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import cv2 |
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import numpy as np |
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import os |
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import plotly.express as px |
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import plotly.figure_factory as ff |
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import datetime |
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import plotly.io as pio |
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import plotly.graph_objs as go |
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pio.kaleido.scope.mathjax = None |
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import math |
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from matplotlib.colors import LinearSegmentedColormap |
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from PIL import ImageColor |
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def distribute_glacier(list_of_samples): |
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list_of_glaciers = {} |
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for glacier in ['JAC']: |
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list_of_glaciers[glacier] = [sample for sample in list_of_samples if glacier in sample] |
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return list_of_glaciers |
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def create_dict(list_of_samples): |
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list_dict = [] |
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for sample in list_of_samples: |
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sample_split = sample.split('_') |
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finish_date = datetime.datetime.fromisoformat(sample_split[1]) + datetime.timedelta(days=50) |
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sample_dict = { |
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'Glacier': sample_split[0], |
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'Start': sample_split[1], |
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'Finish': str(finish_date), |
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'Satellite:': sample_split[2] |
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} |
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list_dict.append(sample_dict) |
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return list_dict |
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if __name__ == '__main__': |
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train_dir = '/home/ho11laqe/PycharmProjects/data_raw/fronts/train/' |
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test_dir = '/home/ho11laqe/PycharmProjects/data_raw/fronts/test/' |
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list_of_train_samples = os.listdir(train_dir) |
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list_of_test_samples = os.listdir(test_dir) |
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list_of_samples = list_of_train_samples + list_of_test_samples |
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list_of_glaciers = distribute_glacier(list_of_samples) |
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list_dict = create_dict(list_of_samples) |
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colormap = px.colors.sequential.Reds[-1::-1] |
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for glacier in list_of_glaciers: |
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print(glacier) |
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list_of_glaciers[glacier].sort() |
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if glacier in ['COL', 'Mapple']: |
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data_directory = test_dir |
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image_directory = '/home/ho11laqe/PycharmProjects/data_raw/sar_images/test/' |
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else: |
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data_directory = train_dir |
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image_directory = '/home/ho11laqe/PycharmProjects/data_raw/sar_images/train/' |
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if glacier == 'COL': |
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canvas = cv2.imread(image_directory + 'COL_2011-11-13_TDX_7_1_092.png') |
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shape = canvas.shape |
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elif glacier == 'JAC': |
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canvas = cv2.imread(image_directory + 'JAC_2009-06-21_TSX_6_1_005.png') |
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shape = canvas.shape |
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elif glacier == 'Jorum': |
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canvas = cv2.imread(image_directory + 'Jorum_2011-09-04_TSX_7_4_034.png') |
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shape = canvas.shape |
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elif glacier == 'Mapple': |
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canvas = cv2.imread(image_directory + 'Mapple_2008-10-13_TSX_7_2_034.png') |
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shape = canvas.shape |
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elif glacier == 'SI': |
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canvas = cv2.imread(image_directory + 'SI_2013-08-14_TSX_7_1_125.png') |
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elif glacier == 'Crane': |
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canvas = cv2.imread(image_directory + 'Crane_2008-10-13_TSX_7_3_034.png') |
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elif glacier == 'DBE': |
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canvas = cv2.imread(image_directory + 'DBE_2008-03-30_TSX_7_3_049.png') |
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else: |
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print('No image for background') |
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exit() |
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number_images = len(list_of_glaciers[glacier]) |
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kernel = np.ones((3, 3), np.uint8) |
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for i, image_name in enumerate(list_of_glaciers[glacier]): |
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front = cv2.imread(data_directory + image_name) |
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if front.shape != canvas.shape: |
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front = cv2.resize(front, (shape[1], shape[0])) |
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else: |
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front = cv2.dilate(front, kernel) |
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index = (1 - i / number_images) * (len(colormap) - 1) |
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up = math.ceil(index) |
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down = up - 1 |
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color_up = np.array(ImageColor.getcolor(colormap[up], 'RGB')) |
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color_down = np.array(ImageColor.getcolor(colormap[down], 'RGB')) |
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dif = up - down |
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color = color_up * (1 - dif) + color_down * dif |
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non_zeros = np.nonzero(front) |
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canvas[non_zeros[:2]] = np.uint([color for _ in non_zeros[0]]) |
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ref_x = 15000 / 7 |
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if glacier == 'COL': |
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image = canvas[750:, 200:2800] |
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new_shape = image.shape |
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res = 7 |
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scale = new_shape[1] / ref_x |
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fig = px.imshow(image, height=new_shape[0]- int(80 * scale), width=new_shape[1]) |
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legend = dict(thickness=int(50 * scale), tickvals=[-4.4, 4.4], |
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ticktext=['2011<br>(+0.8°C)', '2020<br>(+1.2°C)'], |
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outlinewidth=0) |
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elif glacier == 'Mapple': |
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image = canvas |
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new_shape = image.shape |
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res = 7 |
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scale = new_shape[1] / ref_x |
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fig = px.imshow(image, height=new_shape[0] - int(150 * scale), width=new_shape[1]) |
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legend = dict(thickness=int(50 * scale), tickvals=[-4.8, 4.8], ticktext=['2006', '2020 '], |
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outlinewidth=0) |
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elif glacier == 'Crane': |
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image = canvas[:2500,:] |
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new_shape = image.shape |
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res = 7 |
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scale = new_shape[1] / ref_x |
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fig = px.imshow(image, height=new_shape[0] - int(150 * scale), width=new_shape[1]) |
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legend = dict(thickness=int(50 * scale), tickvals=[-4.8, 4.8], ticktext=['2002', '2014'], |
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outlinewidth=0) |
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elif glacier == 'Jorum': |
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image = canvas |
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new_shape = image.shape |
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res = 7 |
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scale = new_shape[1] / ref_x |
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fig = px.imshow(image, height=new_shape[0] - int(240 * scale), width=new_shape[1]) |
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legend = dict(thickness=int(50 * scale), tickvals=[-4.8, 4.8], ticktext=['2003', '2020'], |
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outlinewidth=0) |
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elif glacier == 'DBE': |
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image = canvas[700:, 750:] |
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new_shape = image.shape |
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res = 7 |
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scale = new_shape[1] / ref_x |
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fig = px.imshow(image, height=new_shape[0] - int(150 * scale), width=new_shape[1]) |
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legend = dict(thickness=int(50 * scale), tickvals=[-4.7, 4.7], ticktext=['1995', '2014'], |
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outlinewidth=0) |
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elif glacier == 'SI': |
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image = canvas |
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new_shape = image.shape |
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res = 7 |
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scale = new_shape[0] / ref_x |
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fig = px.imshow(image, height=new_shape[0] - int(240 * scale), width=new_shape[1]) |
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legend = dict(thickness=int(50 * scale), tickvals=[-4.8, 4.8], ticktext=['1995', '2014'], |
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outlinewidth=0) |
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elif glacier == 'JAC': |
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image = canvas[:, :] |
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new_shape = image.shape |
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res = 6 |
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scale = new_shape[1] / ref_x |
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fig = px.imshow(image, height=new_shape[0] - int(340 * scale), width=new_shape[1]) |
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legend = dict(thickness=int(50 * scale), tickvals=[-4.6, 4.7], |
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ticktext=['2009<br>(+0.7°C)', '2015<br>(+0.9°C)'], |
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outlinewidth=0) |
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else: |
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fig = px.imshow(canvas) |
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res = 7 |
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scale = 1 |
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colorbar_trace = go.Scatter(x=[None], |
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y=[None], |
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mode='markers', |
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marker=dict( |
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colorscale=colormap[::-1], |
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showscale=True, |
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cmin=-5, |
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cmax=5, |
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colorbar=legend |
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), |
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hoverinfo='none' |
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) |
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fig.update_layout(yaxis=dict(tickmode='array', |
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tickvals=[0, 5000 / res, 10000 / res, 15000 / res, 20000 / res, 25000 / res], |
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ticktext=[0, 5, 10, 15, 20, 25], |
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title='km')) |
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fig.update_layout(xaxis=dict(tickmode='array', |
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tickvals=[0, 5000 / res, 10000 / res, 15000 / res, 20000 / res, 25000 / res], |
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ticktext=[0, 5, 10, 15, 20, 25], |
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title='km')) |
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fig.update_xaxes(tickfont=dict(size=int(40 * scale))) |
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fig.update_yaxes(tickfont=dict(size=int(40 * scale))) |
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fig.update_layout(font=dict(size=int(60 * scale), family="Computer Modern")) |
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fig.update_coloraxes(colorbar_x=0) |
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fig['layout']['xaxis']['title']['font']['size'] = int(60 * scale) |
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fig['layout']['yaxis']['title']['font']['size'] = int(60 * scale) |
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fig['layout']['showlegend'] = False |
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fig.add_trace(colorbar_trace) |
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fig.write_image('output/' + glacier + "_front_change.pdf", format='pdf') |
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