmert_both_30/Helmert_both_30_20" + year + month + ".csv"
gw_file_name = "../data/csv_w/ecm" + year + month + "15.csv"
iw_file_name = "../data/csv_iw/" + year + month + "15.csv"
helmert_data = calc_data.get_1month_helmert_data(helmert_file_name)
gw_data = calc_data.get_1day_w_data(gw_file_name)
iw_data = calc_data.get_1day_iw_data(iw_file_name)
gw_speed = np.array(gw_data.loc[plot_grids, "w_speed"])
iw_speed = np.array(iw_data.loc[plot_grids, "iw_speed"])
iw_ocean_u = np.array(iw_data.loc[plot_grids, "iw_u"] -
helmert_data.loc[plot_grids, "ocean_u"])
iw_ocean_v = np.array(iw_data.loc[plot_grids, "iw_v"] -
helmert_data.loc[plot_grids, "ocean_v"])
iw_speed_ocean = np.sqrt(iw_ocean_u**2 + iw_ocean_v**2)
gw_list.append(gw_speed)
iw_list.append(iw_speed)
iw_ocean_list.append(iw_speed_ocean)
gw_array = np.array(gw_list)
iw_array = np.array(iw_list)
iw_ocean_array = np.array(iw_ocean_list)
for i in range(len(plot_grids)):
gw = gw_array[:, i]
iw = iw_array[:, i]
iw_ocean = iw_ocean_array[:, i]
save_name_1 = dirs_1 + month + "15_grid_" + str(
plot_grids[i]) + ".png"
save_name_2 = dirs_2 + month + "15_grid_" + str(
plot_grids[i]) + ".png"
try:
sns.set_style("darkgrid")
sns.jointplot(x=gw, y=iw, kind="reg")
plt.savefig(save_name_1)
plt.close()
sns.set_style("darkgrid")
sns.jointplot(x=gw, y=iw_ocean, kind="reg")
plt.savefig(save_name_2)
plt.close()
except:
continue