Commit e426ec6e authored by Bryce Hepner's avatar Bryce Hepner
Browse files

end of day, no major findings

parent 824f26de

FPNprojstart.py

+34 −13
Original line number Original line Diff line number Diff line 
from functools import singledispatchmethod

from cv2 import mean

import numpy as np

import numpy as np

from WorkingPyDemo import *

from WorkingPyDemo import *

from Remove_Noise import *

from Remove_Noise import *
@@ -13,7 +11,7 @@ from sklearn.metrics import mean_squared_error 




scenes = remote_file_extractor("/media/elphel/NVME/lwir16-proc/te0607/scenes/")

scenes = remote_file_extractor("/media/elphel/NVME/lwir16-proc/te0607/scenes/")

images = remote_image_extractor(scenes)

images = remote_image_extractor(scenes)

images = find_only_in_channel(images, "5")

# images = find_only_in_channel(images, "5")

sftp_client = setup_remote_sftpclient()

sftp_client = setup_remote_sftpclient()

image_array = np.array(Image.open(sftp_client.open(images[250])))

image_array = np.array(Image.open(sftp_client.open(images[250])))

# image_array = np.array(Image.open(images[250])).astype(np.uint16)

# image_array = np.array(Image.open(images[250])).astype(np.uint16)
@@ -52,22 +50,30 @@ def intarray_to_uint32(int_array): 
# print(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[0:6])

# print(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[0:6])

frame_spacings = []

frame_spacings = []

signaltonoise = []

signaltonoise = []

information_array = np.zeros((len(images),3))

information_array = np.zeros((len(images),5))

def celcius_to_kelvin(celcius):

def celcius_to_kelvin(celcius):

    return celcius + 273.15

    return celcius + 273.15



last_image = np.array(Image.open(sftp_client.open(images[0]))).astype(np.uint16)

for i in range(len(images)):

for i in range(1,3000):

    image_array = np.array(Image.open(sftp_client.open(images[i]))).astype(np.uint16)

    image_array = np.array(Image.open(sftp_client.open(images[i]))).astype(np.uint16)

    current_frame_count = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[84:88])

    current_frame_count = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[84:88])

    frame_count_at_FFC = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[88:92])

    frame_count_at_FFC = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[88:92])

    # signaltonoise.append(1/np.std(image_array[1:]))

    # signaltonoise.append(1/np.std(image_array[1:]))

    information_array[i,0] = current_frame_count - frame_count_at_FFC

    information_array[i,0] = current_frame_count - frame_count_at_FFC

    # information_array[i,-1] = 1/np.std(image_array[1:])

    information_array[i,-1] = 4096/np.std(image_array[1:])

    information_array[i,-1] = mean_squared_error(gaussian_filter(image_array[1:],sigma=.4),image_array[1:])

    information_array[i,-2] = mean_squared_error(gaussian_filter(image_array[1:],sigma=.4),image_array[1:])

    # print(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[76:77])

    # print(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[76:77])

    # print("start")

    # print("start")

    information_array[i,1] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[94:96]) - \

    # information_array[i,1] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[94:96]) - \

    celcius_to_kelvin(intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[162:166]))

    # celcius_to_kelvin(intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[162:166]))

    information_array[i,1] = mean_squared_error(gaussian_filter(last_image[1:],sigma=.4),last_image[1:])

    # information_array[i,2] = 20*np.log10(np.std(image_array[1:]))

    if images[i][-7] == "1":

        information_array[i,2] = images[i][-7:-5]

    else:

        information_array[i,2] = images[i][-6:-5]

    # print(information_array[i,2])

    # information_array[i,3] = np.std(image_array[1:])

    # information_array[i,2] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[96:98])

    # information_array[i,2] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[96:98])

    # information_array[i,2] = celcius_to_kelvin(intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[162:166]))

    # information_array[i,2] = celcius_to_kelvin(intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[162:166]))

    # information_array[i,4] = information_array[i,1] - information_array[i,2]

    # information_array[i,4] = information_array[i,1] - information_array[i,2]
@@ -75,6 +81,7 @@ for i in range(len(images)): 
    # information_array[i,4] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[170:174])

    # information_array[i,4] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[170:174])

    # information_array[i,5] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[174:178])

    # information_array[i,5] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[174:178])

    # frame_spacings.append(current_frame_count - frame_count_at_FFC)

    # frame_spacings.append(current_frame_count - frame_count_at_FFC)

    last_image = np.array(Image.open(sftp_client.open(images[i]))).astype(np.uint16)

# print(np.argmin(signaltonoise))

# print(np.argmin(signaltonoise))

# print(np.argmax(signaltonoise))

# print(np.argmax(signaltonoise))

# print(np.min(abs(np.array(frame_spacings))))

# print(np.min(abs(np.array(frame_spacings))))
@@ -82,11 +89,25 @@ for i in range(len(images)): 








mask = information_array[:,0] > 0

mask = information_array[:,0] > 0

information_df = pd.DataFrame(information_array[mask],columns=["Frame_Spacing","Curr_Temp_Diff","Signal_to_Noise"])



information_df.to_csv("information_weird_array.csv")

information_df = pd.DataFrame(information_array[mask],columns=["Frame_Spacing","Last_MSE","ImageName","Signal_to_Noise","MSE"])

information_df = pd.read_csv("information_weird_array.csv")

information_df.to_csv("smaller_information_weird_array.csv")

information_df = pd.read_csv("smaller_information_weird_array.csv",index_col=0)

information_array = information_df.values

information_array = information_df.values

print(information_array[0,2])

plt.scatter(information_array[:,0],information_array[:,-1],s=1)

plt.scatter(information_array[:,0],information_array[:,-1],s=1)

plt.legend()

plt.xlabel("Frame_Spacing")

plt.ylabel("Signal_to_Noise")

plt.show()

colors = ["red","blue","green","orange","purple","brown","pink","black","grey","cyan","magenta","yellow","white","lime","teal","olive","maroon","navy","silver","gold","indigo","violet"]

secondmask = information_array[:,1] < 30000

print(np.unique(information_array[:,2]))

for g in np.unique(information_array[:,2]):

    i = np.where(information_array[:,2] == g)

    print(g)

    plt.scatter(information_array[:,1][secondmask][i],information_array[:,4][secondmask][i],s=1,label=g,color = colors[int(g)])



plt.legend()

plt.legend()

plt.xlabel("Frame_Spacing")

plt.xlabel("Frame_Spacing")

plt.ylabel("Signal_to_Noise")

plt.ylabel("Signal_to_Noise")

information_weird_array.csv

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smaller_information_weird_array.csv

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