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Python library for reading and writing map gridded data using ZMAP Plus ASCII Grid format

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zmapio: reading and writing ZMAP Plus Grid files

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To install:

$ pip install zmapio

Basic usage of zmapio

import matplotlib.pyplot as plt
import numpy as np
from zmapio import ZMAPGrid
%matplotlib inline

Reading a ZMAP file:

z_file = ZMAPGrid('./examples/NSLCU.dat')

Accessing the comments header:

for c in z_file.comments:
    print(c)
Landmark Zmap grid file name:   .DATANSLCU.dat
Created/converted by Oasis Montaj, Geosoft Inc.

Plotting the grid data:

z_file.plot()

https://raw.githubusercontent.com/abduhbm/zmapio/master/_static/output_9_1.png

Counts for rows and columns:

z_file.no_cols, z_file.no_rows
(435, 208)

Shape for z-values:

z_file.z_values.shape
(208, 435)

Exporting to CSV file:

z_file.to_csv('./output/output.csv')
head ./output/output.csv
-630000.0,2621000.0,-16481.9570313
-630000.0,2618000.0,-16283.9033203
-630000.0,2615000.0,-16081.5751953
-630000.0,2612000.0,-15856.7861328
-630000.0,2609000.0,-15583.7167969
-630000.0,2606000.0,-15255.734375
-630000.0,2603000.0,-14869.3769531
-630000.0,2600000.0,-14426.1513672
-630000.0,2597000.0,-13915.8769531
-630000.0,2594000.0,-13340.4677734

Exporting to WKT file:

z_file.to_wkt('./output/output.wkt', precision=2)

Exporting to GeoJSON file:

z_file.to_geojson('./output/output.json')

Exporting to Pandas Dataframe:

df = z_file.to_dataframe()
df.Z.describe()
count    90480.000000
mean     -5244.434235
std       4692.845490
min     -16691.371094
25%     -10250.590088
50%      -4003.433105
75%      -1320.896881
max       2084.417969
Name: Z, dtype: float64

Write a new ZMAP file as 3 nodes per line format:

z_file.write('./output/test.zmap', nodes_per_line=3)
head ./output/test.zmap
! Landmark Zmap grid file name:   .DATANSLCU.dat
! Created/converted by Oasis Montaj, Geosoft Inc.
@.DATANSLCU.dat, GRID, 3
20, 1e+30, , 7, 1
208, 435, -630000.0, 672000.0, 2000000.0, 2621000.0
0.0, 0.0, 0.0
@
      -16481.9570313      -16283.9033203      -16081.5751953
      -15856.7861328      -15583.7167969      -15255.7343750
      -14869.3769531      -14426.1513672      -13915.8769531

Creating a ZMAP object from string:

z_text = """
!
! File created by DMBTools2.GridFileFormats.ZmapPlusFile
!
@GRID FILE, GRID, 4
20, -9999.0000000, , 7, 1
6, 4, 0, 200, 0, 300
0.0, 0.0, 0.0
@
       -9999.0000000       -9999.0000000           3.0000000          32.0000000
          88.0000000          13.0000000
       -9999.0000000          20.0000000           8.0000000          42.0000000
          75.0000000           5.0000000
           5.0000000         100.0000000          35.0000000          50.0000000
          27.0000000           1.0000000
           2.0000000          36.0000000          10.0000000           6.0000000
           9.0000000       -9999.0000000
"""
z_t = ZMAPGrid(z_text)
z_t.plot()

https://raw.githubusercontent.com/abduhbm/zmapio/master/_static/output_28_1.png

Adding colorbar and colormap using matplotlib:

z_obj = ZMAPGrid('./examples/NStopo.dat')
fig=plt.figure(figsize=(12, 6))
z_obj.plot(cmap='jet')
plt.colorbar()

https://raw.githubusercontent.com/abduhbm/zmapio/master/_static/output_30_1.png

Creating a new ZMAP object from 2D-Numpy array with shape (no_cols, no_rows):

z_val = z_obj.z_values
print('Z-values shape: ', z_val.shape)
new_zgrid = ZMAPGrid(z_values=z_val, min_x=-630000.0000, max_x=672000.0000,
                     min_y=2000000.0000,  max_y=2621000.0000)
Z-values shape:  (435, 208)
new_zgrid.plot(cmap='gist_earth')

https://raw.githubusercontent.com/abduhbm/zmapio/master/_static/output_33_1.png

Customize writing a ZMAP file:

new_zgrid.comments = ['this is', 'a test']
new_zgrid.nodes_per_line = 4
new_zgrid.field_width = 15
new_zgrid.decimal_places = 3
new_zgrid.name = 'test'
new_zgrid.write('./output/new_z.dat')
head ./output/new_z.dat
!this is
!a test
@test, GRID, 4
15, 1e+30, , 3, 1
208, 435, -630000.0, 672000.0, 2000000.0, 2621000.0
0.0, 0.0, 0.0
@
        -67.214        -67.570        -67.147        -69.081
        -73.181        -74.308        -72.766        -72.034
        -70.514        -68.555        -66.195        -62.776

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