[SOLVED] Reading and plotting HDF5(.h5) file and showing map for a specific latitude and longitude

Issue

I got a HDF5 file from MOSDAC website named 3DIMG_30MAR2018_0000_L1B_STD.h5 and I’m tying to read the this file and visualize the TIR and VIS dataset in the file in map. Since I am new to programming I don’t have much idea how to do this for a specific location on the global data using the Latitude and longitude values. My problem statement is to show data for Indian region.

The coding I have done till now:

#Importing libraries`

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import h5py
import os
import netCDF4 as nc
import seaborn as sns
import geopandas as gpd  

#Reading and listing keys present in HDF

fn = '3DIMG_30MAR2018_0000_L1B_STD.h5' #filename (the ".h5" file)
f = h5py.File(fn)
list(f.keys())

#extract data from the HDF5 file
mir = f['IMG_MIR'][:]  #middle infra-red
swir = f['IMG_SWIR'][:] #shortwave IR
tir1 = f['IMG_TIR1'][:] #Thermal IR1
tir2 = f['IMG_TIR2'][:] #Thermal IR2
vis = f['IMG_VIS'][:]   #Visible count
wv = f['IMG_WV'][:]     #Water vapor count
lat = f['Latitude'][:] 
lon = f['Longitude'][:]
lat_vis = f['Latitude_VIS'][:]
lon_vis = f['Longitude_VIS'][:]
lat_wv = f['Latitude_WV'][:]
lon_wv = f['Longitude_WV'][:]

vis = f['IMG_MIR'][0,:,:]
fig,ax = plt.subplots(figsize=(10,10))
im1 = plt.imshow(vis)
plt.colorbar(im1)

tir1d = f['/IMG_TIR1'];
lat = f['/Latitude'];
lon = f['/Longitude'];
   
Lat = np.linspace(81.041527, -81.041527, 2805)
Lon = np.linspace(0.84329641, 163.15671, 2816)

shp = gpd.read_file(r'C:\Users\offic\shape\IND_adm0.shp')

%lat=0:gs:60;%INDIA
%lon=60:gs:100;
 import numpy as np
 import matplotlib.pyplot as plt
 from mpl_toolkits.basemap import Basemap

data = Dataset(r'C:\Users\offic\3DIMG_30MAR2018_0000_L1B_STD.h5')
data

Out: <class 'netCDF4._netCDF4.Dataset'>
root group (NETCDF4 data model, file format HDF5):
    conventions: CF-1.6
    title: 3DIMG_30MAR2018_0000_L1B
    institute: BES,SAC/ISRO,Ahmedabad,INDIA.
    source: BES,SAC/ISRO,Ahmedabad,INDIA.
    Unique_Id: 3DIMG_30MAR2018_0000
    Satellite_Name: INSAT-3D
    Sensor_Id: IMG
    Sensor_Name: IMAGER
    HDF_Product_File_Name: 3DIMG_30MAR2018_0000_L1B_STD.h5
    Output_Format: hdf5-1.8.8
    Station_Id: BES
    Ground_Station: BES,SAC/ISRO,Ahmedabad,INDIA.
    Product_Type: STANDARD(FULL DISK)
    Processing_Level: L1B
    Imaging_Mode: FULL FRAME
    Acquisition_Date: 30MAR2018
    Acquisition_Time_in_GMT: 0000
    Acquisition_Start_Time: 30-MAR-2018T00:00:08
    Acquisition_End_Time: 30-MAR-2018T00:26:58
    Product_Creation_Time: 2018-03-30T06:03:39
    Radiometric_Calibration_Type: LAB CALIBRATED
    Nominal_Altitude(km): 36000.0
    Observed_Altitude(km): 35787.8215
    Field_of_View(degrees): 17.973925
    Nominal_Central_Point_Coordinates(degrees)_Latitude_Longitude: [ 0. 82.]
    Attitude_Source: STAR
    Sun_Azimuth(Degrees): 86.314133
    Sat_Azimuth(Degrees): 286.793152
    Sat_Elevation(Degrees): 89.813721
    Sun_Elevation(Degrees): -6.010917
    FastScan_Linearity_Enabled: no
    SlowScan_Linearity_Enabled: no
    MCD_FS_Enabled: no
    MCD_SS_Enabled: no
    Yaw_Flip_Flag: Y
    Software_Version: 1.0
    TIR1_Gain_Mode: 2
    TIR2_Gain_Mode: 2
    MIR_Gain_Mode: 2
    WV_Gain_Mode: 3
    VIS_Gain_Mode: 2
    SWIR_Gain_Mode: 3
    TIR1_Acquisition_Mode: MAIN
    TIR2_Acquisition_Mode: MAIN
    MIR_Acquisition_Mode: MAIN
    WV_Acquisition_Mode: MAIN
    VIS_Acquisition_Mode: MAIN
    SWIR_Acquisition_Mode: MAIN
    left_longitude: 0.8432964
    right_longitude: 163.15671
    upper_latitude: 81.04153
    lower_latitude: -81.04153
    Datum: WGS84
    Ellipsoid: WGS84
    dimensions(sizes): GeoX(2805), GeoX1(1402), GeoX2(11220), GeoY(2816), GeoY1(1408), GeoY2(11264), GreyCount(1024), time(1)
    variables(dimensions): int32 GeoX(GeoX), int32 GeoX1(GeoX1), int32 GeoX2(GeoX2), int32 GeoY(GeoY), int32 GeoY1(GeoY1), int32 GeoY2(GeoY2), int32 GreyCount(GreyCount), uint16 IMG_MIR(time, GeoY, GeoX), float32 IMG_MIR_RADIANCE(GreyCount), float32 IMG_MIR_TEMP(GreyCount), uint16 IMG_SWIR(time, GeoY2, GeoX2), float32 IMG_SWIR_RADIANCE(GreyCount), uint16 IMG_TIR1(time, GeoY, GeoX), float32 IMG_TIR1_RADIANCE(GreyCount), float32 IMG_TIR1_TEMP(GreyCount), uint16 IMG_TIR2(time, GeoY, GeoX), float32 IMG_TIR2_RADIANCE(GreyCount), float32 IMG_TIR2_TEMP(GreyCount), uint16 IMG_VIS(time, GeoY2, GeoX2), float32 IMG_VIS_ALBEDO(GreyCount), float32 IMG_VIS_RADIANCE(GreyCount), uint16 IMG_WV(time, GeoY1, GeoX1), float32 IMG_WV_RADIANCE(GreyCount), float32 IMG_WV_TEMP(GreyCount), int16 Latitude(GeoY, GeoX), int32 Latitude_VIS(GeoY2, GeoX2), int16 Latitude_WV(GeoY1, GeoX1), int16 Longitude(GeoY, GeoX), int32 Longitude_VIS(GeoY2, GeoX2), int16 Longitude_WV(GeoY1, GeoX1), <class 'str'> SCAN_LINE_TIME(GeoY1), uint16 Sat_Azimuth(time, GeoY, GeoX), int16 Sat_Elevation(time, GeoY, GeoX), uint16 Sun_Azimuth(time, GeoY, GeoX), int16 Sun_Elevation(time, GeoY, GeoX), float64 time(time)
    groups: 

data.variables
Out: {'GeoX': <class 'netCDF4._netCDF4.Variable'>
 int32 GeoX(GeoX)
 unlimited dimensions: 
 current shape = (2805,)
 filling off,
 'GeoX1': <class 'netCDF4._netCDF4.Variable'>
 int32 GeoX1(GeoX1)
 unlimited dimensions: 
 current shape = (1402,)
 filling off,
 'GeoX2': <class 'netCDF4._netCDF4.Variable'>
 int32 GeoX2(GeoX2)
 unlimited dimensions: 
 current shape = (11220,)
 filling off,
 'GeoY': <class 'netCDF4._netCDF4.Variable'>
 int32 GeoY(GeoY)
 unlimited dimensions: 
 current shape = (2816,)
 filling off,
 'GeoY1': <class 'netCDF4._netCDF4.Variable'>
 int32 GeoY1(GeoY1)
 unlimited dimensions: 
 current shape = (1408,)
 filling off,
 'GeoY2': <class 'netCDF4._netCDF4.Variable'>
 int32 GeoY2(GeoY2)
 unlimited dimensions: 
 current shape = (11264,)
 filling off,
 'GreyCount': <class 'netCDF4._netCDF4.Variable'>
 int32 GreyCount(GreyCount)
 unlimited dimensions: 
 current shape = (1024,)
 filling off,
 'IMG_MIR': <class 'netCDF4._netCDF4.Variable'>
 uint16 IMG_MIR(time, GeoY, GeoX)
     long_name: Middle Infrared Count
     invert: true
     central_wavelength: 3.9313
     bandwidth: 0.2
     wavelength_unit: micron
     bits_per_pixel: 10
     resolution: 4.0
     resolution_unit: km
     _FillValue: 1023
     lab_radiance_scale_factor: 0.000283937
     lab_radiance_add_offset: -0.00401529
     lab_radiance_quad: 0.0
     lab_radiance_scale_factor_gsics: 0.000366208
     lab_radiance_add_offset_gsics: -0.00833466
     lab_radiance_quad_gsics: 0.0
     radiance_units: mW.cm-2.sr-1.micron-1
     coordinates: time Latitude Longitude
 unlimited dimensions: 
 current shape = (1, 2816, 2805)
 filling on,
 'IMG_MIR_RADIANCE': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_MIR_RADIANCE(GreyCount)
     long_name: Middle Infrared Radiance
     invert: true
     units: mW.cm-2.sr-1.micron-1
     _FillValue: 999.0
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'IMG_MIR_TEMP': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_MIR_TEMP(GreyCount)
     long_name: Middle Infrared Brightness Temperature
     invert: true
     units: K
     _FillValue: 999.0
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'IMG_SWIR': <class 'netCDF4._netCDF4.Variable'>
 uint16 IMG_SWIR(time, GeoY2, GeoX2)
     long_name: Shortwave Infrared Count
     invert: false
     central_wavelength: 1.625
     bandwidth: 0.15
     wavelength_unit: micron
     bits_per_pixel: 10
     resolution: 1.0
     resolution_unit: km
     _FillValue: 0
     lab_radiance_scale_factor: 0.007835
     lab_radiance_add_offset: -0.172166
     lab_radiance_quad: 0.0
     lab_radiance_scale_factor_gsics: 0.007835
     lab_radiance_add_offset_gsics: -0.172166
     lab_radiance_quad_gsics: 0.0
     radiance_units: mW.cm-2.sr-1.micron-1
     coordinates: time Latitude_VIS Longitude_VIS
 unlimited dimensions: 
 current shape = (1, 11264, 11220)
 filling on,
 'IMG_SWIR_RADIANCE': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_SWIR_RADIANCE(GreyCount)
     long_name: Shortwave Infrared Radiance
     invert: false
     units: mW.cm-2.sr-1.micron-1
     _FillValue: 999.0
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'IMG_TIR1': <class 'netCDF4._netCDF4.Variable'>
 uint16 IMG_TIR1(time, GeoY, GeoX)
     long_name: Thermal Infrared1 Count
     invert: true
     central_wavelength: 10.8288
     bandwidth: 1.0
     wavelength_unit: micron
     bits_per_pixel: 10
     resolution: 4.0
     resolution_unit: km
     _FillValue: 1023
     lab_radiance_scale_factor: 0.00163731
     lab_radiance_add_offset: -0.0199179
     lab_radiance_quad: 0.0
     lab_radiance_scale_factor_gsics: 0.00203982
     lab_radiance_add_offset_gsics: -0.118067
     lab_radiance_quad_gsics: 0.0
     radiance_units: mW.cm-2.sr-1.micron-1
     coordinates: time Latitude Longitude
 unlimited dimensions: 
 current shape = (1, 2816, 2805)
 filling on,
 'IMG_TIR1_RADIANCE': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_TIR1_RADIANCE(GreyCount)
     long_name: Thermal Infrared1 Radiance
     invert: true
     units: mW.cm-2.sr-1.micron-1
     _FillValue: 999.0
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'IMG_TIR1_TEMP': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_TIR1_TEMP(GreyCount)
     units: K
     _FillValue: 999.0
     long_name: Thermal Infrared1 Brightness Temperature
     invert: true
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'IMG_TIR2': <class 'netCDF4._netCDF4.Variable'>
 uint16 IMG_TIR2(time, GeoY, GeoX)
     long_name: Thermal Infrared2 Count
     invert: true
     central_wavelength: 11.9593
     bandwidth: 1.0
     wavelength_unit: micron
     bits_per_pixel: 10
     resolution: 4.0
     resolution_unit: km
     _FillValue: 1023
     lab_radiance_scale_factor: 0.00143966
     lab_radiance_add_offset: -0.017032
     lab_radiance_quad: 0.0
     lab_radiance_scale_factor_gsics: 0.00181987
     lab_radiance_add_offset_gsics: -0.090434
     lab_radiance_quad_gsics: 0.0
     radiance_units: mW.cm-2.sr-1.micron-1
     coordinates: time Latitude Longitude
 unlimited dimensions: 
 current shape = (1, 2816, 2805)
 filling on,
 'IMG_TIR2_RADIANCE': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_TIR2_RADIANCE(GreyCount)
     _FillValue: 999.0
     long_name: Thermal Infrared2 Radiance
     invert: true
     units: mW.cm-2.sr-1.micron-1
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'IMG_TIR2_TEMP': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_TIR2_TEMP(GreyCount)
     long_name: Thermal Infrared2 Brightness Temperature
     invert: true
     units: K
     _FillValue: 999.0
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'IMG_VIS': <class 'netCDF4._netCDF4.Variable'>
 uint16 IMG_VIS(time, GeoY2, GeoX2)
     long_name: Visible Count
     invert: false
     central_wavelength: 0.65
     bandwidth: 0.25
     wavelength_unit: micron
     bits_per_pixel: 10
     resolution: 1.0
     resolution_unit: km
     _FillValue: 0
     lab_radiance_scale_factor: 0.0630857
     lab_radiance_add_offset: -1.85891
     lab_radiance_quad: 0.0
     lab_radiance_scale_factor_gsics: 0.0630857
     lab_radiance_add_offset_gsics: -1.85891
     lab_radiance_quad_gsics: 0.0
     radiance_units: mW.cm-2.sr-1.micron-1
     coordinates: time Latitude_VIS Longitude_VIS
 unlimited dimensions: 
 current shape = (1, 11264, 11220)
 filling on,
 'IMG_VIS_ALBEDO': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_VIS_ALBEDO(GreyCount)
     long_name: Visible Albedo
     invert: false
     units: %
 unlimited dimensions: 
 current shape = (1024,)
 filling on, default _FillValue of 9.969209968386869e+36 used,
 'IMG_VIS_RADIANCE': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_VIS_RADIANCE(GreyCount)
     long_name: Visible Radiance
     invert: false
     units: mW.cm-2.sr-1.micron-1
     _FillValue: 999.0
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'IMG_WV': <class 'netCDF4._netCDF4.Variable'>
 uint16 IMG_WV(time, GeoY1, GeoX1)
     long_name: Water Vapor Count
     invert: true
     central_wavelength: 6.8841
     bandwidth: 0.6
     wavelength_unit: micron
     bits_per_pixel: 10
     resolution: 8.0
     resolution_unit: km
     _FillValue: 1023
     lab_radiance_scale_factor: 0.000858417
     lab_radiance_add_offset: 0.000380381
     lab_radiance_quad: 0.0
     lab_radiance_scale_factor_gsics: 0.00125055
     lab_radiance_add_offset_gsics: -0.0299274
     lab_radiance_quad_gsics: 0.0
     radiance_units: mW.cm-2.sr-1.micron-1
     coordinates: time Latitude_WV Longitude_WV
 unlimited dimensions: 
 current shape = (1, 1408, 1402)
 filling on,
 'IMG_WV_RADIANCE': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_WV_RADIANCE(GreyCount)
     long_name: Water Vapor Radiance
     invert: true
     units: mW.cm-2.sr-1.micron-1
     _FillValue: 999.0
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'IMG_WV_TEMP': <class 'netCDF4._netCDF4.Variable'>
 float32 IMG_WV_TEMP(GreyCount)
     long_name: Water Vapor Brightness Temperature
     invert: true
     units: K
     _FillValue: 999.0
 unlimited dimensions: 
 current shape = (1024,)
 filling on,
 'Latitude': <class 'netCDF4._netCDF4.Variable'>
 int16 Latitude(GeoY, GeoX)
     long_name: latitude
     add_offset: 0.0
     scale_factor: 0.01
     units: degrees_north
     _FillValue: 32767
 unlimited dimensions: 
 current shape = (2816, 2805)
 filling on,
 'Latitude_VIS': <class 'netCDF4._netCDF4.Variable'>
 int32 Latitude_VIS(GeoY2, GeoX2)
     long_name: latitude
     add_offset: 0.0
     scale_factor: 0.001
     units: degrees_north
     _FillValue: 327670
 unlimited dimensions: 
 current shape = (11264, 11220)
 filling on,
 'Latitude_WV': <class 'netCDF4._netCDF4.Variable'>
 int16 Latitude_WV(GeoY1, GeoX1)
     long_name: latitude
     add_offset: 0.0
     scale_factor: 0.01
     units: degrees_north
     _FillValue: 32767
 unlimited dimensions: 
 current shape = (1408, 1402)
 filling on,
 'Longitude': <class 'netCDF4._netCDF4.Variable'>
 int16 Longitude(GeoY, GeoX)
     long_name: longitude
     units: degrees_east
     add_offset: 0.0
     scale_factor: 0.01
     _FillValue: 32767
 unlimited dimensions: 
 current shape = (2816, 2805)
 filling on,
 'Longitude_VIS': <class 'netCDF4._netCDF4.Variable'>
 int32 Longitude_VIS(GeoY2, GeoX2)
     add_offset: 0.0
     scale_factor: 0.001
     long_name: longitude
     units: degrees_east
     _FillValue: 327670
 unlimited dimensions: 
 current shape = (11264, 11220)
 filling on,
 'Longitude_WV': <class 'netCDF4._netCDF4.Variable'>
 int16 Longitude_WV(GeoY1, GeoX1)
     long_name: longitude
     add_offset: 0.0
     scale_factor: 0.01
     units: degrees_east
     _FillValue: 32767
 unlimited dimensions: 
 current shape = (1408, 1402)
 filling on,
 'SCAN_LINE_TIME': <class 'netCDF4._netCDF4.Variable'>
 vlen SCAN_LINE_TIME(GeoY1)
     long_name: Scan Time for Water Vapor Resolution
 vlen data type: <class 'str'>
 unlimited dimensions: 
 current shape = (1408,),
 'Sat_Azimuth': <class 'netCDF4._netCDF4.Variable'>
 uint16 Sat_Azimuth(time, GeoY, GeoX)
     long_name: Satellite Azimuth
     add_offset: 0.0
     scale_factor: 0.01
     units: degree
     _FillValue: 65535
     coordinates: time Latitude Longitude
 unlimited dimensions: 
 current shape = (1, 2816, 2805)
 filling on,
 'Sat_Elevation': <class 'netCDF4._netCDF4.Variable'>
 int16 Sat_Elevation(time, GeoY, GeoX)
     long_name: Satellite Elevation
     add_offset: 0.0
     units: degree
     scale_factor: 0.01
     _FillValue: 32767
     coordinates: time Latitude Longitude
 unlimited dimensions: 
 current shape = (1, 2816, 2805)
 filling on,
 'Sun_Azimuth': <class 'netCDF4._netCDF4.Variable'>
 uint16 Sun_Azimuth(time, GeoY, GeoX)
     long_name: Sun Azimuth
     add_offset: 0.0
     units: degree
     scale_factor: 0.01
     _FillValue: 65535
     coordinates: time Latitude Longitude
 unlimited dimensions: 
 current shape = (1, 2816, 2805)
 filling on,
 'Sun_Elevation': <class 'netCDF4._netCDF4.Variable'>
 int16 Sun_Elevation(time, GeoY, GeoX)
     long_name: Sun Elevation
     add_offset: 0.0
     scale_factor: 0.01
     units: degree
     _FillValue: 32767
     coordinates: time Latitude Longitude
 unlimited dimensions: 
 current shape = (1, 2816, 2805)
 filling on,
 'time': <class 'netCDF4._netCDF4.Variable'>
 float64 time(time)
     units: minutes since 2000-01-01 00:00:00
 unlimited dimensions: 
 current shape = (1,)
 filling off}

data.variables.keys()
Out: dict_keys(['GeoX', 'GeoX1', 'GeoX2', 'GeoY', 'GeoY1', 'GeoY2', 'GreyCount', 'IMG_MIR', 'IMG_MIR_RADIANCE', 'IMG_MIR_TEMP', 'IMG_SWIR', 'IMG_SWIR_RADIANCE', 'IMG_TIR1', 'IMG_TIR1_RADIANCE', 'IMG_TIR1_TEMP', 'IMG_TIR2', 'IMG_TIR2_RADIANCE', 'IMG_TIR2_TEMP', 'IMG_VIS', 'IMG_VIS_ALBEDO', 'IMG_VIS_RADIANCE', 'IMG_WV', 'IMG_WV_RADIANCE', 'IMG_WV_TEMP', 'Latitude', 'Latitude_VIS', 'Latitude_WV', 'Longitude', 'Longitude_VIS', 'Longitude_WV', 'SCAN_LINE_TIME', 'Sat_Azimuth', 'Sat_Elevation', 'Sun_Azimuth', 'Sun_Elevation', 'time'])

lats = data.variables['Latitude'][:]
lons = data.variables['Longitude'][:]
tir = data.variables['IMG_TIR1'][:]

lats.shape
Out:(2816, 2805)
lons.shape
Out:(2816, 2805)
tir.shape
Out:(1, 2816, 2805)

` I was not so sure about exact lat and lon that I want to plot so here's two of them. Although I think the 1st one is the correct one`

#mp = Basemap(projection = 'merc', 
            # llcrnrlon  = 68.766521,
            # llcrnrlat  = 3.323179,
            # urcrnrlon  = 100.202163, 
            # urcrnrlat  = 37.315495,
            # resolution = 'i')

mp = Basemap(projection = 'merc', 
             llcrnrlon  = 0.8432964,
             llcrnrlat  = -81.04153,
             urcrnrlon  = 163.15671, 
             urcrnrlat  = 81.04153,
             resolution = 'i')

` I'm getting an error in this line dk what it is`

lon, lat = np.meshgrid(lons, lats)
Out: ---------------------------------------------------------------------------
MemoryError                               Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_12060/1726626783.py in <module>
----> 1 lon, lat = np.meshgrid(lons, lats)

~\anaconda3\lib\site-packages\numpy\core\overrides.py in meshgrid(*args, **kwargs)

~\anaconda3\lib\site-packages\numpy\lib\function_base.py in meshgrid(copy, sparse, indexing, *xi)
   4947 
   4948     if copy:
-> 4949         output = [x.copy() for x in output]
   4950 
   4951     return output

~\anaconda3\lib\site-packages\numpy\lib\function_base.py in <listcomp>(.0)
   4947 
   4948     if copy:
-> 4949         output = [x.copy() for x in output]
   4950 
   4951     return output

~\anaconda3\lib\site-packages\numpy\ma\core.py in wrapped_method(self, *args, **params)
   2576     """
   2577     def wrapped_method(self, *args, **params):
-> 2578         result = getattr(self._data, funcname)(*args, **params)
   2579         result = result.view(type(self))
   2580         result._update_from(self)

MemoryError: Unable to allocate 227. TiB for an array with shape (7898880, 7898880) and data type float32

x,y = mp(lon, lat)
Out:---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_6908/3885003198.py in <module>
----> 1 x,y = mp(lon, lat)

NameError: name 'lon' is not defined

c_scheme = mp.pcolor(x, y, np.squeeze(tir1[0, :, :]), cmap = 'jet')

Out: ---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_6908/254152092.py in <module>
----> 1 c_scheme = mp.pcolor(x, y, np.squeeze(tir1[0, :, :]), cmap = 'jet')

NameError: name 'x' is not defined

Solution

Another code to obtain the same results:

import cv2
import numpy as np
import matplotlib.pyplot as plt

fn = '3DIMG_30MAR2018_0000_L1B_STD.h5' #filename (the ".h5" file) 
hf = h5py.File(fn, 'r')
hf.keys()
data = hf.get('IMG_TIR1')
data = data[0,:,:]
data=np.where(data>1022, np.nan, data)

Lat= hf.get('Latitude')
Lat = Lat[:,:]
Lat=Lat*0.0099999998
Lat=np.where(Lat>312, np.nan, Lat)

Long= hf.get('Longitude')
Long = Long[:,:]
Long=Long*0.0099999998
Long=np.where(Long>312, np.nan, Long)

X=Long[427:1421,804:1902]
Y=Lat[427:1421,804:1902]
Z=data[427:1421,804:1902]
fig = plt.figure(figsize=(10,10))
plt.pcolor(X, Y, Z)
plt.xlim(60, 100)
plt.ylim(0, 40)

fig = plt.figure(figsize=(10,10))
plt.pcolor(X, Y, Z)
plt.colorbar(label="Radiance", orientation="vertical")
plt.xlim(60, 100)
plt.ylim(0, 40)

#Threshold
Zn=np.where(Z>810, 1, 0)
fig = plt.figure(figsize=(10,10))
plt.pcolor(X, Y, Zn, cmap='jet', vmin=0, vmax=1)
plt.colorbar(label="Radiance", orientation="vertical")
plt.xlim(60, 100)
plt.ylim(0, 40)

Answered By – Black Viking

Answer Checked By – Marilyn (BugsFixing Volunteer)

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