anomaly_in_file = bool(anomaly_index)
if anomaly_in_file:
# Aliasing for brevity.
x = previous_dataset.index.size + anomaly_index[0]
dx = LOOKUP_RANGE
surrounding_data = dataset.iloc[x - dx: x + dx + 1]
latitudes = surrounding_data.latitude
longitudes = surrounding_data.longitude
points = list(zip(latitudes, longitudes))
reference = (latitudes.iloc[dx], longitudes.iloc[dx])
distances = np.array(list(map(lambda p: lambert(reference, p), points)))
distances[:LOOKUP_RANGE] *= -1
modis_cloud_top_height = surrounding_data["modis_cloud_top_height"].values
cal_cloud_top_height = surrounding_data["cal_cloud_top_height"].values
nan_mask = np.isnan(distances) | np.isnan(modis_cloud_top_height) | np.isnan(cal_cloud_top_height)
latitude_envelope_series[i] = latitudes
longitude_envelope_series[i] = longitudes
distance_series[i] = distances
modis_cloud_top_height_series[i] = modis_cloud_top_height
cal_cloud_top_height_series[i] = cal_cloud_top_height
else:
def calculate_azimuthal_angle(latitude_1: float, longitude_1: float,
latitude_2: float, longitude_2: float) -> float:
'''
Computes the azimuthal angle for a vector described by two points,
going from point (latitude_1, longitude_1) to point (latitude_2, longitude_2)
Parameters:
* latitude_1 (float) :
- Latiutde position for starting point of the vector
* longitude_1 (float) :
- Longitude position for starting point of the vector
* latitude_2 (float) :
- Latiutde position for end point of the vector
* longitude_2 (float) :
- Longitude position for end point of the vector
Return values:
* angle (float) :
- Units: degrees
- Azimuthal angle for the vector
'''
latitude_diff = latitude_2 - latitude_1
longitude_diff = longitude_2 - longitude_1
# if satellite is moving E or W along cadinal axes
if latitude_diff == 0:
# if satellite is moving E
if longitude_2 > longitude_1:
angle = 90
# if satellite is moving W
else:
angle = 270
return angle
# if satellite is moving N or S along cadinal axes
if longitude_diff == 0:
# if satellite is moving N
if latitude_2 > latitude_1:
angle = 0
# if satellite is moving S
else:
angle = 180
return angle
# if satellite is not moving along cardinal axes find the x and y component
# of the displacement vector between these two points calculated along the
# cardinal axes
point_start = np.array([(latitude_1, longitude_1)])
point_mid = np.array([(latitude_1, longitude_2)])
point_end = np.array([(latitude_2, longitude_2)])
# Lambert formula calculates distance between first and second point given
distance_x = lambert(point_start[0], point_mid[0])
distance_y = lambert(point_mid[0], point_end[0])
angle = np.degrees(np.arctan(distance_x / distance_y))
# Determine azimuthal angle based on whether latitude and longtitude decrease
# between the previous and next point for the anomaly
if latitude_diff < 0 and longitude_diff < 0:
angle = 180 + angle
elif longitude_diff < 0:
angle = 360 - angle
elif latitude_diff < 0:
angle = 180 - angle
return angle
if anomaly_in_file:
# Aliasing for brevity.
x = previous_dataset.index.size + anomaly_index[0]
dx = LOOKUP_RANGE
surrounding_data = dataset.iloc[x - dx:x + dx + 1]
latitudes = surrounding_data.latitude
longitudes = surrounding_data.longitude
points = list(zip(latitudes, longitudes))
reference = (latitudes.iloc[dx], longitudes.iloc[dx])
distances = np.array(
list(map(lambda p: lambert(reference, p), points)))
distances[:LOOKUP_RANGE] *= -1
modis_cloud_top_height = surrounding_data[
"modis_cloud_top_height"].values
cal_cloud_top_height = surrounding_data[
"cal_cloud_top_height"].values
layer_type = surrounding_data["layer_type"]
# convert CAL layer top height data to CALIPSO cloud top height data
for i in range(len(layer_type)):
# call on function from other script to identify layer type
vfm = vertical_feature_mask.classify_vfm(layer_type[i])
if vfm[0][0] != 2:
cal_cloud_top_height[i] = np.nan
# Calculate sign of dot product of the 2d vectors
sign_2d = dot_product_sign(displacement_azimuthal_angle, SAA)
#print("2D Sign: ", sign_2d)
# Determine which point to use in the slope calculation based on the sign
# If positive, use point before anomaly
if sign_2d > 0:
# Calculate azimuthal angle for the satellite displacement vector
slope_azimuthal_angle = calculate_azimuthal_angle(
prev_latitude, prev_longitude, anomaly_latitude,
anomaly_longitude)
distance_bween_points = lambert(
(anomaly_latitude, anomaly_longitude),
(prev_latitude, prev_longitude))
#read in cloud top height for the previous point
point_height = ncin["calipso_cloud_top_height"][i][prevIndex]
# find height in meters
height_diff_bween_points = (anomaly_height - point_height) * 1000
# Append 'True' to the prevPointUsed array, since the previous point was the one used to calculate slope
prevPointUsed = 1
# If negative, use point after anomaly
if sign_2d < 0:
# Calculate azimuthal angle for the satellite displacement vector